Stargardt disease: towards developing a model to predict phenotype.

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Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S

2013-10-01

Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype-phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype-phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families.

Structural and Functional Phenotyping of the Failing Heart: Is the Left Ventricular Ejection Fraction Obsolete?

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Bristow, Michael R; Kao, David P; Breathett, Khadijah K; Altman, Natasha L; Gorcsan, John; Gill, Edward A; Lowes, Brian D; Gilbert, Edward M; Quaife, Robert A; Mann, Douglas L

2017-11-01

Diagnosis, prognosis, treatment, and development of new therapies for diseases or syndromes depend on a reliable means of identifying phenotypes associated with distinct predictive probabilities for these various objectives. Left ventricular ejection fraction (LVEF) provides the current basis for combined functional and structural phenotyping in heart failure by classifying patients as those with heart failure with reduced ejection fraction (HFrEF) and those with heart failure with preserved ejection fraction (HFpEF). Recently the utility of LVEF as the major phenotypic determinant of heart failure has been challenged based on its load dependency and measurement variability. We review the history of the development and adoption of LVEF as a critical measurement of LV function and structure and demonstrate that, in chronic heart failure, load dependency is not an important practical issue, and we provide hemodynamic and molecular biomarker evidence that LVEF is superior or equal to more unwieldy methods of identifying phenotypes of ventricular remodeling. We conclude that, because it reliably measures both left ventricular function and structure, LVEF remains the best current method of assessing pathologic remodeling in heart failure in both individual clinical and multicenter group settings. Because of the present and future importance of left ventricular phenotyping in heart failure, LVEF should be measured by using the most accurate technology and methodologic refinements available, and improved characterization methods should continue to be sought. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Spice: discovery of phenotype-determining component interplays

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Chen Zhengzhang

2012-05-01

Full Text Available Abstract Background A latent behavior of a biological cell is complex. Deriving the underlying simplicity, or the fundamental rules governing this behavior has been the Holy Grail of systems biology. Data-driven prediction of the system components and their component interplays that are responsible for the target system’s phenotype is a key and challenging step in this endeavor. Results The proposed approach, which we call System Phenotype-related Interplaying Components Enumerator (Spice, iteratively enumerates statistically significant system components that are hypothesized (1 to play an important role in defining the specificity of the target system’s phenotype(s; (2 to exhibit a functionally coherent behavior, namely, act in a coordinated manner to perform the phenotype-specific function; and (3 to improve the predictive skill of the system’s phenotype(s when used collectively in the ensemble of predictive models. Spice can be applied to both instance-based data and network-based data. When validated, Spice effectively identified system components related to three target phenotypes: biohydrogen production, motility, and cancer. Manual results curation agreed with the known phenotype-related system components reported in literature. Additionally, using the identified system components as discriminatory features improved the prediction accuracy by 10% on the phenotype-classification task when compared to a number of state-of-the-art methods applied to eight benchmark microarray data sets. Conclusion We formulate a problem—enumeration of phenotype-determining system component interplays—and propose an effective methodology (Spice to address this problem. Spice improved identification of cancer-related groups of genes from various microarray data sets and detected groups of genes associated with microbial biohydrogen production and motility, many of which were reported in literature. Spice also improved the predictive skill of the

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

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Ulrike Ober

Full Text Available Predicting organismal phenotypes from genotype data is important for plant and animal breeding, medicine, and evolutionary biology. Genomic-based phenotype prediction has been applied for single-nucleotide polymorphism (SNP genotyping platforms, but not using complete genome sequences. Here, we report genomic prediction for starvation stress resistance and startle response in Drosophila melanogaster, using ∼2.5 million SNPs determined by sequencing the Drosophila Genetic Reference Panel population of inbred lines. We constructed a genomic relationship matrix from the SNP data and used it in a genomic best linear unbiased prediction (GBLUP model. We assessed predictive ability as the correlation between predicted genetic values and observed phenotypes by cross-validation, and found a predictive ability of 0.239±0.008 (0.230±0.012 for starvation resistance (startle response. The predictive ability of BayesB, a Bayesian method with internal SNP selection, was not greater than GBLUP. Selection of the 5% SNPs with either the highest absolute effect or variance explained did not improve predictive ability. Predictive ability decreased only when fewer than 150,000 SNPs were used to construct the genomic relationship matrix. We hypothesize that predictive power in this population stems from the SNP-based modeling of the subtle relationship structure caused by long-range linkage disequilibrium and not from population structure or SNPs in linkage disequilibrium with causal variants. We discuss the implications of these results for genomic prediction in other organisms.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

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Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

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Le, Duc-Hau; Dao, Lan T M

2018-05-23

Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs. Therefore, prediction performance is highly dependent on how well the similarities can be captured. Previous studies have calculated the similarity between two diseases by mapping exactly each disease to a single Disease Ontology (DO) term, and then use a semantic similarity measure to calculate the similarity between them. However, the problem of this approach is that a disease can be described by more than one DO terms. Until now, there is no annotation database of DO terms for diseases except for genes. In contrast, Human Phenotype Ontology (HPO) is designed to fully annotate human disease phenotypes. Therefore, in this study, we constructed disease similarity networks/matrices using HPO instead of DO. Then, we used these networks/matrices as inputs of two representative machine learning-based and network-based ranking algorithms, that is, regularized least square and heterogeneous graph-based inference, respectively. The results showed that the prediction performance of the two algorithms on HPO-based is better than that on DO-based networks/matrices. In addition, our method can predict 11 novel cancer-associated lncRNAs, which are supported by literature evidence. Copyright © 2018 Elsevier Ltd. All rights reserved.

Forensic DNA Phenotyping: Predicting human appearance from crime scene material for investigative purposes.

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Kayser, Manfred

2015-09-01

Forensic DNA Phenotyping refers to the prediction of appearance traits of unknown sample donors, or unknown deceased (missing) persons, directly from biological materials found at the scene. "Biological witness" outcomes of Forensic DNA Phenotyping can provide investigative leads to trace unknown persons, who are unidentifiable with current comparative DNA profiling. This intelligence application of DNA marks a substantially different forensic use of genetic material rather than that of current DNA profiling presented in the courtroom. Currently, group-specific pigmentation traits are already predictable from DNA with reasonably high accuracies, while several other externally visible characteristics are under genetic investigation. Until individual-specific appearance becomes accurately predictable from DNA, conventional DNA profiling needs to be performed subsequent to appearance DNA prediction. Notably, and where Forensic DNA Phenotyping shows great promise, this is on a (much) smaller group of potential suspects, who match the appearance characteristics DNA-predicted from the crime scene stain or from the deceased person's remains. Provided sufficient funding being made available, future research to better understand the genetic basis of human appearance will expectedly lead to a substantially more detailed description of an unknown person's appearance from DNA, delivering increased value for police investigations in criminal and missing person cases involving unknowns. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Local connectome phenotypes predict social, health, and cognitive factors

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Michael A. Powell

2018-03-01

Full Text Available The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N = 841 of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP maps that could reliably predict a subset of subject attributes measured, including demographic, health, and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions. The local connectome is the pattern of fiber systems (i.e., number of fibers, orientation, and size within a voxel, and it reflects the proximal characteristics of white matter fascicles distributed throughout the brain. Here we show how variability in the local connectome is correlated in a principled way across individuals. This intersubject correlation is reliable enough that unique phenotype maps can be learned to predict between-subject variability in a range of social, health, and cognitive attributes. This work shows, for the first time, how the local connectome has both the sensitivity and the specificity to

Design of Biomedical Robots for Phenotype Prediction Problems.

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deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Sonis, Stephen T

2016-08-01

Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem.

Functional Dysregulation of CDC42 Causes Diverse Developmental Phenotypes.

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Martinelli, Simone; Krumbach, Oliver H F; Pantaleoni, Francesca; Coppola, Simona; Amin, Ehsan; Pannone, Luca; Nouri, Kazem; Farina, Luciapia; Dvorsky, Radovan; Lepri, Francesca; Buchholzer, Marcel; Konopatzki, Raphael; Walsh, Laurence; Payne, Katelyn; Pierpont, Mary Ella; Vergano, Samantha Schrier; Langley, Katherine G; Larsen, Douglas; Farwell, Kelly D; Tang, Sha; Mroske, Cameron; Gallotta, Ivan; Di Schiavi, Elia; Della Monica, Matteo; Lugli, Licia; Rossi, Cesare; Seri, Marco; Cocchi, Guido; Henderson, Lindsay; Baskin, Berivan; Alders, Mariëlle; Mendoza-Londono, Roberto; Dupuis, Lucie; Nickerson, Deborah A; Chong, Jessica X; Meeks, Naomi; Brown, Kathleen; Causey, Tahnee; Cho, Megan T; Demuth, Stephanie; Digilio, Maria Cristina; Gelb, Bruce D; Bamshad, Michael J; Zenker, Martin; Ahmadian, Mohammad Reza; Hennekam, Raoul C; Tartaglia, Marco; Mirzaa, Ghayda M

2018-01-17

Exome sequencing has markedly enhanced the discovery of genes implicated in Mendelian disorders, particularly for individuals in whom a known clinical entity could not be assigned. This has led to the recognition that phenotypic heterogeneity resulting from allelic mutations occurs more commonly than previously appreciated. Here, we report that missense variants in CDC42, a gene encoding a small GTPase functioning as an intracellular signaling node, underlie a clinically heterogeneous group of phenotypes characterized by variable growth dysregulation, facial dysmorphism, and neurodevelopmental, immunological, and hematological anomalies, including a phenotype resembling Noonan syndrome, a developmental disorder caused by dysregulated RAS signaling. In silico, in vitro, and in vivo analyses demonstrate that mutations variably perturb CDC42 function by altering the switch between the active and inactive states of the GTPase and/or affecting CDC42 interaction with effectors, and differentially disturb cellular and developmental processes. These findings reveal the remarkably variable impact that dominantly acting CDC42 mutations have on cell function and development, creating challenges in syndrome definition, and exemplify the importance of functional profiling for syndrome recognition and delineation. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genotype-phenotype associations in filaggrin loss-of-function mutation carriers

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Landeck, Lilla; Visser, Maaike; Kezic, Sanja; John, Swen M.

2013-01-01

Loss-of-function mutations in the filaggrin gene (FLG) have been reported to be associated with specific phenotypic characteristics such as hyperlinearity and keratosis pilaris. To study phenotypic features in patients with occupational irritant contact eczema of the hands in relation to FLG

Phenotypic and functional characterization of earthworm coelomocyte subsets

DEFF Research Database (Denmark)

Engelmann, Péter; Hayashi, Yuya; Bodo, Kornélia

2016-01-01

Flow cytometry is a common approach to study invertebrate immune cells including earthworm coelomocytes. However, the link between light-scatter- and microscopy-based phenotyping remains obscured. Here we show, by means of light scatter-based cell sorting, both subpopulations (amoebocytes...... amoebocytes and eleocytes, with the former being in favor of bacterial engulfment. This study has proved successful in linking flow cytometry and microscopy analysis and provides further experimental evidence of phenotypic and functional heterogeneity in earthworm coelomocyte subsets....

Phenotypic and functional plasticity of cells of innate immunity: macrophages, mast cells and neutrophils

DEFF Research Database (Denmark)

Galli, Stephen J; Borregaard, Niels; Wynn, Thomas A

2011-01-01

Hematopoietic cells, including lymphoid and myeloid cells, can develop into phenotypically distinct 'subpopulations' with different functions. However, evidence indicates that some of these subpopulations can manifest substantial plasticity (that is, undergo changes in their phenotype and function......). Here we focus on the occurrence of phenotypically distinct subpopulations in three lineages of myeloid cells with important roles in innate and acquired immunity: macrophages, mast cells and neutrophils. Cytokine signals, epigenetic modifications and other microenvironmental factors can substantially...... and, in some cases, rapidly and reversibly alter the phenotype of these cells and influence their function. This suggests that regulation of the phenotype and function of differentiated hematopoietic cells by microenvironmental factors, including those generated during immune responses, represents...

Phenotypic and functional plasticity of cells of innate immunity: macrophages, mast cells and neutrophils

DEFF Research Database (Denmark)

Galli, Stephen J; Borregaard, Niels; Wynn, Thomas A

2011-01-01

). Here we focus on the occurrence of phenotypically distinct subpopulations in three lineages of myeloid cells with important roles in innate and acquired immunity: macrophages, mast cells and neutrophils. Cytokine signals, epigenetic modifications and other microenvironmental factors can substantially......Hematopoietic cells, including lymphoid and myeloid cells, can develop into phenotypically distinct 'subpopulations' with different functions. However, evidence indicates that some of these subpopulations can manifest substantial plasticity (that is, undergo changes in their phenotype and function...... and, in some cases, rapidly and reversibly alter the phenotype of these cells and influence their function. This suggests that regulation of the phenotype and function of differentiated hematopoietic cells by microenvironmental factors, including those generated during immune responses, represents...

GWIS: Genome-Wide Inferred Statistics for Functions of Multiple Phenotypes

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Nieuwboer, H.A.; Pool, R.; Dolan, C.V.; Boomsma, D.I.; Nivard, M.G.

2016-01-01

Here we present a method of genome-wide inferred study (GWIS) that provides an approximation of genome-wide association study (GWAS) summary statistics for a variable that is a function of phenotypes for which GWAS summary statistics, phenotypic means, and covariances are available. A GWIS can be

The geometry of the Pareto front in biological phenotype space

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Sheftel, Hila; Shoval, Oren; Mayo, Avi; Alon, Uri

2013-01-01

When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade-off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption, the best-fitness solutions (termed the Pareto front) lie on simple low-dimensional shapes in trait space: line segments, triangles and other polygons. The vertices of these polygons are specialists at a single task. Here, we generalize this finding, by considering performance functions of general form, not necessarily functions that decay monotonically with distance from their peak. We find that, except for performance functions with highly eccentric contours, simple shapes in phenotype space are still found, but with mildly curving edges instead of straight ones. In a wide range of systems, complex data on multiple quantitative traits, which might be expected to fill a high-dimensional phenotype space, is predicted instead to collapse onto low-dimensional shapes; phenotypes near the vertices of these shapes are predicted to be specialists, and can thus suggest which tasks may be at play. PMID:23789060

Hypertriglyceridemic-waist phenotype predicts diabetes: a cohort study in Chinese urban adults

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Zhang Meilin

2012-12-01

Full Text Available Abstract Background Hypertriglycedemic-waist (HTGW phenotype is a simple and inexpensive screening parameter to identify people at increased risk for cardiovascular disease. We evaluated whether the HTGW phenotype predicts prediabetes and diabetes in Chinese urban adults. Methods Two thousand nine hundred and eight (2908 subjects including 1957 men and 951 women, aged 20 years and older, free of prediabetes and diabetes at baseline were enrolled in 2008 and followed for 3 years. Meanwhile, new cases of prediabetes and diabetes were identified via annual physical examination. Cox proportional hazards models were used to assess the association of HTGW phenotype with the incidence of prediabetes and diabetes. Results One thousand five hundred and thirty-three (1533 new prediabetes and 90 new diabetes cases were diagnosed during the follow-up period. The accumulated incidence of prediabetes and diabetes was 52.7% and 3.1%, respectively. Compared with the normal waist normal triglyceride (NWNT group, those in the HTGW group had higher incidence of prediabetes and diabetes for both men and women. The hazard ratio (HR for developing prediabetes in the presence of HTGW phenotype at baseline was 1.51 (95% confidence interval [CI] =1.04-2.19 in women, not in men (HR=1.01; 95% CI = 0.82-1.24, after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. The HR for developing diabetes were 4.46 (95% CI = 1.88-10.60 in men and 4.64 (95% CI = 1.20-17.97 in women for people who were HTGW phenotype at baseline, after adjusting for age, body mass index, systolic blood pressure, total cholesterol and low density lipoprotein-cholesterol. Conclusions The HTGW phenotype can be used as a simple screening approach to predict diabetes. By using this approach, it is possible to identify individuals at high-risk for diabetes, which is of great significance in reducing the incidence of diabetes among Chinese

Relationship between endophenotype and phenotype in ADHD

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Buitelaar Jan K

2008-01-01

Full Text Available Abstract Background It has been hypothesized that genetic and environmental factors relate to psychiatric disorders through the effect of intermediating, vulnerability traits called endophenotypes. The study had a threefold aim: to examine the predictive validity of an endophenotypic construct for the ADHD diagnosis, to test whether the magnitude of group differences at the endophenotypic and phenotypic level is comparable, and to investigate whether four factors (gender, age, IQ, rater bias have an effect (moderation or mediation on the relation between endophenotype and phenotype. Methods Ten neurocognitive tasks were administered to 143 children with ADHD, 68 non-affected siblings, and 120 control children (first-borns and 132 children with ADHD, 78 non-affected siblings, and 113 controls (second-borns (5 – 19 years. The task measures have been investigated previously for their endophenotypic viability and were combined to one component which was labeled 'the endophenotypic construct': one measure representative of endophenotypic functioning across several domains of functioning. Results The endophenotypic construct classified children with moderate accuracy (about 50% for each of the three groups. Non-affected children differed as much from controls at the endophenotypic as at the phenotypic level, but affected children displayed a more severe phenotype than endophenotype. Although a potentially moderating effect (age and several mediating effects (gender, age, IQ were found affecting the relation between endophenotypic construct and phenotype, none of the effects studied could account for the finding that affected children had a more severe phenotype than endophenotype. Conclusion Endophenotypic functioning is moderately predictive of the ADHD diagnosis, though findings suggest substantial overlap exists between endophenotypic functioning in the groups of affected children, non-affected siblings, and controls. Results suggest other

Vagal innervation is required for pulmonary function phenotype in Htr4-/- mice.

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House, John S; Nichols, Cody E; Li, Huiling; Brandenberger, Christina; Virgincar, Rohan S; DeGraff, Laura M; Driehuys, Bastiaan; Zeldin, Darryl C; London, Stephanie J

2017-04-01

Human genome-wide association studies have identified over 50 loci associated with pulmonary function and related phenotypes, yet follow-up studies to determine causal genes or variants are rare. Single nucleotide polymorphisms in serotonin receptor 4 ( HTR4 ) are associated with human pulmonary function in genome-wide association studies and follow-up animal work has demonstrated that Htr4 is causally associated with pulmonary function in mice, although the precise mechanisms were not identified. We sought to elucidate the role of neural innervation and pulmonary architecture in the lung phenotype of Htr4 -/- animals. We report here that the Htr4 -/- phenotype in mouse is dependent on vagal innervation to the lung. Both ex vivo tracheal ring reactivity and in vivo flexiVent pulmonary functional analyses demonstrate that vagotomy abrogates the Htr4 -/- airway hyperresponsiveness phenotype. Hyperpolarized 3 He gas magnetic resonance imaging and stereological assessment of wild-type and Htr4 -/- mice reveal no observable differences in lung volume, inflation characteristics, or pulmonary microarchitecture. Finally, control of breathing experiments reveal substantive differences in baseline breathing characteristics between mice with/without functional HTR4 in breathing frequency, relaxation time, flow rate, minute volume, time of inspiration and expiration and breathing pauses. These results suggest that HTR4's role in pulmonary function likely relates to neural innervation and control of breathing. Copyright © 2017 the American Physiological Society.

Adaptive evolution of molecular phenotypes

International Nuclear Information System (INIS)

Held, Torsten; Nourmohammad, Armita; Lässig, Michael

2014-01-01

Molecular phenotypes link genomic information with organismic functions, fitness, and evolution. Quantitative traits are complex phenotypes that depend on multiple genomic loci. In this paper, we study the adaptive evolution of a quantitative trait under time-dependent selection, which arises from environmental changes or through fitness interactions with other co-evolving phenotypes. We analyze a model of trait evolution under mutations and genetic drift in a single-peak fitness seascape. The fitness peak performs a constrained random walk in the trait amplitude, which determines the time-dependent trait optimum in a given population. We derive analytical expressions for the distribution of the time-dependent trait divergence between populations and of the trait diversity within populations. Based on this solution, we develop a method to infer adaptive evolution of quantitative traits. Specifically, we show that the ratio of the average trait divergence and the diversity is a universal function of evolutionary time, which predicts the stabilizing strength and the driving rate of the fitness seascape. From an information-theoretic point of view, this function measures the macro-evolutionary entropy in a population ensemble, which determines the predictability of the evolutionary process. Our solution also quantifies two key characteristics of adapting populations: the cumulative fitness flux, which measures the total amount of adaptation, and the adaptive load, which is the fitness cost due to a population's lag behind the fitness peak. (paper)

Migration Phenotype of Brain-Cancer Cells Predicts Patient Outcomes

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Chris L. Smith

2016-06-01

Full Text Available Glioblastoma multiforme is a heterogeneous and infiltrative cancer with dismal prognosis. Studying the migratory behavior of tumor-derived cell populations can be informative, but it places a high premium on the precision of in vitro methods and the relevance of in vivo conditions. In particular, the analysis of 2D cell migration may not reflect invasion into 3D extracellular matrices in vivo. Here, we describe a method that allows time-resolved studies of primary cell migration with single-cell resolution on a fibrillar surface that closely mimics in vivo 3D migration. We used this platform to screen 14 patient-derived glioblastoma samples. We observed that the migratory phenotype of a subset of cells in response to platelet-derived growth factor was highly predictive of tumor location and recurrence in the clinic. Therefore, migratory phenotypic classifiers analyzed at the single-cell level in a patient-specific way can provide high diagnostic and prognostic value for invasive cancers.

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

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Xin Wang

Full Text Available Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the 'search space' for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package

When should we expect microbial phenotypic traits to predict microbial abundances?

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Jeremy W. Fox

2012-08-01

Full Text Available Species’ phenotypic traits may predict their relative abundances. Intuitively, this is because locally-abundant species have traits making them well adapted to local abiotic and biotic conditions, while locally-rare species are not as well-adapted. But this intuition may not be valid. If competing species vary in how well-adapted they are to local conditions, why doesn’t the best-adapted species simply exclude the others entirely? But conversely, if species exhibit niche differences that allow them to coexist, then by definition there is no single best adapted species. Rather, demographic rates depend on species’ relative abundances, so that phenotypic traits conferring high adaptedness do not necessarily confer high abundance. I illustrate these points using a simple theoretical model incorporating adjustable levels of "adaptedness" and "niche differences". Even very small niche differences can weaken or even reverse the expected correlation between adaptive traits and abundance. Conversely, adaptive traits confer high abundance when niche differences are very strong. Future work should be directed towards understanding the link between phenotypic traits and frequency-dependence of demographic rates.

When should we expect microbial phenotypic traits to predict microbial abundances?

Science.gov (United States)

Fox, Jeremy W

2012-01-01

Species' phenotypic traits may predict their relative abundances. Intuitively, this is because locally abundant species have traits making them well-adapted to local abiotic and biotic conditions, while locally rare species are not as well-adapted. But this intuition may not be valid. If competing species vary in how well-adapted they are to local conditions, why doesn't the best-adapted species simply exclude the others entirely? But conversely, if species exhibit niche differences that allow them to coexist, then by definition there is no single best adapted species. Rather, demographic rates depend on species' relative abundances, so that phenotypic traits conferring high adaptedness do not necessarily confer high abundance. I illustrate these points using a simple theoretical model incorporating adjustable levels of "adaptedness" and "niche differences." Even very small niche differences can weaken or even reverse the expected correlation between adaptive traits and abundance. Conversely, adaptive traits confer high abundance when niche differences are very strong. Future work should be directed toward understanding the link between phenotypic traits and frequency-dependence of demographic rates.

A comprehensive dataset of genes with a loss-of-function mutant phenotype in Arabidopsis.

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Lloyd, Johnny; Meinke, David

2012-03-01

Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A preliminary list published nine years ago in Plant Physiology is outdated, and genome-wide phenotype information remains difficult to obtain. We describe here a comprehensive dataset of 2,400 genes with a loss-of-function mutant phenotype in Arabidopsis. Phenotype descriptions were gathered primarily from manual curation of the scientific literature. Genes were placed into prioritized groups (essential, morphological, cellular-biochemical, and conditional) based on the documented phenotypes of putative knockout alleles. Phenotype classes (e.g. vegetative, reproductive, and timing, for the morphological group) and subsets (e.g. flowering time, senescence, circadian rhythms, and miscellaneous, for the timing class) were also established. Gene identities were classified as confirmed (through molecular complementation or multiple alleles) or not confirmed. Relationships between mutant phenotype and protein function, genetic redundancy, protein connectivity, and subcellular protein localization were explored. A complementary dataset of 401 genes that exhibit a mutant phenotype only when disrupted in combination with a putative paralog was also compiled. The importance of these genes in confirming functional redundancy and enhancing the value of single gene datasets is discussed. With further input and curation from the Arabidopsis community, these datasets should help to address a variety of important biological questions, provide a foundation for exploring the relationship between genotype and phenotype in angiosperms, enhance the utility of Arabidopsis as a reference plant, and facilitate comparative studies with model genetic organisms.

Macrophage Phenotype and Function in Different Stages of Atherosclerosis

Science.gov (United States)

Tabas, Ira; Bornfeldt, Karin E.

2016-01-01

The remarkable plasticity and plethora of biological functions performed by macrophages have enticed scientists to study these cells in relation to atherosclerosis for more than 50 years, and major discoveries continue to be made today. It is now understood that macrophages play important roles in all stages of atherosclerosis, from initiation of lesions and lesion expansion, to necrosis leading to rupture and the clinical manifestations of atherosclerosis, to resolution and regression of atherosclerotic lesions. Lesional macrophages are derived primarily from blood monocytes, although recent research has shown that lesional macrophage-like cells can also be derived from smooth muscle cells. Lesional macrophages take on different phenotypes depending on their environment and which intracellular signaling pathways are activated. Rather than a few distinct populations of macrophages, the phenotype of the lesional macrophage is more complex and likely changes during the different phases of atherosclerosis and with the extent of lipid and cholesterol loading, activation by a plethora of receptors, and metabolic state of the cells. These different phenotypes allow the macrophage to engulf lipids, dead cells, and other substances perceived as danger signals; efflux cholesterol to HDL; proliferate and migrate; undergo apoptosis and death; and secrete a large number of inflammatory and pro-resolving molecules. This review article, part of the Compendium on Atherosclerosis, discusses recent advances in our understanding of lesional macrophage phenotype and function in different stages of atherosclerosis. With the increasing understanding of the roles of lesional macrophages, new research areas and treatment strategies are beginning to emerge. PMID:26892964

Network science meets respiratory medicine for OSAS phenotyping and severity prediction

Directory of Open Access Journals (Sweden)

Stefan Mihaicuta

2017-05-01

Full Text Available Obstructive sleep apnea syndrome (OSAS is a common clinical condition. The way that OSAS risk factors associate and converge is not a random process. As such, defining OSAS phenotypes fosters personalized patient management and population screening. In this paper, we present a network-based observational, retrospective study on a cohort of 1,371 consecutive OSAS patients and 611 non-OSAS control patients in order to explore the risk factor associations and their correlation with OSAS comorbidities. To this end, we construct the Apnea Patients Network (APN using patient compatibility relationships according to six objective parameters: age, gender, body mass index (BMI, blood pressure (BP, neck circumference (NC and the Epworth sleepiness score (ESS. By running targeted network clustering algorithms, we identify eight patient phenotypes and corroborate them with the co-morbidity types. Also, by employing machine learning on the uncovered phenotypes, we derive a classification tree and introduce a computational framework which render the Sleep Apnea Syndrome Score (SASScore; our OSAS score is implemented as an easy-to-use, web-based computer program which requires less than one minute for processing one individual. Our evaluation, performed on a distinct validation database with 231 consecutive patients, reveals that OSAS prediction with SASScore has a significant specificity improvement (an increase of 234% for only 8.2% sensitivity decrease in comparison with the state-of-the-art score STOP-BANG. The fact that SASScore has bigger specificity makes it appropriate for OSAS screening and risk prediction in big, general populations.

The Face of Noonan Syndrome: Does Phenotype Predict Genotype

Science.gov (United States)

Allanson, Judith E.; Bohring, Axel; Dorr, Helmuth-Guenther; Dufke, Andreas; Gillessen-Kaesbach, Gabrielle; Horn, Denise; König, Rainer; Kratz, Christian P.; Kutsche, Kerstin; Pauli, Silke; Raskin, Salmo; Rauch, Anita; Turner, Anne; Wieczorek, Dagmar; Zenker, Martin

2011-01-01

The facial photographs of 81 individuals with Noonan syndrome, from infancy to adulthood, have been evaluated by two dysmorphologists (JA and MZ), each of whom has considerable experience with disorders of the Ras/MAPK pathway. Thirty-two of this cohort have PTPN11 mutations, 21 SOS1 mutations, 11 RAF1 mutations, and 17 KRAS mutations. The facial appearance of each person was judged to be typical of Noonan syndrome or atypical. In each gene category both typical and unusual faces were found. We determined that some individuals with mutations in the most commonly affected gene, PTPN11, which is correlated with the cardinal physical features, may have a quite atypical face. Conversely, some individuals with KRAS mutations, which may be associated with a less characteristic intellectual phenotype and a resemblance to Costello and cardio-facio-cutaneous syndromes, can have a very typical face. Thus, the facial phenotype, alone, is insufficient to predict the genotype, but certain facial features may facilitate an educated guess in some cases. PMID:20602484

Genetics and evolution of function-valued traits: understanding environmentally responsive phenotypes.

Science.gov (United States)

Stinchcombe, John R; Kirkpatrick, Mark

2012-11-01

Many central questions in ecology and evolutionary biology require characterizing phenotypes that change with time and environmental conditions. Such traits are inherently functions, and new 'function-valued' methods use the order, spacing, and functional nature of the data typically ignored by traditional univariate and multivariate analyses. These rapidly developing methods account for the continuous change in traits of interest in response to other variables, and are superior to traditional summary-based analyses for growth trajectories, morphological shapes, and environmentally sensitive phenotypes. Here, we explain how function-valued methods make flexible use of data and lead to new biological insights. These approaches frequently offer enhanced statistical power, a natural basis of interpretation, and are applicable to many existing data sets. We also illustrate applications of function-valued methods to address ecological, evolutionary, and behavioral hypotheses, and highlight future directions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Role of dystrophin in airway smooth muscle phenotype, contraction and lung function.

Directory of Open Access Journals (Sweden)

Pawan Sharma

Full Text Available Dystrophin links the transmembrane dystrophin-glycoprotein complex to the actin cytoskeleton. We have shown that dystrophin-glycoprotein complex subunits are markers for airway smooth muscle phenotype maturation and together with caveolin-1, play an important role in calcium homeostasis. We tested if dystrophin affects phenotype maturation, tracheal contraction and lung physiology. We used dystrophin deficient Golden Retriever dogs (GRMD and mdx mice vs healthy control animals in our approach. We found significant reduction of contractile protein markers: smooth muscle myosin heavy chain (smMHC and calponin and reduced Ca2+ response to contractile agonist in dystrophin deficient cells. Immunocytochemistry revealed reduced stress fibers and number of smMHC positive cells in dystrophin-deficient cells, when compared to control. Immunoblot analysis of Akt1, GSK3β and mTOR phosphorylation further revealed that downstream PI3K signaling, which is essential for phenotype maturation, was suppressed in dystrophin deficient cell cultures. Tracheal rings from mdx mice showed significant reduction in the isometric contraction to methacholine (MCh when compared to genetic control BL10ScSnJ mice (wild-type. In vivo lung function studies using a small animal ventilator revealed a significant reduction in peak airway resistance induced by maximum concentrations of inhaled MCh in mdx mice, while there was no change in other lung function parameters. These data show that the lack of dystrophin is associated with a concomitant suppression of ASM cell phenotype maturation in vitro, ASM contraction ex vivo and lung function in vivo, indicating that a linkage between the DGC and the actin cytoskeleton via dystrophin is a determinant of the phenotype and functional properties of ASM.

Biogenetic mechanisms predisposing to complex phenotypes in parents may function differently in their children

DEFF Research Database (Denmark)

Kulminski, Alexander M; Arbeev, Konstantin G; Christensen, Kaare

2013-01-01

rule. Our findings suggest that biogenetic mechanisms underlying relationships among different phenotypes, even if they are causally related, can function differently in successive generations or in different age groups of biologically related individuals. The results suggest that the role of aging-related......This study focuses on the participants of the Long Life Family Study to elucidate whether biogenetic mechanisms underlying relationships among heritable complex phenotypes in parents function in the same way for the same phenotypes in their children. Our results reveal 3 characteristic groups...

Analysis of mammalian gene function through broad based phenotypic screens across a consortium of mouse clinics

Science.gov (United States)

Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl MJ; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie

2015-01-01

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse ES cell knockout resource provides a basis for characterisation of relationships between gene and phenotype. The EUMODIC consortium developed and validated robust methodologies for broad-based phenotyping of knockouts through a pipeline comprising 20 disease-orientated platforms. We developed novel statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no prior functional annotation. We captured data from over 27,000 mice finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. Novel phenotypes were uncovered for many genes with unknown function providing a powerful basis for hypothesis generation and further investigation in diverse systems. PMID:26214591

Differential functional readthrough over homozygous nonsense mutations contributes to the bleeding phenotype in coagulation factor VII deficiency.

Science.gov (United States)

Branchini, A; Ferrarese, M; Lombardi, S; Mari, R; Bernardi, F; Pinotti, M

2016-10-01

Essentials Potentially null homozygous Factor(F)7 nonsense mutations are associated to variable bleeding symptoms. Readthrough of p.Ser112X (life-threatening) and p.Cys132X (moderate) stop codons was investigated. Readthrough-mediated insertion of wild-type or tolerated residues produce functional proteins. Functional readthrough over homozygous F7 nonsense mutations contributes to the bleeding phenotype. Background Whereas the rare homozygous nonsense mutations causing factor (F)VII deficiency may predict null conditions that are almost completely incompatible with life, they are associated with appreciable differences in hemorrhagic symptoms. The misrecognition of premature stop codons (readthrough) may account for variable levels of functional full-length proteins. Objectives To experimentally evaluate the basal and drug-induced levels of FVII resulting from the homozygous p.Cys132X and p.Ser112X nonsense mutations that are associated with moderate (132X) or life-threatening (112X) symptoms, and that are predicted to undergo readthrough with (132X) or without (112X) production of wild-type FVII. Methods We transiently expressed recombinant FVII (rFVII) nonsense and missense variants in human embryonic kidney 293 cells, and evaluated secreted FVII protein and functional levels by ELISA, activated FX generation, and coagulation assays. Results The levels of functional FVII produced by p.Cys132X and p.Ser112X mutants (rFVII-132X, 1.1% ± 0.2% of wild-type rFVII; rFVII-112X, 0.5% ± 0.1% of wild-type rFVII) were compatible with the occurrence of spontaneous readthrough, which was magnified by the addition of G418 - up to 12% of the wild-type value for the rFVII-132X nonsense variant. The predicted missense variants arising from readthrough abolished (rFVII-132Trp/Arg) or reduced (rFVII-112Trp/Cys/Arg, 22-45% of wild-type levels) secretion and function. These data suggest that the appreciable rescue of p.Cys132X function was driven by reinsertion of the wild

In vitro atrazine exposure affects the phenotypic and functional maturation of dendritic cells

International Nuclear Information System (INIS)

Pinchuk, Lesya M.; Lee, Sang-Ryul; Filipov, Nikolay M.

2007-01-01

Recent data suggest that some of the immunotoxic effects of the herbicide atrazine, a very widely used pesticide, may be due to perturbations in dendritic cell (DC) function. As consequences of atrazine exposure on the phenotypic and functional maturation of DC have not been studied, our objective was, using the murine DC line, JAWSII, to determine whether atrazine will interfere with DC maturation. First, we characterized the maturation of JAWSII cells in vitro by inducing them to mature in the presence of growth factors and selected maturational stimuli in vitro. Next, we exposed the DC cell line to a concentration range of atrazine and examined its effects on phenotypic and functional maturation of DC. Atrazine exposure interfered with the phenotypic and functional maturation of DC at non-cytotoxic concentrations. Among the phenotypic changes caused by atrazine exposure was a dose-dependent removal of surface MHC-I with a significant decrease being observed at 1 μM concentration. In addition, atrazine exposure decreased the expression of the costimulatory molecule CD86 and it downregulated the expression of the CD11b and CD11c accessory molecules and the myeloid developmental marker CD14. When, for comparative purposes, we exposed primary thymic DC to atrazine, MHC-I and CD11c expression was also decreased. Phenotypic changes in JAWSII DC maturation were associated with functional inhibition of maturation as, albeit at higher concentrations, receptor-mediated antigen uptake was increased by atrazine. Thus, our data suggest that atrazine directly targets DC maturation and that toxicants such as atrazine that efficiently remove MHC-I molecules from the DC surface are likely to contribute to immune evasion

Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics.

Science.gov (United States)

de Angelis, Martin Hrabě; Nicholson, George; Selloum, Mohammed; White, Jacqui; Morgan, Hugh; Ramirez-Solis, Ramiro; Sorg, Tania; Wells, Sara; Fuchs, Helmut; Fray, Martin; Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl Mj; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie; Holmes, Chris; Steel, Karen P; Herault, Yann; Gailus-Durner, Valérie; Mallon, Ann-Marie; Brown, Steve Dm

2015-09-01

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.

Prediction of disease and phenotype associations from genome-wide association studies.

Directory of Open Access Journals (Sweden)

Stephanie N Lewis

Full Text Available Genome wide association studies (GWAS have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP. The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases.Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits.The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.

Microbial-Host Co-metabolites Are Prodromal Markers Predicting Phenotypic Heterogeneity in Behavior, Obesity, and Impaired Glucose Tolerance

Directory of Open Access Journals (Sweden)

Marc-Emmanuel Dumas

2017-07-01

Full Text Available The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50 and show that microbial-host co-metabolites are prodromal (i.e., early markers predicting future divergence in metabolic (obesity and glucose homeostasis and behavioral (anxiety and activity outcomes with 94%–100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO, a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT, and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity.

Stargardt disease: towards developing a model to predict phenotype

OpenAIRE

Heathfield, Laura; Lacerda, Miguel; Nossek, Christel; Roberts, Lisa; Ramesar, Rajkumar S

2013-01-01

Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype–phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual...

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

Association Between Vitamin D Status and COPD Phenotypes

DEFF Research Database (Denmark)

Moberg, M.; Ringbaek, T.; Roberts, N. B.

2014-01-01

It has been suggested that identifying phenotypes in chronic obstructive pulmonary disease (COPD) might improve treatment outcome and the accuracy of prediction of prognosis. In observational studies vitamin D deficiency has been associated with decreased pulmonary function, presence of emphysema...

Linking genotypes database with locus-specific database and genotype-phenotype correlation in phenylketonuria.

Science.gov (United States)

Wettstein, Sarah; Underhaug, Jarl; Perez, Belen; Marsden, Brian D; Yue, Wyatt W; Martinez, Aurora; Blau, Nenad

2015-03-01

The wide range of metabolic phenotypes in phenylketonuria is due to a large number of variants causing variable impairment in phenylalanine hydroxylase function. A total of 834 phenylalanine hydroxylase gene variants from the locus-specific database PAHvdb and genotypes of 4181 phenylketonuria patients from the BIOPKU database were characterized using FoldX, SIFT Blink, Polyphen-2 and SNPs3D algorithms. Obtained data was correlated with residual enzyme activity, patients' phenotype and tetrahydrobiopterin responsiveness. A descriptive analysis of both databases was compiled and an interactive viewer in PAHvdb database was implemented for structure visualization of missense variants. We found a quantitative relationship between phenylalanine hydroxylase protein stability and enzyme activity (r(s) = 0.479), between protein stability and allelic phenotype (r(s) = -0.458), as well as between enzyme activity and allelic phenotype (r(s) = 0.799). Enzyme stability algorithms (FoldX and SNPs3D), allelic phenotype and enzyme activity were most powerful to predict patients' phenotype and tetrahydrobiopterin response. Phenotype prediction was most accurate in deleterious genotypes (≈ 100%), followed by homozygous (92.9%), hemizygous (94.8%), and compound heterozygous genotypes (77.9%), while tetrahydrobiopterin response was correctly predicted in 71.0% of all cases. To our knowledge this is the largest study using algorithms for the prediction of patients' phenotype and tetrahydrobiopterin responsiveness in phenylketonuria patients, using data from the locus-specific and genotypes database.

Demographic and phenotypic responses of juvenile steelhead trout to spatial predictability of food resources

Science.gov (United States)

Matthew R. Sloat; Gordon H. Reeves

2014-01-01

We manipulated food inputs among patches within experimental streams to determine how variation in foraging behavior influenced demographic and phenotypic responses of juvenile steelhead trout (Oncorhynchus mykiss) to the spatial predictability of food resources. Demographic responses included compensatory adjustments in fish abundance, mean fish...

Population FBA predicts metabolic phenotypes in yeast.

Directory of Open Access Journals (Sweden)

Piyush Labhsetwar

2017-09-01

Full Text Available Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen, while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but

Multidimensional clinical phenotyping of an adult cystic fibrosis patient population.

Directory of Open Access Journals (Sweden)

Douglas J Conrad

Full Text Available Cystic Fibrosis (CF is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease.The variables included age, gender, CFTR mutations, FEV1% predicted, FVC% predicted, height, weight, Brasfield chest xray score, pancreatic sufficiency status and clinical microbiology results. Complete datasets were compiled on 211 subjects. Phenotypes were identified using a proximity matrix generated by the unsupervised Random Forests algorithm and subsequent clustering by the Partitioning around Medoids (PAM algorithm. The final phenotypic classes were then characterized and compared to a similar dataset obtained three years earlier.Clinical phenotypes were identified using a clustering strategy that generated four and five phenotypes. Each strategy identified 1 a low lung health scores phenotype, 2 a younger, well-nourished, male-dominated class, 3 various high lung health score phenotypes that varied in terms of age, gender and nutritional status. This multidimensional clinical phenotyping strategy identified classes with expected microbiology results and low risk clinical phenotypes with pancreatic sufficiency.This study demonstrated regional adult CF clinical phenotypes using non-parametric, continuous, ordinal and categorical data with a minimal amount of subjective data to identify clinically relevant phenotypes. These studies identified the relative stability of the phenotypes, demonstrated specific phenotypes consistent with published findings and identified others needing further study.

Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest.

Science.gov (United States)

Holliday, Jason A; Wang, Tongli; Aitken, Sally

2012-09-01

Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.

A Comprehensive Dataset of Genes with a Loss-of-Function Mutant Phenotype in Arabidopsis1[W][OA

Science.gov (United States)

Lloyd, Johnny; Meinke, David

2012-01-01

Despite the widespread use of Arabidopsis (Arabidopsis thaliana) as a model plant, a curated dataset of Arabidopsis genes with mutant phenotypes remains to be established. A preliminary list published nine years ago in Plant Physiology is outdated, and genome-wide phenotype information remains difficult to obtain. We describe here a comprehensive dataset of 2,400 genes with a loss-of-function mutant phenotype in Arabidopsis. Phenotype descriptions were gathered primarily from manual curation of the scientific literature. Genes were placed into prioritized groups (essential, morphological, cellular-biochemical, and conditional) based on the documented phenotypes of putative knockout alleles. Phenotype classes (e.g. vegetative, reproductive, and timing, for the morphological group) and subsets (e.g. flowering time, senescence, circadian rhythms, and miscellaneous, for the timing class) were also established. Gene identities were classified as confirmed (through molecular complementation or multiple alleles) or not confirmed. Relationships between mutant phenotype and protein function, genetic redundancy, protein connectivity, and subcellular protein localization were explored. A complementary dataset of 401 genes that exhibit a mutant phenotype only when disrupted in combination with a putative paralog was also compiled. The importance of these genes in confirming functional redundancy and enhancing the value of single gene datasets is discussed. With further input and curation from the Arabidopsis community, these datasets should help to address a variety of important biological questions, provide a foundation for exploring the relationship between genotype and phenotype in angiosperms, enhance the utility of Arabidopsis as a reference plant, and facilitate comparative studies with model genetic organisms. PMID:22247268

A strong loss-of-function mutation in RAN1 results in constitutive activation of the ethylene response pathway as well as a rosette-lethal phenotype

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Woeste, K. E.; Kieber, J. J.; Evans, M. L. (Principal Investigator)

2000-01-01

A recessive mutation was identified that constitutively activated the ethylene response pathway in Arabidopsis and resulted in a rosette-lethal phenotype. Positional cloning of the gene corresponding to this mutation revealed that it was allelic to responsive to antagonist1 (ran1), a mutation that causes seedlings to respond in a positive manner to what is normally a competitive inhibitor of ethylene binding. In contrast to the previously identified ran1-1 and ran1-2 alleles that are morphologically indistinguishable from wild-type plants, this ran1-3 allele results in a rosette-lethal phenotype. The predicted protein encoded by the RAN1 gene is similar to the Wilson and Menkes disease proteins and yeast Ccc2 protein, which are integral membrane cation-transporting P-type ATPases involved in copper trafficking. Genetic epistasis analysis indicated that RAN1 acts upstream of mutations in the ethylene receptor gene family. However, the rosette-lethal phenotype of ran1-3 was not suppressed by ethylene-insensitive mutants, suggesting that this mutation also affects a non-ethylene-dependent pathway regulating cell expansion. The phenotype of ran1-3 mutants is similar to loss-of-function ethylene receptor mutants, suggesting that RAN1 may be required to form functional ethylene receptors. Furthermore, these results suggest that copper is required not only for ethylene binding but also for the signaling function of the ethylene receptors.

Recommendations for using standardised phenotypes in genetic association studies

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Naylor Melissa G

2009-07-01

Full Text Available Abstract Genetic association studies of complex traits often rely on standardised quantitative phenotypes, such as percentage of predicted forced expiratory volume and body mass index to measure an underlying trait of interest (eg lung function, obesity. These phenotypes are appealing because they provide an easy mechanism for comparing subjects, although such standardisations may not be the best way to control for confounders and other covariates. We recommend adjusting raw or standardised phenotypes within the study population via regression. We illustrate through simulation that optimal power in both population- and family-based association tests is attained by using the residuals from within-study adjustment as the complex trait phenotype. An application of family-based association analysis of forced expiratory volume in one second, and obesity in the Childhood Asthma Management Program data, illustrates that power is maintained or increased when adjusted phenotype residuals are used instead of typical standardised quantitative phenotypes.

Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems.

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Yu, Michael Ku; Kramer, Michael; Dutkowski, Janusz; Srivas, Rohith; Licon, Katherine; Kreisberg, Jason; Ng, Cherie T; Krogan, Nevan; Sharan, Roded; Ideker, Trey

2016-02-24

Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.

Multiparametric classification links tumor microenvironments with tumor cell phenotype.

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Bojana Gligorijevic

2014-11-01

Full Text Available While it has been established that a number of microenvironment components can affect the likelihood of metastasis, the link between microenvironment and tumor cell phenotypes is poorly understood. Here we have examined microenvironment control over two different tumor cell motility phenotypes required for metastasis. By high-resolution multiphoton microscopy of mammary carcinoma in mice, we detected two phenotypes of motile tumor cells, different in locomotion speed. Only slower tumor cells exhibited protrusions with molecular, morphological, and functional characteristics associated with invadopodia. Each region in the primary tumor exhibited either fast- or slow-locomotion. To understand how the tumor microenvironment controls invadopodium formation and tumor cell locomotion, we systematically analyzed components of the microenvironment previously associated with cell invasion and migration. No single microenvironmental property was able to predict the locations of tumor cell phenotypes in the tumor if used in isolation or combined linearly. To solve this, we utilized the support vector machine (SVM algorithm to classify phenotypes in a nonlinear fashion. This approach identified conditions that promoted either motility phenotype. We then demonstrated that varying one of the conditions may change tumor cell behavior only in a context-dependent manner. In addition, to establish the link between phenotypes and cell fates, we photoconverted and monitored the fate of tumor cells in different microenvironments, finding that only tumor cells in the invadopodium-rich microenvironments degraded extracellular matrix (ECM and disseminated. The number of invadopodia positively correlated with degradation, while the inhibiting metalloproteases eliminated degradation and lung metastasis, consistent with a direct link among invadopodia, ECM degradation, and metastasis. We have detected and characterized two phenotypes of motile tumor cells in vivo, which

Evolution of molecular phenotypes under stabilizing selection

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Nourmohammad, Armita; Schiffels, Stephan; Lässig, Michael

2013-01-01

Molecular phenotypes are important links between genomic information and organismic functions, fitness, and evolution. Complex phenotypes, which are also called quantitative traits, often depend on multiple genomic loci. Their evolution builds on genome evolution in a complicated way, which involves selection, genetic drift, mutations and recombination. Here we develop a coarse-grained evolutionary statistics for phenotypes, which decouples from details of the underlying genotypes. We derive approximate evolution equations for the distribution of phenotype values within and across populations. This dynamics covers evolutionary processes at high and low recombination rates, that is, it applies to sexual and asexual populations. In a fitness landscape with a single optimal phenotype value, the phenotypic diversity within populations and the divergence between populations reach evolutionary equilibria, which describe stabilizing selection. We compute the equilibrium distributions of both quantities analytically and we show that the ratio of mean divergence and diversity depends on the strength of selection in a universal way: it is largely independent of the phenotype’s genomic encoding and of the recombination rate. This establishes a new method for the inference of selection on molecular phenotypes beyond the genome level. We discuss the implications of our findings for the predictability of evolutionary processes. (paper)

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

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Zhu, Xuli; Jiang, Libo; Ye, Meixia; Sun, Lidan; Gragnoli, Claudia; Wu, Rongling

2016-05-01

Natural selection has shaped the evolution of organisms toward optimizing their structural and functional design. However, how this universal principle can enhance genotype-phenotype mapping of quantitative traits has remained unexplored. Here we show that the integration of this principle and functional mapping through evolutionary game theory gains new insight into the genetic architecture of complex traits. By viewing phenotype formation as an evolutionary system, we formulate mathematical equations to model the ecological mechanisms that drive the interaction and coordination of its constituent components toward population dynamics and stability. Functional mapping provides a procedure for estimating the genetic parameters that specify the dynamic relationship of competition and cooperation and predicting how genes mediate the evolution of this relationship during trait formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Anomalous baroreflex functionality inherent in floxed and Cre-Lox mice: an overlooked physiological phenotype.

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Tsai, Ching-Yi; Poon, Yan-Yuen; Chen, Chang-Han; Chan, Samuel H H

2017-10-01

The last two decades have seen the emergence of Cre-Lox recombination as one of the most powerful and versatile technologies for cell-specific genetic engineering of mammalian cells. Understandably, the primary concerns in the practice of Cre-Lox recombination are whether the predicted genome has been correctly modified and the targeted phenotypes expressed. Rarely are the physiological conditions of the animals routinely examined because the general assumption is that they are normal. Based on corroborative results from radiotelemetric recording, power spectral analysis, and magnetic resonance imaging/diffusion tensor imaging in brain-derived neurotrophic factor-floxed mice, the present study revealed that this assumption requires amendment. We found that despite comparable blood pressure and heart rate with C57BL/6 or Cre mice under the conscious state, floxed and Cre-Lox mice exhibited diminished baroreflex-mediated sympathetic vasomotor tone and cardiac vagal baroreflex. We further found that the capacity and plasticity of baroreflex of these two strains of mice under isoflurane anesthesia were retarded, as reflected by reduced connectivity between the nucleus tractus solitarii and rostral ventrolateral medulla or nucleus ambiguus. The identification of anomalous baroreflex functionality inherent in floxed and Cre-Lox mice points to the importance of incorporating physiological phenotypes into studies that engage gene manipulations such as Cre-Lox recombination. NEW & NOTEWORTHY We established that anomalous baroreflex functionality is inherent in floxed and Cre-Lox mice. These two mouse strains exhibited diminished baroreflex-mediated sympathetic vasomotor tone and cardiac vagal baroreflex under the conscious state, retarded capacity and plasticity of baroreflex under isoflurane anesthesia, and reduced connectivity between key nuclei in the baroreflex neural circuits. Copyright © 2017 the American Physiological Society.

Phenotype prediction using regularized regression on genetic data in the DREAM5 Systems Genetics B Challenge.

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Po-Ru Loh

Full Text Available A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only. We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

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Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Heterogeneity of functional properties of Clone 66 murine breast cancer cells expressing various stem cell phenotypes.

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Mukhopadhyay, Partha; Farrell, Tracy; Sharma, Gayatri; McGuire, Timothy R; O'Kane, Barbara; Sharp, J Graham

2013-01-01

Breast cancer grows, metastasizes and relapses from rare, therapy resistant cells with a stem cell phenotype (cancer stem cells/CSCs). However, there is a lack of studies comparing the functions of CSCs isolated using different phenotypes in order to determine if CSCs are homogeneous or heterogeneous. Cells with various stem cell phenotypes were isolated by sorting from Clone 66 murine breast cancer cells that grow orthotopically in immune intact syngeneic mice. These populations were compared by in vitro functional assays for proliferation, growth, sphere and colony formation; and in vivo limiting dilution analysis of tumorigenesis. The proportion of cells expressing CD44(high)CD24(low/neg), side population (SP) cells, ALDH1(+), CD49f(high), CD133(high), and CD34(high) differed, suggesting heterogeneity. Differences in frequency and size of tumor spheres from these populations were observed. Higher rates of proliferation of non-SP, ALDH1(+), CD34(low), and CD49f(high) suggested properties of transit amplifying cells. Colony formation was higher from ALDH1(-) and non-SP cells than ALDH1(+) and SP cells suggesting a progenitor phenotype. The frequency of clonal colonies that grew in agar varied and was differentially altered by the presence of Matrigel™. In vivo, fewer cells with a stem cell phenotype were needed for tumor formation than "non-stem" cells. Fewer SP cells were needed to form tumors than ALDH1(+) cells suggesting further heterogeneities of cells with stem phenotypes. Different levels of cytokines/chemokines were produced by Clone 66 with RANTES being the highest. Whether the heterogeneity reflects soluble factor production remains to be determined. These data demonstrate that Clone 66 murine breast cancer cells that express stem cell phenotypes are heterogeneous and exhibit different functional properties, and this may also be the case for human breast cancer stem cells.

Family function, Parenting Style and Broader Autism Phenotype as Predicting Factors of Psychological Adjustment in Typically Developing Siblings of Children with Autism Spectrum Disorders.

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Mohammadi, Mohammadreza; Zarafshan, Hadi

2014-04-01

Siblings of children with autism are at a greater risk of experiencing behavioral and social problems. Previous researches had focused on environmental variables such as family history of autism spectrum disorders (ASDs), behavior problems in the child with an ASD, parental mental health problems, stressful life events and "broader autism phenotype" (BAP), while variables like parenting style and family function that are shown to influence children's behavioral and psychosocial adjustment are overlooked. The aim of the present study was to reveal how parenting style and family function as well as BAP effect psychological adjustment of siblings of children with autism. The Participants included 65 parents who had one child with an Autism Spectrum Disorder and one typically developing child. Of the children with ASDs, 40 were boys and 25 were girls; and they were diagnosed with ASDs by a psychiatrist based on DSM-IV-TR criteria and Autism Diagnostic Interview-Revised (ADI-R). The Persian versions of the six scales were used to collect data from the families. Pearson's correlation test and regression analysis were used to determine which variables were related to the psychological adjustment of sibling of children with ASDs and which variables predicted it better. Significant relationships were found between Strengths and Difficulties Questionnaire (SDQ) total difficulties, prosocial behaviors and ASDs symptoms severity, parenting styles and some aspects of family function. In addition, siblings who had more BAP characteristics had more behavior problems and less prosocial behavior. Behavioral problems increased and prosocial behavior decreased with permissive parenting style. Besides, both of authoritarian and authoritative parenting styles led to a decrease in behavioral problems and an increase in prosocial behaviors. Our findings revealed that some aspects of family function (affective responsiveness, roles, problem solving and behavior control) were significantly

Chromatin Phenotype Karyometry Can Predict Recurrence in Papillary Urothelial Neoplasms of Low Malignant Potential

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Rodolfo Montironi

2007-01-01

Full Text Available Background: A preceding exploratory study (J. Clin. Pathol. 57(2004, 1201–1207 had shown that a karyometric assessment of nuclei from papillary urothelial neoplasms of low malignant potential (PUNLMP revealed subtle differences in phenotype which correlated with recurrence of disease. Aim of the Study: To validate the results from the exploratory study on a larger sample size. Materials: 93 karyometric features were analyzed on haematoxylin and eosin-stained sections from 85 cases of PUNLMP. 45 cases were from patients who had a solitary PUNLMP lesion and were disease-free during a follow-up period of at least 8 years. The other 40 were from patients with a unifocal PUNLMP, with one or more recurrences in the follow-up. A combination of the previously defined classification functions together with a new P-index derived classification method was used in an attempt to classify cases and identify a biomarker of recurrence in PUNLMP lesions. Results: Validation was pursued by a number of separate approaches. First, the exact procedure from the exploratory study was applied to the large validation set. Second, since the discriminant function 2 of the exploratory study had been based on a small sample size, a new discriminant function was derived. The case classification showed a correct classification of 61% for non-recurrent and 74% for recurrent cases, respectively. Greater success was obtained by applying unsupervised learning technologies to take advantage of phenotypical composition (correct classification of 92%. This approach was validated by dividing the data into training and test sets with 2/3 of the cases assigned to the training sets, and 1/3 to the test sets, on a rotating basis, and validation of the classification rate was thus tested on three separate data sets by a leave-k-out process. The average correct classification was 92.8% (training set and 84.6% (test set. Conclusions: Our validation study detected subvisual differences in

Relationships between functional genes in Lactobacillus delbrueckii ssp. bulgaricus isolates and phenotypic characteristics associated with fermentation time and flavor production in yogurt elucidated using multilocus sequence typing.

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Liu, Wenjun; Yu, Jie; Sun, Zhihong; Song, Yuqin; Wang, Xueni; Wang, Hongmei; Wuren, Tuoya; Zha, Musu; Menghe, Bilige; Heping, Zhang

2016-01-01

Lactobacillus delbrueckii ssp. bulgaricus (L. bulgaricus) is well known for its worldwide application in yogurt production. Flavor production and acid producing are considered as the most important characteristics for starter culture screening. To our knowledge this is the first study applying functional gene sequence multilocus sequence typing technology to predict the fermentation and flavor-producing characteristics of yogurt-producing bacteria. In the present study, phenotypic characteristics of 35 L. bulgaricus strains were quantified during the fermentation of milk to yogurt and during its subsequent storage; these included fermentation time, acidification rate, pH, titratable acidity, and flavor characteristics (acetaldehyde concentration). Furthermore, multilocus sequence typing analysis of 7 functional genes associated with fermentation time, acid production, and flavor formation was done to elucidate the phylogeny and genetic evolution of the same L. bulgaricus isolates. The results showed that strains significantly differed in fermentation time, acidification rate, and acetaldehyde production. Combining functional gene sequence analysis with phenotypic characteristics demonstrated that groups of strains established using genotype data were consistent with groups identified based on their phenotypic traits. This study has established an efficient and rapid molecular genotyping method to identify strains with good fermentation traits; this has the potential to replace time-consuming conventional methods based on direct measurement of phenotypic traits. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Phenotype and Tissue Expression as a Function of Genetic Risk in Polycystic Ovary Syndrome.

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Cindy T Pau

Full Text Available Genome-wide association studies and replication analyses have identified (n = 5 or replicated (n = 10 DNA variants associated with risk for polycystic ovary syndrome (PCOS in European women. However, the causal gene and underlying mechanism for PCOS risk at these loci have not been determined. We hypothesized that analysis of phenotype, gene expression and metformin response as a function of genotype would identify candidate genes and pathways that could provide insight into the underlying mechanism for risk at these loci. To test the hypothesis, subjects with PCOS (n = 427 diagnosed according to the NIH criteria (< 9 menses per year and clinical or biochemical hyperandrogenism and controls (n = 407 with extensive phenotyping were studied. A subset of subjects (n = 38 underwent a subcutaneous adipose tissue biopsy for RNA sequencing and were subsequently treated with metformin for 12 weeks with standardized outcomes measured. Data were analyzed according to genotype at PCOS risk loci and adjusted for the false discovery rate. A gene variant in the THADA locus was associated with response to metformin and metformin was a predicted upstream regulator at the same locus. Genotype at the FSHB locus was associated with LH levels. Genes near the PCOS risk loci demonstrated differences in expression as a function of genotype in adipose including BLK and NEIL2 (GATA4 locus, GLIPR1 and PHLDA1 (KRR1 locus. Based on the phenotypes, expression quantitative trait loci (eQTL, and upstream regulatory and pathway analyses we hypothesize that there are PCOS subtypes. FSHB, FHSR and LHR loci may influence PCOS risk based on their relationship to gonadotropin levels. The THADA, GATA4, ERBB4, SUMO1P1, KRR1 and RAB5B loci appear to confer risk through metabolic mechanisms. The IRF1, SUMO1P1 and KRR1 loci may confer PCOS risk in development. The TOX3 and GATA4 loci appear to be involved in inflammation and its consequences. The data suggest potential PCOS subtypes and

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

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He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

2018-02-20

Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness/diversity decreased as uranium increased in groundwater, while specific key microbial guilds increased significantly as

Expansion of phenotype and genotypic data in CRB2-related syndrome.

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Lamont, Ryan E; Tan, Wen-Hann; Innes, A Micheil; Parboosingh, Jillian S; Schneidman-Duhovny, Dina; Rajkovic, Aleksandar; Pappas, John; Altschwager, Pablo; DeWard, Stephanie; Fulton, Anne; Gray, Kathryn J; Krall, Max; Mehta, Lakshmi; Rodan, Lance H; Saller, Devereux N; Steele, Deanna; Stein, Deborah; Yatsenko, Svetlana A; Bernier, François P; Slavotinek, Anne M

2016-10-01

Sequence variants in CRB2 cause a syndrome with greatly elevated maternal serum alpha-fetoprotein and amniotic fluid alpha-fetoprotein levels, cerebral ventriculomegaly and renal findings similar to Finnish congenital nephrosis. All reported patients have been homozygotes or compound heterozygotes for sequence variants in the Crumbs, Drosophila, Homolog of, 2 (CRB2) genes. Variants affecting CRB2 function have also been identified in four families with steroid resistant nephrotic syndrome, but without any other known systemic findings. We ascertained five, previously unreported individuals with biallelic variants in CRB2 that were predicted to affect function. We compiled the clinical features of reported cases and reviewed available literature for cases with features suggestive of CRB2-related syndrome in order to better understand the phenotypic and genotypic manifestations. Phenotypic analyses showed that ventriculomegaly was a common clinical manifestation (9/11 confirmed cases), in contrast to the original reports, in which patients were ascertained due to renal disease. Two children had minor eye findings and one was diagnosed with a B-cell lymphoma. Further genetic analysis identified one family with two affected siblings who were both heterozygous for a variant in NPHS2 predicted to affect function and separate families with sequence variants in NPHS4 and BBS7 in addition to the CRB2 variants. Our report expands the clinical phenotype of CRB2-related syndrome and establishes ventriculomegaly and hydrocephalus as frequent manifestations. We found additional sequence variants in genes involved in kidney development and ciliopathies in patients with CRB2-related syndrome, suggesting that these variants may modify the phenotype.

PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources [v1; ref status: indexed, http://f1000r.es/5j2

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Indika Kahanda

2015-07-01

Full Text Available The human phenotype ontology (HPO was recently developed as a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. At present, only a small fraction of human protein coding genes have HPO annotations. But, researchers believe that a large portion of currently unannotated genes are related to disease phenotypes. Therefore, it is important to predict gene-HPO term associations using accurate computational methods. In this work we demonstrate the performance advantage of the structured SVM approach which was shown to be highly effective for Gene Ontology term prediction in comparison to several baseline methods. Furthermore, we highlight a collection of informative data sources suitable for the problem of predicting gene-HPO associations, including large scale literature mining data.

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

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Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

Macrophage heterogeneity in tissues: phenotypic diversity and functions

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Gordon, Siamon; Plüddemann, Annette; Martinez Estrada, Fernando

2014-01-01

During development and throughout adult life, macrophages derived from hematopoietic progenitors are seeded throughout the body, initially in the absence of inflammatory and infectious stimuli as tissue-resident cells, with enhanced recruitment, activation, and local proliferation following injury and pathologic insults. We have learned a great deal about macrophage properties ex vivo and in cell culture, but their phenotypic heterogeneity within different tissue microenvironments remains poorly characterized, although it contributes significantly to maintaining local and systemic homeostasis, pathogenesis, and possible treatment. In this review, we summarize the nature, functions, and interactions of tissue macrophage populations within their microenvironment and suggest questions for further investigation. PMID:25319326

Mutations in RIT1 cause Noonan syndrome - additional functional evidence and expanding the clinical phenotype.

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Koenighofer, M; Hung, C Y; McCauley, J L; Dallman, J; Back, E J; Mihalek, I; Gripp, K W; Sol-Church, K; Rusconi, P; Zhang, Z; Shi, G-X; Andres, D A; Bodamer, O A

2016-03-01

RASopathies are a clinically heterogeneous group of conditions caused by mutations in 1 of 16 proteins in the RAS-mitogen activated protein kinase (RAS-MAPK) pathway. Recently, mutations in RIT1 were identified as a novel cause for Noonan syndrome. Here we provide additional functional evidence for a causal role of RIT1 mutations and expand the associated phenotypic spectrum. We identified two de novo missense variants p.Met90Ile and p.Ala57Gly. Both variants resulted in increased MEK-ERK signaling compared to wild-type, underscoring gain-of-function as the primary functional mechanism. Introduction of p.Met90Ile and p.Ala57Gly into zebrafish embryos reproduced not only aspects of the human phenotype but also revealed abnormalities of eye development, emphasizing the importance of RIT1 for spatial and temporal organization of the growing organism. In addition, we observed severe lymphedema of the lower extremity and genitalia in one patient. We provide additional evidence for a causal relationship between pathogenic mutations in RIT1, increased RAS-MAPK/MEK-ERK signaling and the clinical phenotype. The mutant RIT1 protein may possess reduced GTPase activity or a diminished ability to interact with cellular GTPase activating proteins; however the precise mechanism remains unknown. The phenotypic spectrum is likely to expand and includes lymphedema of the lower extremities in addition to nuchal hygroma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Functional specialization and phenotypic generalization in the pollination system of an epiphytic cactus

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Cristiane Martins

2018-03-01

Full Text Available ABSTRACT Plant-pollinator interactions range from obligatory specialists to facultative generalists, and floral morphology and pollination system may not match completely. The floral biology, reproductive system and floral visitors of a species of the tribe Rhipsalideae were investigated with a focus on the consistency between the pollination system and the floral phenotype. Rhipsalis neves-armondii is an obligate xenogamous species, due to self-sterility. Its flowers are white, small and diurnal, and radially symmetrical. These features, along with their small amount of nectar, characterize the flowers as phenotypic generalists. The most frequent pollinators were a solitary oligolectic species of Andrenidae (Rhophitulus solani, two species of Meliponinae (Trigona spinipes and T. braueri and Apis mellifera. Despite the generalist floral phenotype, the pollination system is functionally specialized, since only small bees performed effective visits. Flowers of R. neves-armondii may represent a case of cryptic floral specialization in which attributes other than morphology act as filters, restricting them to a single functional group of pollinators. Moreover, the four most frequent species of pollinators cover a spectrum ranging from solitary oligolectic to social polylectic bees, including an exotic species. These results illustrate the distinct dimensions of specialization-generalization that may occur in the pollination process of a single species.

Incorporating functional inter-relationships into protein function prediction algorithms

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Kumar Vipin

2009-05-01

Full Text Available Abstract Background Functional classification schemes (e.g. the Gene Ontology that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches. Results We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the k-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of

Prediction of Long-Term Benefits of Inhaled Steroids by Phenotypic Markers in Moderate-to-Severe COPD: A Randomized Controlled Trial.

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Jiska B Snoeck-Stroband

Full Text Available The decline in lung function can be reduced by long-term inhaled corticosteroid (ICS treatment in subsets of patients with chronic obstructive pulmonary disease (COPD. We aimed to identify which clinical, physiological and non-invasive inflammatory characteristics predict the benefits of ICS on lung function decline in COPD.Analysis was performed in 50 steroid-naive compliant patients with moderate to severe COPD (postbronchodilator forced expiratory volume in one second (FEV1, 30-80% of predicted, compatible with GOLD stages II-III, age 45-75 years, >10 packyears smoking and without asthma. Patients were treated with fluticasone propionate (500 μg bid or placebo for 2.5 years. Postbronchodilator FEV1, dyspnea and health status were measured every 3 months; lung volumes, airway hyperresponsiveness (PC20, and induced sputum at 0, 6 and 30 months. A linear mixed effect model was used for analysis of this hypothesis generating study.Significant predictors of attenuated FEV1-decline by fluticasone treatment compared to placebo were: fewer packyears smoking, preserved diffusion capacity, limited hyperinflation and lower inflammatory cell counts in induced sputum (p<0.04.Long-term benefits of ICS on lung function decline in patients with moderate-to-severe COPD are most pronounced in patients with fewer packyears, and less severe emphysema and inflammation. These data generate novel hypotheses on phenotype-driven therapy in COPD.ClinicalTrials.gov NCT00158847.

Phenotypic, Functional, and Safety Control at Preimplantation Phase of MSC-Based Therapy

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Lech, Wioletta; Figiel-Dabrowska, Anna; Drela, Katarzyna; Obtulowicz, Patrycja; Noszczyk, Bartlomiej Henryk; Buzanska, Leonora

2016-01-01

Mesenchymal stem cells (MSC) exhibit enormous heterogeneity which can modify their regenerative properties and therefore influence therapeutic effectiveness as well as safety of these cells transplantation. In addition the high phenotypic plasticity of MSC population makes it enormously sensitive to any changes in environmental properties including fluctuation in oxygen concentration. We have shown here that lowering oxygen level far below air atmosphere has a beneficial impact on various parameters characteristic for umbilical cord Wharton Jelly- (WJ-) MSC and adipose tissue- (AD-) derived MSC cultures. This includes their cellular composition, rate of proliferation, and maintenance of stemness properties together with commitment to cell differentiation toward mesodermal and neural lineages. In addition, the culture genomic stability increased significantly during long-term cell passaging and eventually protected cells against spontaneous transformation. Also by comparing of two routinely used methods of MSCs isolation (mechanical versus enzymatic) we have found substantial divergence arising between cell culture properties increasing along the time of cultivation in vitro. Thus, in this paper we highlight the urgent necessity to develop the more sensitive and selective methods for prediction and control cells fate and functioning during the time of growth in vitro. PMID:27651796

Phenotypic, Functional, and Safety Control at Preimplantation Phase of MSC-Based Therapy.

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Lech, Wioletta; Figiel-Dabrowska, Anna; Sarnowska, Anna; Drela, Katarzyna; Obtulowicz, Patrycja; Noszczyk, Bartlomiej Henryk; Buzanska, Leonora; Domanska-Janik, Krystyna

2016-01-01

Mesenchymal stem cells (MSC) exhibit enormous heterogeneity which can modify their regenerative properties and therefore influence therapeutic effectiveness as well as safety of these cells transplantation. In addition the high phenotypic plasticity of MSC population makes it enormously sensitive to any changes in environmental properties including fluctuation in oxygen concentration. We have shown here that lowering oxygen level far below air atmosphere has a beneficial impact on various parameters characteristic for umbilical cord Wharton Jelly- (WJ-) MSC and adipose tissue- (AD-) derived MSC cultures. This includes their cellular composition, rate of proliferation, and maintenance of stemness properties together with commitment to cell differentiation toward mesodermal and neural lineages. In addition, the culture genomic stability increased significantly during long-term cell passaging and eventually protected cells against spontaneous transformation. Also by comparing of two routinely used methods of MSCs isolation (mechanical versus enzymatic) we have found substantial divergence arising between cell culture properties increasing along the time of cultivation in vitro. Thus, in this paper we highlight the urgent necessity to develop the more sensitive and selective methods for prediction and control cells fate and functioning during the time of growth in vitro.

Family function, Parenting Style and Broader Autism Phenotype as Predicting Factors of Psychological Adjustment in Typically Developing Siblings of Children with Autism Spectrum Disorders.

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Mohammadreza Mohammadi

2014-06-01

Full Text Available Siblings of children with autism are at a greater risk of experiencing behavioral and social problems. Previous researches had focused on environmental variables such as family history of autism spectrum disorders (ASDs, behavior problems in the child with an ASD, parental mental health problems, stressful life events and "broader autism phenotype" (BAP, while variables like parenting style and family function that are shown to influence children's behavioral and psychosocial adjustment are overlooked. The aim of the present study was to reveal how parenting style and family function as well as BAP effect psychological adjustment of siblings of children with autism.The Participants included 65 parents who had one child with an Autism Spectrum Disorder and one typically developing child. Of the children with ASDs, 40 were boys and 25 were girls; and they were diagnosed with ASDs by a psychiatrist based on DSM-IV-TR criteria and Autism Diagnostic Interview-Revised (ADI-R. The Persian versions of the six scales were used to collect data from the families. Pearson's correlation test and regression analysis were used to determine which variables were related to the psychological adjustment of sibling of children with ASDs and which variables predicted it better.Significant relationships were found between Strengths and Difficulties Questionnaire (SDQ total difficulties, prosocial behaviors and ASDs symptoms severity, parenting styles and some aspects of family function. In addition, siblings who had more BAP characteristics had more behavior problems and less prosocial behavior. Behavioral problems increased and prosocial behavior decreased with permissive parenting style. Besides, both of authoritarian and authoritative parenting styles led to a decrease in behavioral problems and an increase in prosocial behaviors. Our findings revealed that some aspects of family function (affective responsiveness, roles, problem solving and behavior control were

A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

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Han Kyungsook

2010-06-01

Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

GGCX-Associated Phenotypes: An Overview in Search of Genotype-Phenotype Correlations

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Eva Y. G. De Vilder

2017-01-01

Full Text Available Gamma-carboxylation, performed by gamma-glutamyl carboxylase (GGCX, is an enzymatic process essential for activating vitamin K-dependent proteins (VKDP with important functions in various biological processes. Mutations in the encoding GGCX gene are associated with multiple phenotypes, amongst which vitamin K-dependent coagulation factor deficiency (VKCFD1 is best known. Other patients have skin, eye, heart or bone manifestations. As genotype–phenotype correlations were never described, literature was systematically reviewed in search of patients with at least one GGCX mutation with a phenotypic description, resulting in a case series of 47 patients. Though this number was too low for statistically valid correlations—a frequent problem in orphan diseases—we demonstrate the crucial role of the horizontally transferred transmembrane domain in developing cardiac and bone manifestations. Moreover, natural history suggests ageing as the principal determinant to develop skin and eye symptoms. VKCFD1 symptoms seemed more severe in patients with both mutations in the same protein domain, though this could not be linked to a more perturbed coagulation factor function. Finally, distinct GGCX functional domains might be dedicated to carboxylation of very specific VKDP. In conclusion, this systematic review suggests that there indeed may be genotype–phenotype correlations for GGCX-related phenotypes, which can guide patient counseling and management.

Proteomic analysis uncovers a metabolic phenotype in C. elegans after nhr-40 reduction of function

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Pohludka, Michal; Simeckova, Katerina; Vohanka, Jaroslav; Yilma, Petr; Novak, Petr; Krause, Michael W.; Kostrouchova, Marta; Kostrouch, Zdenek

2008-01-01

Caenorhabditis elegans has an unexpectedly large number (284) of genes encoding nuclear hormone receptors, most of which are nematode-specific and are of unknown function. We have exploited comparative two-dimensional chromatography of synchronized cultures of wild type C. elegans larvae and a mutant in nhr-40 to determine if proteomic approaches will provide additional insight into gene function. Chromatofocusing, followed by reversed-phase chromatography and mass spectrometry, identified altered chromatographic patterns for a set of proteins, many of which function in muscle and metabolism. Prompted by the proteomic analysis, we find that the penetrance of the developmental phenotypes in the mutant is enhanced at low temperatures and by food restriction. The combination of our phenotypic and proteomic analysis strongly suggests that NHR-40 provides a link between metabolism and muscle development. Our results highlight the utility of comparative two-dimensional chromatography to provide a relatively rapid method to gain insight into gene function

DNA Phenotyping: The prediction of human pigmentation traits from genetic data

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S. Walsh (Susan)

2013-01-01

textabstractPhenotyping is the ability to assign characteristics to an organism based on certain measurable parameters. In the case of DNA phenotyping, it is limited to the sole use of DNA to determine a phenotype such as an externally visible characteristic. In a forensic setting, it encompasses

Phenotype and Function of CD209+ Bovine Blood Dendritic Cells, Monocyte-Derived-Dendritic Cells and Monocyte-Derived Macrophages.

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Kun Taek Park

Full Text Available Phylogenic comparisons of the mononuclear phagocyte system (MPS of humans and mice demonstrate phenotypic divergence of dendritic cell (DC subsets that play similar roles in innate and adaptive immunity. Although differing in phenotype, DC can be classified into four groups according to ontogeny and function: conventional DC (cDC1 and cDC2, plasmacytoid DC (pDC, and monocyte derived DC (MoDC. DC of Artiodactyla (pigs and ruminants can also be sub-classified using this system, allowing direct functional and phenotypic comparison of MoDC and other DC subsets trafficking in blood (bDC. Because of the high volume of blood collections required to study DC, cattle offer the best opportunity to further our understanding of bDC and MoDC function in an outbred large animal species. As reported here, phenotyping DC using a monoclonal antibody (mAb to CD209 revealed CD209 is expressed on the major myeloid population of DC present in blood and MoDC, providing a phenotypic link between these two subsets. Additionally, the present study demonstrates that CD209 is also expressed on monocyte derived macrophages (MoΦ. Functional analysis revealed each of these populations can take up and process antigens (Ags, present them to CD4 and CD8 T cells, and elicit a T-cell recall response. Thus, bDC, MoDC, and MoΦ pulsed with pathogens or candidate vaccine antigens can be used to study factors that modulate DC-driven T-cell priming and differentiation ex vivo.

Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks

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2012-01-01

Background Age-related macular degeneration (AMD) is a leading cause of blindness that affects the central region of the retinal pigmented epithelium (RPE), choroid, and neural retina. Initially characterized by an accumulation of sub-RPE deposits, AMD leads to progressive retinal degeneration, and in advanced cases, irreversible vision loss. Although genetic analysis, animal models, and cell culture systems have yielded important insights into AMD, the molecular pathways underlying AMD's onset and progression remain poorly delineated. We sought to better understand the molecular underpinnings of this devastating disease by performing the first comparative transcriptome analysis of AMD and normal human donor eyes. Methods RPE-choroid and retina tissue samples were obtained from a common cohort of 31 normal, 26 AMD, and 11 potential pre-AMD human donor eyes. Transcriptome profiles were generated for macular and extramacular regions, and statistical and bioinformatic methods were employed to identify disease-associated gene signatures and functionally enriched protein association networks. Selected genes of high significance were validated using an independent donor cohort. Results We identified over 50 annotated genes enriched in cell-mediated immune responses that are globally over-expressed in RPE-choroid AMD phenotypes. Using a machine learning model and a second donor cohort, we show that the top 20 global genes are predictive of AMD clinical diagnosis. We also discovered functionally enriched gene sets in the RPE-choroid that delineate the advanced AMD phenotypes, neovascular AMD and geographic atrophy. Moreover, we identified a graded increase of transcript levels in the retina related to wound response, complement cascade, and neurogenesis that strongly correlates with decreased levels of phototransduction transcripts and increased AMD severity. Based on our findings, we assembled protein-protein interactomes that highlight functional networks likely to be

Cardio-facio-cutaneous syndrome: does genotype predict phenotype?

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Allanson, Judith E; Annerén, Göran; Aoki, Yoki; Armour, Christine M; Bondeson, Marie-Louise; Cave, Helene; Gripp, Karen W; Kerr, Bronwyn; Nystrom, Anna-Maja; Sol-Church, Katia; Verloes, Alain; Zenker, Martin

2011-05-15

Cardio-facio-cutaneous (CFC) syndrome is a sporadic multiple congenital anomalies/mental retardation condition principally caused by mutations in BRAF, MEK1, and MEK2. Mutations in KRAS and SHOC2 lead to a phenotype with overlapping features. In approximately 10–30% of individuals with a clinical diagnosis of CFC, a mutation in one of these causative genes is not found. Cardinal features of CFC include congenital heart defects, a characteristic facial appearance, and ectodermal abnormalities. Additional features include failure to thrive with severe feeding problems, moderate to severe intellectual disability and short stature with relative macrocephaly. First described in 1986, more than 100 affected individuals are reported. Following the discovery of the causative genes, more information has emerged on the breadth of clinical features. Little, however, has been published on genotype–phenotype correlations. This clinical study of 186 children and young adults with mutation-proven CFC syndrome is the largest reported to date. BRAF mutations are documented in 140 individuals (approximately 75%), while 46 (approximately 25%) have a mutation in MEK 1 or MEK 2. The age range is 6 months to 32 years, the oldest individual being a female from the original report [Reynolds et al. (1986); Am J Med Genet 25:413–427]. While some clinical data on 136 are in the literature, 50 are not previously published. We provide new details of the breadth of phenotype and discuss the frequency of particular features in each genotypic group. Pulmonary stenosis is the only anomaly that demonstrates a statistically significant genotype–phenotype correlation, being more common in individuals with a BRAF mutation.

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation.

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Lande, Russell

2009-07-01

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag tau between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag tau. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.

Text mining improves prediction of protein functional sites.

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Karin M Verspoor

Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Text Mining Improves Prediction of Protein Functional Sites

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Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

The search for Pleiades in trait constellations: functional integration and phenotypic selection in the complex flowers of Morrenia brachystephana (Apocynaceae).

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Baranzelli, M C; Sérsic, A N; Cocucci, A A

2014-04-01

Pollinator-mediated natural selection on single traits, such as corolla tube or spur length, has been well documented. However, flower phenotypes are usually complex, and selection is expected to act on several traits that functionally interact rather than on a single isolated trait. Despite the fact that selection on complex phenotypes is expectedly widespread, multivariate selection modelling on such phenotypes still remains under-explored in plants. Species of the subfamily Asclepiadoideae (Apocynaceae) provide an opportunity to study such complex flower contrivances integrated by fine-scaled organs from disparate developmental origin. We studied the correlation structure among linear floral traits (i) by testing a priori morphological, functional or developmental hypotheses among traits and (ii) by exploring the organization of flower covariation, considering alternative expectations of modular organization or whole flower integration through conditional dependence analysis (CDA) and integration matrices. The phenotypic selection approach was applied to determine whether floral traits involved in the functioning of the pollination mechanism were affected by natural selection. Floral integration was low, suggesting that flowers are organized in more than just one correlation pleiad; our hypothetical functional correlation matrix was significantly correlated with the empirical matrix, and the CDA revealed three putative modules. Analyses of phenotypic selection showed significant linear and correlational gradients, lending support to expectations of functional interactions between floral traits. Significant correlational selection gradients found involved traits of different floral whorls, providing evidence for the existence of functional integration across developmental domains. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Phenotypic, functional, and quantitative characterization of canine peripheral blood monocyte-derived macrophages

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R Bueno

2005-08-01

Full Text Available The yield as well as phenotypic and functional parameters of canine peripheral blood monocyte-derived macrophages were analyzed. The cells that remained adherent to Teflon after 10 days of culture had high phagocytic activity when inoculated with Leishmania chagasi. Flow cytometric analysis demonstrated that more than 80% of cultured cells were positive for the monocyte/macrophage marker CD14.

Defining predictive values using three different platelet function tests for CYP2C19 phenotype status on maintenance dual antiplatelet therapy after PCI.

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Zhang, Hong-Zhe; Kim, Moo Hyun; Han, Jin-Yeong; Jeong, Young-Hoon

2014-01-01

Published data suggests that the presence of CYP2C19*2 or *3 loss of function (LOF) alleles is indicative of increased platelet aggregation and a higher risk of adverse cardiovascular events after clopidogrel administration. We sought to determine cut-off values using three different assays for prediction of the CYP2C19 phenotype in Korean percutaneous coronary intervention (PCI) patients. We enrolled 244 patients with drug-eluting stent implantation who were receiving clopidogrel and aspirin maintenance therapy for one month or more. Platelet reactivity was assessed with light transmittance aggregometry (LTA), multiple electrode aggregometry (MEA) and the VerifyNow P2Y12 assay (VN). The CYP2C19 genotype was analyzed by polymerase chain reaction (PCR) and snapshot method. The frequency of CYP2C19 LOF allele carriers was 58.6%. The cut-off values from LTA, MEA and VerifyNow for the identification of LOF allele carriers were as follows: 10 µM ADP-induced LTA ≥ 48 %, VN>242 PRU and MEA ≥ 37 U. Between the three tests, correlation was higher between LTA vs. VN assays (r=0.69) and LTA vs. MEA (r=0.56), with moderate agreement (κ=0.46 and κ=0.46), but between VN assay and MEA, both devices using whole blood showed a lower correlation (r=0.42) and agreement (κ=0.3). Our results provide guidance regarding cut-off levels for LTA, VerifyNow and MEA assays to detect the CYP2C19 LOF allele in patients during dual antiplatelet maintenance therapy.

Enabling phenotypic big data with PheNorm.

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Yu, Sheng; Ma, Yumeng; Gronsbell, Jessica; Cai, Tianrun; Ananthakrishnan, Ashwin N; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Liao, Katherine P; Cai, Tianxi

2018-01-01

Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation, annotation remains a major bottleneck. In this paper, we present PheNorm, a phenotyping algorithm that does not require expert-labeled samples for training. The most predictive features, such as the number of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes or mentions of the target phenotype, are normalized to resemble a normal mixture distribution with high area under the receiver operating curve (AUC) for prediction. The transformed features are then denoised and combined into a score for accurate disease classification. We validated the accuracy of PheNorm with 4 phenotypes: coronary artery disease, rheumatoid arthritis, Crohn's disease, and ulcerative colitis. The AUCs of the PheNorm score reached 0.90, 0.94, 0.95, and 0.94 for the 4 phenotypes, respectively, which were comparable to the accuracy of supervised algorithms trained with sample sizes of 100-300, with no statistically significant difference. The accuracy of the PheNorm algorithms is on par with algorithms trained with annotated samples. PheNorm fully automates the generation of accurate phenotyping algorithms and demonstrates the capacity for EHR-driven annotations to scale to the next level - phenotypic big data. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

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Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Phenotypic and Functional Alterations in Circulating Memory CD8 T Cells with Time after Primary Infection.

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Matthew D Martin

2015-10-01

Full Text Available Memory CD8 T cells confer increased protection to immune hosts upon secondary viral, bacterial, and parasitic infections. The level of protection provided depends on the numbers, quality (functional ability, and location of memory CD8 T cells present at the time of infection. While primary memory CD8 T cells can be maintained for the life of the host, the full extent of phenotypic and functional changes that occur over time after initial antigen encounter remains poorly characterized. Here we show that critical properties of circulating primary memory CD8 T cells, including location, phenotype, cytokine production, maintenance, secondary proliferation, secondary memory generation potential, and mitochondrial function change with time after infection. Interestingly, phenotypic and functional alterations in the memory population are not due solely to shifts in the ratio of effector (CD62Llo and central memory (CD62Lhi cells, but also occur within defined CD62Lhi memory CD8 T cell subsets. CD62Lhi memory cells retain the ability to efficiently produce cytokines with time after infection. However, while it is was not formally tested whether changes in CD62Lhi memory CD8 T cells over time occur in a cell intrinsic manner or are due to selective death and/or survival, the gene expression profiles of CD62Lhi memory CD8 T cells change, phenotypic heterogeneity decreases, and mitochondrial function and proliferative capacity in either a lymphopenic environment or in response to antigen re-encounter increase with time. Importantly, and in accordance with their enhanced proliferative and metabolic capabilities, protection provided against chronic LCMV clone-13 infection increases over time for both circulating memory CD8 T cell populations and for CD62Lhi memory cells. Taken together, the data in this study reveal that memory CD8 T cells continue to change with time after infection and suggest that the outcome of vaccination strategies designed to elicit

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

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Zhili He

2018-02-01

Full Text Available Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN, representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5 increased significantly (P < 0.05 as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.

No Association between Variation in Longevity Candidate Genes and Aging-related Phenotypes in Oldest-old Danes.

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Soerensen, Mette; Nygaard, Marianne; Debrabant, Birgit; Mengel-From, Jonas; Dato, Serena; Thinggaard, Mikael; Christensen, Kaare; Christiansen, Lene

2016-06-01

In this study we explored the association between aging-related phenotypes previously reported to predict survival in old age and variation in 77 genes from the DNA repair pathway, 32 genes from the growth hormone 1/ insulin-like growth factor 1/insulin (GH/IGF-1/INS) signalling pathway and 16 additional genes repeatedly considered as candidates for human longevity: APOE, APOA4, APOC3, ACE, CETP, HFE, IL6, IL6R, MTHFR, TGFB1, SIRTs 1, 3, 6; and HSPAs 1A, 1L, 14. Altogether, 1,049 single nucleotide polymorphisms (SNPs) were genotyped in 1,088 oldest-old (age 92-93 years) Danes and analysed with phenotype data on physical functioning (hand grip strength), cognitive functioning (mini mental state examination and a cognitive composite score), activity of daily living and self-rated health. Five SNPs showed association to one of the phenotypes; however, none of these SNPs were associated with a change in the relevant phenotype over time (7 years of follow-up) and none of the SNPs could be confirmed in a replication sample of 1,281 oldest-old Danes (age 94-100). Hence, our study does not support association between common variation in the investigated longevity candidate genes and aging-related phenotypes consistently shown to predict survival. It is possible that larger sample sizes are needed to robustly reveal associations with small effect sizes. Copyright © 2016 Elsevier Inc. All rights reserved.

Effect of Surface Modification and Macrophage Phenotype on Particle Internalization

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Wang, Daniel [Iowa State University; Phan, Ngoc [Iowa State University; Isely, Christopher [Iowa State University; Bruene, Lucas [Iowa State University; Bratlie, Kaitlin M [Ames Laboratory

2014-11-10

Material properties play a key role in the cellular internalization of polymeric particles. In the present study, we have investigated the effects of material characteristics such as water contact angle, zeta potential, melting temperature, and alternative activation of complement on particle internalization for pro-inflammatory, pro-angiogenic, and naïve macrophages by using biopolymers (~600 nm), functionalized with 13 different molecules. Understanding how material parameters influence particle internalization for different macrophage phenotypes is important for targeted delivery to specific cell populations. Here, we demonstrate that material parameters affect the alternative pathway of complement activation as well as particle internalization for different macrophage phenotypes. Here, we show that the quantitative structure–activity relationship method (QSAR) previously used to predict physiochemical properties of materials can be applied to targeting different macrophage phenotypes. These findings demonstrated that targeted drug delivery to macrophages could be achieved by exploiting material parameters.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

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Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

Evolving phenotypic networks in silico.

Science.gov (United States)

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

Phenotypic Profiling of Antibiotic Response Signatures in Escherichia coli Using Raman Spectroscopy

Science.gov (United States)

Athamneh, A. I. M.; Alajlouni, R. A.; Wallace, R. S.; Seleem, M. N.

2014-01-01

Identifying the mechanism of action of new potential antibiotics is a necessary but time-consuming and costly process. Phenotypic profiling has been utilized effectively to facilitate the discovery of the mechanism of action and molecular targets of uncharacterized drugs. In this research, Raman spectroscopy was used to profile the phenotypic response of Escherichia coli to applied antibiotics. The use of Raman spectroscopy is advantageous because it is noninvasive, label free, and prone to automation, and its results can be obtained in real time. In this research, E. coli cultures were subjected to three times the MICs of 15 different antibiotics (representing five functional antibiotic classes) with known mechanisms of action for 30 min before being analyzed by Raman spectroscopy (using a 532-nm excitation wavelength). The resulting Raman spectra contained sufficient biochemical information to distinguish between profiles induced by individual antibiotics belonging to the same class. The collected spectral data were used to build a discriminant analysis model that identified the effects of unknown antibiotic compounds on the phenotype of E. coli cultures. Chemometric analysis showed the ability of Raman spectroscopy to predict the functional class of an unknown antibiotic and to identify individual antibiotics that elicit similar phenotypic responses. Results of this research demonstrate the power of Raman spectroscopy as a cellular phenotypic profiling methodology and its potential impact on antibiotic drug development research. PMID:24295982

Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica.

Science.gov (United States)

Neuert, Saskia; Nair, Satheesh; Day, Martin R; Doumith, Michel; Ashton, Philip M; Mellor, Kate C; Jenkins, Claire; Hopkins, Katie L; Woodford, Neil; de Pinna, Elizabeth; Godbole, Gauri; Dallman, Timothy J

2018-01-01

Surveillance of antimicrobial resistance (AMR) in non-typhoidal Salmonella enterica (NTS), is essential for monitoring transmission of resistance from the food chain to humans, and for establishing effective treatment protocols. We evaluated the prediction of phenotypic resistance in NTS from genotypic profiles derived from whole genome sequencing (WGS). Genes and chromosomal mutations responsible for phenotypic resistance were sought in WGS data from 3,491 NTS isolates received by Public Health England's Gastrointestinal Bacteria Reference Unit between April 2014 and March 2015. Inferred genotypic AMR profiles were compared with phenotypic susceptibilities determined for fifteen antimicrobials using EUCAST guidelines. Discrepancies between phenotypic and genotypic profiles for one or more antimicrobials were detected for 76 isolates (2.18%) although only 88/52,365 (0.17%) isolate/antimicrobial combinations were discordant. Of the discrepant results, the largest number were associated with streptomycin (67.05%, n = 59). Pan-susceptibility was observed in 2,190 isolates (62.73%). Overall, resistance to tetracyclines was most common (26.27% of isolates, n = 917) followed by sulphonamides (23.72%, n = 828) and ampicillin (21.43%, n = 748). Multidrug resistance (MDR), i.e., resistance to three or more antimicrobial classes, was detected in 848 isolates (24.29%) with resistance to ampicillin, streptomycin, sulphonamides and tetracyclines being the most common MDR profile ( n = 231; 27.24%). For isolates with this profile, all but one were S . Typhimurium and 94.81% ( n = 219) had the resistance determinants bla TEM-1, strA-strB, sul2 and tet (A). Extended-spectrum β-lactamase genes were identified in 41 isolates (1.17%) and multiple mutations in chromosomal genes associated with ciprofloxacin resistance in 82 isolates (2.35%). This study showed that WGS is suitable as a rapid means of determining AMR patterns of NTS for public health surveillance.

Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data.

Directory of Open Access Journals (Sweden)

Jonathan D Mosley

Full Text Available A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1 non-synonymous SNPs (nsSNPs associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1 thrombosis, evaluated in a population of 1,655 African Americans; and (2 four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs, and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03, driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10-5, FDR p = 0.03 (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L while the additive model showed enrichment related to chromatid segregation (p = 4×10-6, FDR p = 0.005 (KIF25, PINX1. We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.

Functional variants of the dopamine receptor D2 gene modulate prefronto-striatal phenotypes in schizophrenia.

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Bertolino, Alessandro; Fazio, Leonardo; Caforio, Grazia; Blasi, Giuseppe; Rampino, Antonio; Romano, Raffaella; Di Giorgio, Annabella; Taurisano, Paolo; Papp, Audrey; Pinsonneault, Julia; Wang, Danxin; Nardini, Marcello; Popolizio, Teresa; Sadee, Wolfgang

2009-02-01

Dopamine D2 receptor signalling is strongly implicated in the aetiology of schizophrenia. We have recently characterized the function of three DRD2 SNPs: rs12364283 in the promoter affecting total D2 mRNA expression; rs2283265 and rs1076560, respectively in introns 5 and 6, shifting mRNA splicing to two functionally distinct isoforms, the short form of D2 (D2S) and the long form (D2L). These two isoforms differentially contribute to dopamine signalling in prefrontal cortex and in striatum. We performed a case-control study to determine association of these variants and of their main haplotypes with several schizophrenia-related phenotypes. We demonstrate that the minor allele in the intronic variants is associated with reduced expression of %D2S of total mRNA in post-mortem prefrontal cortex, and with impaired working memory behavioural performance, both in patients and controls. However, the fMRI results show opposite effects in patients compared with controls: enhanced engagement of prefronto-striatal pathways in controls and reduced activity in patients. Moreover, the promoter variant is also associated with working memory activity in prefrontal cortex and striatum of patients, and less robustly with negative symptoms scores. Main haplotypes formed by the three DRD2 variants showed significant associations with these phenotypes consistent with those of the individual SNPs. Our results indicate that the three functional DRD2 variants modulate schizophrenia phenotypes possibly by modifying D2S/D2L ratios in the context of different total D2 density.

Stoichiometric Representation of Gene–Protein–Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction

DEFF Research Database (Denmark)

Machado, Daniel; Herrgard, Markus; Rocha, Isabel

2016-01-01

only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene...... design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions...

GRIN2B encephalopathy : Novel findings on phenotype, variant clustering, functional consequences and treatment aspects

NARCIS (Netherlands)

Platzer, Konrad; Yuan, Hongjie; Schütz, Hannah; Winschel, Alexander; Chen, Wenjuan; Hu, Chun; Kusumoto, Hirofumi; Heyne, Henrike O; Helbig, Katherine L; Tang, Sha; Willing, Marcia C; Tinkle, Brad T; Adams, Darius J; Depienne, Christel; Keren, Boris; Mignot, Cyril; Frengen, Eirik; Strømme, Petter; Biskup, Saskia; Döcker, Dennis; Strom, Tim M.; Mefford, Heather C.; Myers, Candace T.; Muir, Alison M; LaCroix, Amy; Sadleir, Lynette G.; Scheffer, Ingrid E.; Brilstra, Eva; van Haelst, Mieke M.; van der Smagt, Jasper J.; Bok, Levinus A; Møller, Rikke S.; Jensen, Uffe Birk; Millichap, John J; Berg, Anne T; Goldberg, Ethan M; De Bie, Isabelle; Fox, Stephanie; Major, Philippe; Jones, Julie R; Zackai, Elaine H.; Abou Jamra, Rami; Rolfs, Arndt; Leventer, Richard J; Lawson, John A; Roscioli, Tony; Jansen, Floor E.; Ranza, Emmanuelle; Korff, Christian M; Lehesjoki, Anna-Elina; Courage, Carolina; Linnankivi, Tarja; Smith, Douglas R; Stanley, Christine; Mintz, Mark; McKnight, Dianalee; Decker, Amy; Tan, Wen-Hann; Tarnopolsky, Mark A; Brady, Lauren I; Wolff, Markus; Dondit, Lutz; Pedro, Helio F; Parisotto, Sarah E; Jones, Kelly L; Patel, Anup D; Franz, David N; Vanzo, Rena; Marco, Elysa; Ranells, Judith D; Di Donato, Nataliya; Dobyns, William B.; Laube, Bodo; Traynelis, Stephen F; Lemke, Johannes R.

2017-01-01

Background: We aimed for a comprehensive delineation of genetic, functional and phenotypic aspects of GRIN2B encephalopathy and explored potential prospects of personalised medicine. Methods: Data of 48 individuals with de novo GRIN2B variants were collected from several diagnostic and research

Functional analysis of rare variants in mismatch repair proteins augments results from computation-based predictive methods

Science.gov (United States)

Arora, Sanjeevani; Huwe, Peter J.; Sikder, Rahmat; Shah, Manali; Browne, Amanda J.; Lesh, Randy; Nicolas, Emmanuelle; Deshpande, Sanat; Hall, Michael J.; Dunbrack, Roland L.; Golemis, Erica A.

2017-01-01

ABSTRACT The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS. PMID:28494185

Automatic and controlled processing and the Broad Autism Phenotype.

Science.gov (United States)

Camodeca, Amy; Voelker, Sylvia

2016-01-30

Research related to verbal fluency in the Broad Autism Phenotype (BAP) is limited and dated, but generally suggests intact abilities in the context of weaknesses in other areas of executive function (Hughes et al., 1999; Wong et al., 2006; Delorme et al., 2007). Controlled processing, the generation of search strategies after initial, automated responses are exhausted (Spat, 2013), has yet to be investigated in the BAP, and may be evidenced in verbal fluency tasks. One hundred twenty-nine participants completed the Delis-Kaplan Executive Function System Verbal Fluency test (D-KEFS; Delis et al., 2001) and the Broad Autism Phenotype Questionnaire (BAPQ; Hurley et al., 2007). The BAP group (n=53) produced significantly fewer total words during the 2nd 15" interval compared to the Non-BAP (n=76) group. Partial correlations indicated similar relations between verbal fluency variables for each group. Regression analyses predicting 2nd 15" interval scores suggested differentiation between controlled and automatic processing skills in both groups. Results suggest adequate automatic processing, but slowed development of controlled processing strategies in the BAP, and provide evidence for similar underlying cognitive constructs for both groups. Controlled processing was predictive of Block Design score for Non-BAP participants, and was predictive of Pragmatic Language score on the BAPQ for BAP participants. These results are similar to past research related to strengths and weaknesses in the BAP, respectively, and suggest that controlled processing strategy use may be required in instances of weak lower-level skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

Directory of Open Access Journals (Sweden)

Tallulah Andrews

2015-03-01

Full Text Available Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51% groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders.

Science.gov (United States)

Andrews, Tallulah; Meader, Stephen; Vulto-van Silfhout, Anneke; Taylor, Avigail; Steinberg, Julia; Hehir-Kwa, Jayne; Pfundt, Rolph; de Leeuw, Nicole; de Vries, Bert B A; Webber, Caleb

2015-03-01

Readily-accessible and standardised capture of genotypic variation has revolutionised our understanding of the genetic contribution to disease. Unfortunately, the corresponding systematic capture of patient phenotypic variation needed to fully interpret the impact of genetic variation has lagged far behind. Exploiting deep and systematic phenotyping of a cohort of 197 patients presenting with heterogeneous developmental disorders and whose genomes harbour de novo CNVs, we systematically applied a range of commonly-used functional genomics approaches to identify the underlying molecular perturbations and their phenotypic impact. Grouping patients into 408 non-exclusive patient-phenotype groups, we identified a functional association amongst the genes disrupted in 209 (51%) groups. We find evidence for a significant number of molecular interactions amongst the association-contributing genes, including a single highly-interconnected network disrupted in 20% of patients with intellectual disability, and show using microcephaly how these molecular networks can be used as baits to identify additional members whose genes are variant in other patients with the same phenotype. Exploiting the systematic phenotyping of this cohort, we observe phenotypic concordance amongst patients whose variant genes contribute to the same functional association but note that (i) this relationship shows significant variation across the different approaches used to infer a commonly perturbed molecular pathway, and (ii) that the phenotypic similarities detected amongst patients who share the same inferred pathway perturbation result from these patients sharing many distinct phenotypes, rather than sharing a more specific phenotype, inferring that these pathways are best characterized by their pleiotropic effects.

Exposure of Monocytes to Lipoarabinomannan Promotes Their Differentiation into Functionally and Phenotypically Immature Macrophages

Directory of Open Access Journals (Sweden)

Leslie Chávez-Galán

2015-01-01

Full Text Available Lipoarabinomannan (LAM is a lipid virulence factor secreted by Mycobacterium tuberculosis (Mtb, the etiologic agent of tuberculosis. LAM can be measured in the urine or serum of tuberculosis patients (TB-patients. Circulating monocytes are the precursor cells of alveolar macrophages and might be exposed to LAM in patients with active TB. We speculated that exposing monocytes to LAM could produce phenotypically and functionally immature macrophages. To test our hypothesis, human monocytes were stimulated with LAM (24–120 hours and various readouts were measured. The study showed that when monocytes were exposed to LAM, the frequency of CD68+, CD33+, and CD86+ macrophages decreased, suggesting that monocyte differentiation into mature macrophages was affected. Regarding functionality markers, TLR2+ and TLR4+ macrophages also decreased, but the percentage of MMR+ expression did not change. LAM-exposed monocytes generated macrophages that were less efficient in producing proinflammatory cytokines such as TNF-α and IFN-γ; however, their phagocytic capacity was not modified. Taken together, these data indicate that LAM exposure influenced monocyte differentiation and produced poorly functional macrophages with a different phenotype. These results may help us understand how mycobacteria can limit the quality of the innate and adaptive immune responses.

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Predictive pulmonary-function value calculator... SERVICES (CONTINUED) MEDICAL DEVICES ANESTHESIOLOGY DEVICES Diagnostic Devices § 868.1890 Predictive pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

Bypassing Evolutionary Roadblocks: Phenotypic Diversity in Isogenic Population Bridges Tradeoff in Evolution of a New Function

Science.gov (United States)

Petrie, K. L.; Meyer, J. R.

2017-07-01

A novel mechanism of innovation bridges fitness valleys by violating the one gene-one phenotype dogma. Protein products of a single gene partition into populations, some of which carry out a new function and some the old, avoiding tradeoffs.

Phenotypic and Functional Properties of Tumor-Infiltrating Regulatory T Cells

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Gap Ryol Lee

2017-01-01

Full Text Available Regulatory T (Treg cells maintain immune homeostasis by suppressing excessive immune responses. Treg cells induce tolerance against self- and foreign antigens, thus preventing autoimmunity, allergy, graft rejection, and fetus rejection during pregnancy. However, Treg cells also infiltrate into tumors and inhibit antitumor immune responses, thus inhibiting anticancer therapy. Depleting whole Treg cell populations in the body to enhance anticancer treatments will produce deleterious autoimmune diseases. Therefore, understanding the precise nature of tumor-infiltrating Treg cells is essential for effectively targeting Treg cells in tumors. This review summarizes recent results relating to Treg cells in the tumor microenvironment, with particular emphasis on their accumulation, phenotypic, and functional properties, and targeting to enhance the efficacy of anticancer treatment.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze

2015-06-09

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

KAUST Repository

Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

2015-01-01

Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

Phenotypic and functional characterization of human mammary stem/progenitor cells in long term culture.

Directory of Open Access Journals (Sweden)

Devaveena Dey

Full Text Available BACKGROUND: Cancer stem cells exhibit close resemblance to normal stem cells in phenotype as well as function. Hence, studying normal stem cell behavior is important in understanding cancer pathogenesis. It has recently been shown that human breast stem cells can be enriched in suspension cultures as mammospheres. However, little is known about the behavior of these cells in long-term cultures. Since extensive self-renewal potential is the hallmark of stem cells, we undertook a detailed phenotypic and functional characterization of human mammospheres over long-term passages. METHODOLOGY: Single cell suspensions derived from human breast 'organoids' were seeded in ultra low attachment plates in serum free media. Resulting primary mammospheres after a week (termed T1 mammospheres were subjected to passaging every 7th day leading to the generation of T2, T3, and T4 mammospheres. PRINCIPAL FINDINGS: We show that primary mammospheres contain a distinct side-population (SP that displays a CD24(low/CD44(low phenotype, but fails to generate mammospheres. Instead, the mammosphere-initiating potential rests within the CD44(high/CD24(low cells, in keeping with the phenotype of breast cancer-initiating cells. In serial sphere formation assays we find that even though primary (T1 mammospheres show telomerase activity and fourth passage T4 spheres contain label-retaining cells, they fail to initiate new mammospheres beyond T5. With increasing passages, mammospheres showed an increase in smaller sized spheres, reduction in proliferation potential and sphere forming efficiency, and increased differentiation towards the myoepithelial lineage. Significantly, staining for senescence-associated beta-galactosidase activity revealed a dramatic increase in the number of senescent cells with passage, which might in part explain the inability to continuously generate mammospheres in culture. CONCLUSIONS: Thus, the self-renewal potential of human breast stem cells is

Integrating environmental and genetic effects to predict responses of tree populations to climate.

Science.gov (United States)

Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

2010-01-01

Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

Prediction Error During Functional and Non-Functional Action Sequences

DEFF Research Database (Denmark)

Nielbo, Kristoffer Laigaard; Sørensen, Jesper

2013-01-01

recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....

The function and failure of sensory predictions.

Science.gov (United States)

Bansal, Sonia; Ford, Judith M; Spering, Miriam

2018-04-23

Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

Functional validation of candidate genes detected by genomic feature models

DEFF Research Database (Denmark)

Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

2018-01-01

to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) cate- gories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated......Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...

Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

Science.gov (United States)

Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

2018-01-01

ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

Abnormalities of lymphocyte function and phenotypic pattern in a case of toxic epidermal necrolysis

DEFF Research Database (Denmark)

Hagdrup, H; Tønnesen, E; Clemmensen, O

1992-01-01

We examined the blood lymphocyte function and phenotypic pattern in a patient with toxic epidermal necrolysis after taking salazopyrin. We studied cell surface markers, natural killer cell activity and mitogen-induced lymphocyte transformation. Our results point to temporary immunosuppression...... as evidenced by lymphopenia with a large "null cell" population, reduced natural killer cell activity, and impaired lymphocyte response to mitogens....

Assessing the Efficiency of Phenotyping Early Traits in a Greenhouse Automated Platform for Predicting Drought Tolerance of Soybean in the Field.

Science.gov (United States)

Peirone, Laura S; Pereyra Irujo, Gustavo A; Bolton, Alejandro; Erreguerena, Ignacio; Aguirrezábal, Luis A N

2018-01-01

Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes. A group of genotypes was evaluated, which showed variation in their drought susceptibility index (DSI) for final biomass and leaf area. A large number of traits were measured before and after the onset of a water deficit treatment, which were analyzed under several criteria: the significance of the regression with the DSI, phenotyping cost, earliness, and repeatability. The most efficient trait was found to be transpiration efficiency measured at 13 days after emergence. This trait was further tested in a second experiment with different water deficit intensities, and validated using a different set of genotypes against field data from a trial network in a third experiment. The framework applied in this work for assessing traits under different criteria could be helpful for selecting those most efficient for automated phenotyping.

Assessing the Efficiency of Phenotyping Early Traits in a Greenhouse Automated Platform for Predicting Drought Tolerance of Soybean in the Field

Directory of Open Access Journals (Sweden)

Laura S. Peirone

2018-05-01

Full Text Available Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes. A group of genotypes was evaluated, which showed variation in their drought susceptibility index (DSI for final biomass and leaf area. A large number of traits were measured before and after the onset of a water deficit treatment, which were analyzed under several criteria: the significance of the regression with the DSI, phenotyping cost, earliness, and repeatability. The most efficient trait was found to be transpiration efficiency measured at 13 days after emergence. This trait was further tested in a second experiment with different water deficit intensities, and validated using a different set of genotypes against field data from a trial network in a third experiment. The framework applied in this work for assessing traits under different criteria could be helpful for selecting those most efficient for automated phenotyping.

Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics

DEFF Research Database (Denmark)

de Angelis, Martin Hrabě; Nicholson, George; Selloum, Mohammed

2015-01-01

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies...

COPD phenotypes on computed tomography and its correlation with selected lung function variables in severe patients

Directory of Open Access Journals (Sweden)

da Silva SMD

2016-03-01

Full Text Available Silvia Maria Doria da Silva, Ilma Aparecida Paschoal, Eduardo Mello De Capitani, Marcos Mello Moreira, Luciana Campanatti Palhares, Mônica Corso PereiraPneumology Service, Department of Internal Medicine, School of Medical Sciences, State University of Campinas (UNICAMP, Campinas, São Paulo, BrazilBackground: Computed tomography (CT phenotypic characterization helps in understanding the clinical diversity of chronic obstructive pulmonary disease (COPD patients, but its clinical relevance and its relationship with functional features are not clarified. Volumetric capnography (VC uses the principle of gas washout and analyzes the pattern of CO2 elimination as a function of expired volume. The main variables analyzed were end-tidal concentration of carbon dioxide (ETCO2, Slope of phase 2 (Slp2, and Slope of phase 3 (Slp3 of capnogram, the curve which represents the total amount of CO2 eliminated by the lungs during each breath.Objective: To investigate, in a group of patients with severe COPD, if the phenotypic analysis by CT could identify different subsets of patients, and if there was an association of CT findings and functional variables.Subjects and methods: Sixty-five patients with COPD Gold III–IV were admitted for clinical evaluation, high-resolution CT, and functional evaluation (spirometry, 6-minute walk test [6MWT], and VC. The presence and profusion of tomography findings were evaluated, and later, the patients were identified as having emphysema (EMP or airway disease (AWD phenotype. EMP and AWD groups were compared; tomography findings scores were evaluated versus spirometric, 6MWT, and VC variables.Results: Bronchiectasis was found in 33.8% and peribronchial thickening in 69.2% of the 65 patients. Structural findings of airways had no significant correlation with spirometric variables. Air trapping and EMP were strongly correlated with VC variables, but in opposite directions. There was some overlap between the EMP and AWD

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism’s genome (such as the mouse genome in order to make physiological inferences about the role of genes and proteins in a less characterized organism’s genome (such as the Burmese python. We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1 production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2 enhanced assisted reproduction technology for endangered and captive reptiles; and (3 novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

Roles for text mining in protein function prediction.

Science.gov (United States)

Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

Biopsychosocial influence on exercise-induced injury: genetic and psychological combinations are predictive of shoulder pain phenotypes.

Science.gov (United States)

George, Steven Z; Parr, Jeffrey J; Wallace, Margaret R; Wu, Samuel S; Borsa, Paul A; Dai, Yunfeng; Fillingim, Roger B

2014-01-01

Chronic pain is influenced by biological, psychological, social, and cultural factors. The current study investigated potential roles for combinations of genetic and psychological factors in the development and/or maintenance of chronic musculoskeletal pain. An exercise-induced shoulder injury model was used, and a priori selected genetic (ADRB2, COMT, OPRM1, AVPR1 A, GCH1, and KCNS1) and psychological (anxiety, depressive symptoms, pain catastrophizing, fear of pain, and kinesiophobia) factors were included as predictors. Pain phenotypes were shoulder pain intensity (5-day average and peak reported on numerical rating scale), upper extremity disability (5-day average and peak reported on the QuickDASH), and shoulder pain duration (in days). After controlling for age, sex, and race, the genetic and psychological predictors were entered as main effects and interaction terms in separate regression models for the different pain phenotypes. Results from the recruited cohort (N = 190) indicated strong statistical evidence for interactions between the COMT diplotype and 1) pain catastrophizing for 5-day average upper extremity disability and 2) depressive symptoms for pain duration. There was moderate statistical evidence for interactions for other shoulder pain phenotypes between additional genes (ADRB2, AVPR1 A, and KCNS1) and depressive symptoms, pain catastrophizing, or kinesiophobia. These findings confirm the importance of the combined predictive ability of COMT with psychological distress and reveal other novel combinations of genetic and psychological factors that may merit additional investigation in other pain cohorts. Interactions between genetic and psychological factors were investigated as predictors of different exercise-induced shoulder pain phenotypes. The strongest statistical evidence was for interactions between the COMT diplotype and pain catastrophizing (for upper extremity disability) or depressive symptoms (for pain duration). Other novel

Rumination prospectively predicts executive functioning impairments in adolescents.

Science.gov (United States)

Connolly, Samantha L; Wagner, Clara A; Shapero, Benjamin G; Pendergast, Laura L; Abramson, Lyn Y; Alloy, Lauren B

2014-03-01

The current study tested the resource allocation hypothesis, examining whether baseline rumination or depressive symptom levels prospectively predicted deficits in executive functioning in an adolescent sample. The alternative to this hypothesis was also evaluated by testing whether lower initial levels of executive functioning predicted increases in rumination or depressive symptoms at follow-up. A community sample of 200 adolescents (ages 12-13) completed measures of depressive symptoms, rumination, and executive functioning at baseline and at a follow-up session approximately 15 months later. Adolescents with higher levels of baseline rumination displayed decreases in selective attention and attentional switching at follow-up. Rumination did not predict changes in working memory or sustained and divided attention. Depressive symptoms were not found to predict significant changes in executive functioning scores at follow-up. Baseline executive functioning was not associated with change in rumination or depression over time. Findings partially support the resource allocation hypothesis that engaging in ruminative thoughts consumes cognitive resources that would otherwise be allocated towards difficult tests of executive functioning. Support was not found for the alternative hypothesis that lower levels of initial executive functioning would predict increased rumination or depressive symptoms at follow-up. Our study is the first to find support for the resource allocation hypothesis using a longitudinal design and an adolescent sample. Findings highlight the potentially detrimental effects of rumination on executive functioning during early adolescence. Copyright © 2013 Elsevier Ltd. All rights reserved.

Association of single nucleotide polymorphisms in candidate genes previously related to genetic variation in fertility with phenotypic measurements of reproductive function in Holstein cows.

Science.gov (United States)

Ortega, M Sofia; Denicol, Anna C; Cole, John B; Null, Daniel J; Taylor, Jeremy F; Schnabel, Robert D; Hansen, Peter J

2017-05-01

Many genetic markers related to health or production traits are not evaluated in populations independent of the discovery population or related to phenotype. Here we evaluated 68 single nucleotide polymorphisms (SNP) in candidate genes previously associated with genetic merit for fertility and production traits for association with phenotypic measurements of fertility in a population of Holstein cows that was selected based on predicted transmitting ability (PTA) for daughter pregnancy rate (DPR; high, ≥1, n = 989; low, ≤ -1.0, n = 1,285). Cows with a high PTA for DPR had higher pregnancy rate at first service, fewer services per conception, and fewer days open than cows with a low PTA for DPR. Of the 68 SNP, 11 were associated with pregnancy rate at first service, 16 with services per conception, and 19 with days open. Single nucleotide polymorphisms in 12 genes (BDH2, BSP3, CAST, CD2, CD14, FUT1, FYB, GCNT3, HSD17B7, IBSP, OCLN, and PCCB) had significant associations with 2 fertility traits, and SNP in 4 genes (CSPP1, FCER1G, PMM2, and TBC1D24) had significant associations with each of the 3 traits. Results from this experiment were compared with results from 2 earlier studies in which the SNP were associated with genetic estimates of fertility. One study involved the same animals as used here, and the other study was of an independent population of bulls. A total of 13 SNP associated with 1 or more phenotypic estimates of fertility were directionally associated with genetic estimates of fertility in the same cow population. Moreover, 14 SNP associated with reproductive phenotype were directionally associated with genetic estimates of fertility in the bull population. Nine SNP (located in BCAS, BSP3, CAST, FUT1, HSD17B7, OCLN, PCCB, PMM2, and TBC1D24) had a directional association with fertility in all 3 studies. Examination of the function of the genes with SNP associated with reproduction in more than one study indicates the importance of steroid hormones

Sex Differences Influencing Micro- and Macrovascular Endothelial Phenotype In Vitro.

Science.gov (United States)

Huxley, Virginia H; Kemp, Scott S; Schramm, Christine; Sieveking, Steve; Bingaman, Susan; Yu, Yang; Zaniletti, Isabella; Stockard, Kevin; Wang, Jianjie

2018-06-09

(macro- versus microvessel) and sex influenced multiple phenotypic characteristics. Statistical model analysis of EC growth demonstrated an hierarchy of variable importance, recapitulated for other phenotypic characteristics, wherein predictions assuming EC homogeneity Sex Sex and Vessel Origin. Further, patterns of EC mRNA expression by vessel origin and by sex did not predict protein expression. Overall the study demonstrated that accurate assessment of sex-linked EC dysfunction first requires understanding of EC function by position in the vascular tree and by sex. Results from a single EC tissue source/species/sex cannot provide universal insight into the mechanisms regulating in vivo endothelial function in health, no less disease. (250) This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Human Intellectual Disability Genes Form Conserved Functional Modules in Drosophila

Science.gov (United States)

Oortveld, Merel A. W.; Keerthikumar, Shivakumar; Oti, Martin; Nijhof, Bonnie; Fernandes, Ana Clara; Kochinke, Korinna; Castells-Nobau, Anna; van Engelen, Eva; Ellenkamp, Thijs; Eshuis, Lilian; Galy, Anne; van Bokhoven, Hans; Habermann, Bianca; Brunner, Han G.; Zweier, Christiane; Verstreken, Patrik; Huynen, Martijn A.; Schenck, Annette

2013-01-01

Intellectual Disability (ID) disorders, defined by an IQ below 70, are genetically and phenotypically highly heterogeneous. Identification of common molecular pathways underlying these disorders is crucial for understanding the molecular basis of cognition and for the development of therapeutic intervention strategies. To systematically establish their functional connectivity, we used transgenic RNAi to target 270 ID gene orthologs in the Drosophila eye. Assessment of neuronal function in behavioral and electrophysiological assays and multiparametric morphological analysis identified phenotypes associated with knockdown of 180 ID gene orthologs. Most of these genotype-phenotype associations were novel. For example, we uncovered 16 genes that are required for basal neurotransmission and have not previously been implicated in this process in any system or organism. ID gene orthologs with morphological eye phenotypes, in contrast to genes without phenotypes, are relatively highly expressed in the human nervous system and are enriched for neuronal functions, suggesting that eye phenotyping can distinguish different classes of ID genes. Indeed, grouping genes by Drosophila phenotype uncovered 26 connected functional modules. Novel links between ID genes successfully predicted that MYCN, PIGV and UPF3B regulate synapse development. Drosophila phenotype groups show, in addition to ID, significant phenotypic similarity also in humans, indicating that functional modules are conserved. The combined data indicate that ID disorders, despite their extreme genetic diversity, are caused by disruption of a limited number of highly connected functional modules. PMID:24204314

Loss-of-function and gain-of-function phenotypes of stomatocytosis mutant RhAG F65S

Science.gov (United States)

Stewart, Andrew K.; Shmukler, Boris E.; Vandorpe, David H.; Rivera, Alicia; Heneghan, John F.; Li, Xiaojin; Hsu, Ann; Karpatkin, Margaret; O'Neill, Allison F.; Bauer, Daniel E.; Heeney, Matthew M.; John, Kathryn; Kuypers, Frans A.; Gallagher, Patrick G.; Lux, Samuel E.; Brugnara, Carlo; Westhoff, Connie M.

2011-01-01

Four patients with overhydrated cation leak stomatocytosis (OHSt) exhibited the heterozygous RhAG missense mutation F65S. OHSt erythrocytes were osmotically fragile, with elevated Na and decreased K contents and increased cation channel-like activity. Xenopus oocytes expressing wild-type RhAG and RhAG F65S exhibited increased ouabain and bumetanide-resistant uptake of Li+ and 86Rb+, with secondarily increased 86Rb+ influx sensitive to ouabain and to bumetanide. Increased RhAG-associated 14C-methylammonium (MA) influx was severely reduced in RhAG F65S-expressing oocytes. RhAG-associated influxes of Li+, 86Rb+, and 14C-MA were pharmacologically distinct, and Li+ uptakes associated with RhAG and RhAG F65S were differentially inhibited by NH4+ and Gd3+. RhAG-expressing oocytes were acidified and depolarized by 5 mM bath NH3/NH4+, but alkalinized and depolarized by subsequent bath exposure to 5 mM methylammonium chloride (MA/MA+). RhAG F65S-expressing oocytes exhibited near-wild-type responses to NH4Cl, but MA/MA+ elicited attenuated alkalinization and strong hyperpolarization. Expression of RhAG or RhAG F65S increased steady-state cation currents unaltered by bath Li+ substitution or bath addition of 5 mM NH4Cl or MA/MA+. These oocyte studies suggest that 1) RhAG expression increases oocyte transport of NH3/NH4+ and MA/MA+; 2) RhAG F65S exhibits gain-of-function phenotypes of increased cation conductance/permeability, and loss-of-function phenotypes of decreased and modified MA/MA+ transport, and decreased NH3/NH4+-associated depolarization; and 3) RhAG transports NH3/NH4+ and MA/MA+ by distinct mechanisms, and/or the substrates elicit distinct cellular responses. Thus, RhAG F65S is a loss-of-function mutation for amine transport. The altered oocyte intracellular pH, membrane potential, and currents associated with RhAG or RhAG F65S expression may reflect distinct transport mechanisms. PMID:21849667

Development of a Functional Schwann Cell Phenotype from Autologous Porcine Bone Marrow Mononuclear Cells for Nerve Repair

Directory of Open Access Journals (Sweden)

Michael J. Rutten

2012-01-01

Full Text Available Adult bone marrow mononuclear cells (BM-MNCs are a potential resource for making Schwann cells to repair damaged peripheral nerves. However, many methods of producing Schwann-like cells can be laborious with the cells lacking a functional phenotype. The objective of this study was to develop a simple and rapid method using autologous BM-MNCs to produce a phenotypic and functional Schwann-like cell. Adult porcine bone marrow was collected and enriched for BM-MNCs using a SEPAX device, then cells cultured in Neurobasal media, 4 mM L-glutamine and 20% serum. After 6–8 days, the cultures expressed Schwann cell markers, S-100, O4, GFAP, were FluoroMyelin positive, but had low p75(NGF expression. Addition of neuregulin (1–25 nM increased p75(NGF levels at 24–48 hrs. We found ATP dose-dependently increased intracellular calcium [Ca2+]i, with nucleotide potency being UTP=ATP>ADP>AMP>adenosine. Suramin blocked the ATP-induced [Ca2+]i but α, β,-methylene-ATP had little effect suggesting an ATP purinergic P2Y2 G-protein-coupled receptor is present. Both the Schwann cell markers and ATP-induced [Ca2+]i sensitivity decreased in cells passaged >20 times. Our studies indicate that autologous BM-MNCs can be induced to form a phenotypic and functional Schwann-like cell which could be used for peripheral nerve repair.

One gene, many phenotypes | Shawky | Egyptian Journal of Medical ...

African Journals Online (AJOL)

... mechanisms underlying genotype-phenotype discrepancies is important, as it will move clinical genetics towards predictive medicine, allowing better selection of therapeutic strategies and individualized counseling of persons affected with genetic disorders. Keywords: Gene, phenotype, mosaicism, epigenetics, pleiotropy ...

Effect of breast cancer phenotype on diagnostic performance of MRI in the prediction to response to neoadjuvant treatment

Energy Technology Data Exchange (ETDEWEB)

Bufi, Enida, E-mail: reagandus@alice.it [Department of Bioimaging and Radiological Sciences, Catholic University, Rome (Italy); Belli, Paolo; Di Matteo, Marialuisa [Department of Bioimaging and Radiological Sciences, Catholic University, Rome (Italy); Terribile, Daniela; Franceschini, Gianluca [Department of Surgery, Breast Unit, Catholic University, Rome (Italy); Nardone, Luigia [Department of Radiotherapy, Catholic University, Rome (Italy); Petrone, Gianluigi [Department of Pathology, Catholic University, Rome (Italy); Bonomo, Lorenzo [Department of Bioimaging and Radiological Sciences, Catholic University, Rome (Italy)

2014-09-15

Aim: The estimation of response to neoadjuvant chemotherapy (NAC) is useful in the surgical decision in breast cancer. We addressed the diagnostic reliability of conventional MRI, of diffusion weighted imaging (DWI) and of a merged criterion coupling morphological MRI and DWI. Diagnostic performance was analysed separately in different tumor subtypes, including HER2+ (human epidermal growth factor receptor 2)/HR+ (hormone receptor) (hybrid phenotype). Materials and methods: Two-hundred and twenty-five patients underwent MRI before and after NAC. The response to treatment was defined according to the RECIST classification and the evaluation of DWI with apparent diffusion coefficient (ADC). The complete pathological response – pCR was assessed (Mandard classification). Results: Tumor phenotypes were Luminal (63.6%), Triple Negative (16.4%), HER2+ (7.6%) or Hybrid (12.4%). After NAC, pCR was observed in 17.3% of cases. Average ADC was statistically higher after NAC (p < 0.001) among patients showing pCR vs. those who had not pCR. The RECIST classification showed adequate performance in predicting the pCR in Triple Negative (area under the receiver operating characteristic curve, ROC AUC = 0.9) and in the HER2+ subgroup (AUC = 0.826). Lower performance was found in the Luminal and Hybrid subgroups (AUC 0.693 and 0.611, respectively), where the ADC criterion yielded an improved performance (AUC = 0.787 and 0.722). The coupling of morphological and DWI criteria yielded maximally improved performance in the Luminal and Hybrid subgroups (AUC = 0.797 and 0.761). Conclusion: The diagnostic reliability of MRI in predicting the pCR to NAC depends on the tumor phenotype, particularly in the Luminal and Hybrid subgroups. In these cases, the coupling of morphological MRI evaluation and DWI assessment may facilitate the diagnosis.

Altered Functional Subnetwork During Emotional Face Processing: A Potential Intermediate Phenotype for Schizophrenia.

Science.gov (United States)

Cao, Hengyi; Bertolino, Alessandro; Walter, Henrik; Schneider, Michael; Schäfer, Axel; Taurisano, Paolo; Blasi, Giuseppe; Haddad, Leila; Grimm, Oliver; Otto, Kristina; Dixson, Luanna; Erk, Susanne; Mohnke, Sebastian; Heinz, Andreas; Romanczuk-Seiferth, Nina; Mühleisen, Thomas W; Mattheisen, Manuel; Witt, Stephanie H; Cichon, Sven; Noethen, Markus; Rietschel, Marcella; Tost, Heike; Meyer-Lindenberg, Andreas

2016-06-01

Although deficits in emotional processing are prominent in schizophrenia, it has been difficult to identify neural mechanisms related to the genetic risk for this highly heritable illness. Prior studies have not found consistent regional activation or connectivity alterations in first-degree relatives compared with healthy controls, suggesting that a more comprehensive search for connectomic biomarkers is warranted. To identify a potential systems-level intermediate phenotype linked to emotion processing in schizophrenia and to examine the psychological association, task specificity, test-retest reliability, and clinical validity of the identified phenotype. The study was performed in university research hospitals from June 1, 2008, through December 31, 2013. We examined 58 unaffected first-degree relatives of patients with schizophrenia and 94 healthy controls with an emotional face-matching functional magnetic resonance imaging paradigm. Test-retest reliability was analyzed with an independent sample of 26 healthy participants. A clinical association study was performed in 31 patients with schizophrenia and 45 healthy controls. Data analysis was performed from January 1 to September 30, 2014. Conventional amygdala activity and seeded connectivity measures, graph-based global and local network connectivity measures, Spearman rank correlation, intraclass correlation, and gray matter volumes. Among the 152 volunteers included in the relative-control sample, 58 were unaffected first-degree relatives of patients with schizophrenia (mean [SD] age, 33.29 [12.56]; 38 were women), and 94 were healthy controls without a first-degree relative with mental illness (mean [SD] age, 32.69 [10.09] years; 55 were women). A graph-theoretical connectivity approach identified significantly decreased connectivity in a subnetwork that primarily included the limbic cortex, visual cortex, and subcortex during emotional face processing (cluster-level P corrected for familywise error =�

Quality Control Test for Sequence-Phenotype Assignments

Science.gov (United States)

Ortiz, Maria Teresa Lara; Rosario, Pablo Benjamín Leon; Luna-Nevarez, Pablo; Gamez, Alba Savin; Martínez-del Campo, Ana; Del Rio, Gabriel

2015-01-01

Relating a gene mutation to a phenotype is a common task in different disciplines such as protein biochemistry. In this endeavour, it is common to find false relationships arising from mutations introduced by cells that may be depurated using a phenotypic assay; yet, such phenotypic assays may introduce additional false relationships arising from experimental errors. Here we introduce the use of high-throughput DNA sequencers and statistical analysis aimed to identify incorrect DNA sequence-phenotype assignments and observed that 10–20% of these false assignments are expected in large screenings aimed to identify critical residues for protein function. We further show that this level of incorrect DNA sequence-phenotype assignments may significantly alter our understanding about the structure-function relationship of proteins. We have made available an implementation of our method at http://bis.ifc.unam.mx/en/software/chispas. PMID:25700273

Functional Coding Variation in Recombinant Inbred Mouse Lines Reveals Novel Serotonin Transporter-Associated Phenotypes

Energy Technology Data Exchange (ETDEWEB)

Carneiro, Ana [Vanderbilt University; Airey, David [University of Tennessee Health Science Center, Memphis; Thompson, Brent [Vanderbilt University; Zhu, C [Vanderbilt University; Rinchik, Eugene M [ORNL; Lu, Lu [University of Tennessee Health Science Center, Memphis; Chesler, Elissa J [ORNL; Erikson, Keith [University of North Carolina; Blakely, Randy [Vanderbilt University

2009-01-01

The human serotonin (5-hydroxytryptamine, 5-HT) transporter (hSERT, SLC6A4) figures prominently in the etiology or treatment of many prevalent neurobehavioral disorders including anxiety, alcoholism, depression, autism and obsessive-compulsive disorder (OCD). Here we utilize naturally occurring polymorphisms in recombinant inbred (RI) lines to identify novel phenotypes associated with altered SERT function. The widely used mouse strain C57BL/6J, harbors a SERT haplotype defined by two nonsynonymous coding variants (Gly39 and Lys152 (GK)). At these positions, many other mouse lines, including DBA/2J, encode Glu39 and Arg152 (ER haplotype), assignments found also in hSERT. Synaptosomal 5-HT transport studies revealed reduced uptake associated with the GK variant. Heterologous expression studies confirmed a reduced SERT turnover rate for the GK variant. Experimental and in silico approaches using RI lines (C57Bl/6J X DBA/2J=BXD) identifies multiple anatomical, biochemical and behavioral phenotypes specifically impacted by GK/ER variation. Among our findings are multiple traits associated with anxiety and alcohol consumption, as well as of the control of dopamine (DA) signaling. Further bioinformatic analysis of BXD phenotypes, combined with biochemical evaluation of SERT knockout mice, nominates SERT-dependent 5-HT signaling as a major determinant of midbrain iron homeostasis that, in turn, dictates ironregulated DA phenotypes. Our studies provide a novel example of the power of coordinated in vitro, in vivo and in silico approaches using murine RI lines to elucidate and quantify the system-level impact of gene variation.

IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

Directory of Open Access Journals (Sweden)

N Lance Hepler

2014-09-01

Full Text Available Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab, determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license, documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

Elucidating the genotype-phenotype map by automatic enumeration and analysis of the phenotypic repertoire.

Science.gov (United States)

Lomnitz, Jason G; Savageau, Michael A

The gap between genotype and phenotype is filled by complex biochemical systems most of which are poorly understood. Because these systems are complex, it is widely appreciated that quantitative understanding can only be achieved with the aid of mathematical models. However, formulating models and measuring or estimating their numerous rate constants and binding constants is daunting. Here we present a strategy for automating difficult aspects of the process. The strategy, based on a system design space methodology, is applied to a class of 16 designs for a synthetic gene oscillator that includes seven designs previously formulated on the basis of experimentally measured and estimated parameters. Our strategy provides four important innovations by automating: (1) enumeration of the repertoire of qualitatively distinct phenotypes for a system; (2) generation of parameter values for any particular phenotype; (3) simultaneous realization of parameter values for several phenotypes to aid visualization of transitions from one phenotype to another, in critical cases from functional to dysfunctional; and (4) identification of ensembles of phenotypes whose expression can be phased to achieve a specific sequence of functions for rationally engineering synthetic constructs. Our strategy, applied to the 16 designs, reproduced previous results and identified two additional designs capable of sustained oscillations that were previously missed. Starting with a system's relatively fixed aspects, its architectural features, our method enables automated analysis of nonlinear biochemical systems from a global perspective, without first specifying parameter values. The examples presented demonstrate the efficiency and power of this automated strategy.

Advanced phenotyping and phenotype data analysis for the plant growth and development study

Directory of Open Access Journals (Sweden)

Md. Matiur eRahaman

2015-08-01

Full Text Available Due to increase in the consumption of food, feed, fuel and to ensure global food security for rapidly growing human population, there is need to breed high yielding crops that can adapt to future climate. To solve these global issues, novel approaches are required to provide quantitative phenotypes to elucidate the genetic basis of agriculturally import traits and to screen germplasm with super performance in function under resource-limited environment. At present, plant phenomics has offered and integrated suite technologies for understanding the complete set of phenotypes of plants, towards the progression of the full characteristics of plants with whole sequenced genomes. In this aspect, high-throughput phenotyping platforms have been developed that enables to capture extensive and intensive phenotype data from non-destructive imaging over time. These developments advance our view on plant growth and performance with responses to the changing climate and environment. In this paper, we present a brief review on currently developed high-throughput plant phenotyping infrastructures based on imaging techniques and corresponding principles for phenotype data analysis.

The rice growth image files - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us The Rice Growth Monitoring for The Phenotypic Functional Analysis The rice growth image file...s Data detail Data name The rice growth image files DOI 10.18908/lsdba.nbdc00945-004 Description of data contents The rice growth ima...ge files categorized based on file size. Data file File name: image files (director...y) File URL: ftp://ftp.biosciencedbc.jp/archive/agritogo-rice-phenome/LATEST/image...ite Policy | Contact Us The rice growth image files - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive ...

Developmental Research in Space: Predicting Adult Neurobehavioral Phenotypes via Metabolomic Imaging

Science.gov (United States)

Schorn, Julia M.; Moyer, Eric L.; Lowe, Moniece M.; Morgan, Jonathan; Tulbert, Christina D.; Olson, John; Olson, John; Horita, David A.; Kleven, Gale A.

2017-01-01

As human habitation and eventual colonization of space becomes an inevitable reality, there is a necessity to understand how organisms develop over the life span in the space environment. Microgravity, altered CO2, radiation and psychological stress are some of the key factors that could affect mammalian reproduction and development in space, however there is a paucity of information on this topic. Here we combine early (neonatal) in vivo spectroscopic imaging with an adult emotionality assay following a common obstetric complication (prenatal asphyxia) likely to occur during gestation in space. The neural metabolome is sensitive to alteration by degenerative changes and developmental disorders, thus we hypothesized that that early neonatal neurometabolite profiles can predict adult response to novelty. Late gestation fetal rats were exposed to moderate asphyxia by occluding the blood supply feeding one of the rats pair uterine horns for 15min. Blood supply to the opposite horn was not occluded (within-litter cesarean control). Further comparisons were made with vaginal (natural) birth controls. In one-week old neonates, we measured neurometabolites in three brain areas (i.e., striatum, prefrontal cortex, and hippocampus). Adult perinatally-asphyxiated offspring exhibited greater anxiety-like behavioral phenotypes (as measured the composite neurobehavioral assay involving open field activity, responses to novel object, quantification of fecal droppings, and resident-intruder tests of social behavior). Further, early neurometabolite profiles predicted adult responses. Non-invasive MRS screening of mammalian offspring is likely to advance ground-based space analogue studies informing mammalian reproduction in space, and achieving high-priority.

De Novo and Inherited Loss-of-Function Variants in TLK2: Clinical and Genotype-Phenotype Evaluation of a Distinct Neurodevelopmental Disorder.

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Reijnders, Margot R F; Miller, Kerry A; Alvi, Mohsan; Goos, Jacqueline A C; Lees, Melissa M; de Burca, Anna; Henderson, Alex; Kraus, Alison; Mikat, Barbara; de Vries, Bert B A; Isidor, Bertrand; Kerr, Bronwyn; Marcelis, Carlo; Schluth-Bolard, Caroline; Deshpande, Charu; Ruivenkamp, Claudia A L; Wieczorek, Dagmar; Baralle, Diana; Blair, Edward M; Engels, Hartmut; Lüdecke, Hermann-Josef; Eason, Jacqueline; Santen, Gijs W E; Clayton-Smith, Jill; Chandler, Kate; Tatton-Brown, Katrina; Payne, Katelyn; Helbig, Katherine; Radtke, Kelly; Nugent, Kimberly M; Cremer, Kirsten; Strom, Tim M; Bird, Lynne M; Sinnema, Margje; Bitner-Glindzicz, Maria; van Dooren, Marieke F; Alders, Marielle; Koopmans, Marije; Brick, Lauren; Kozenko, Mariya; Harline, Megan L; Klaassens, Merel; Steinraths, Michelle; Cooper, Nicola S; Edery, Patrick; Yap, Patrick; Terhal, Paulien A; van der Spek, Peter J; Lakeman, Phillis; Taylor, Rachel L; Littlejohn, Rebecca O; Pfundt, Rolph; Mercimek-Andrews, Saadet; Stegmann, Alexander P A; Kant, Sarina G; McLean, Scott; Joss, Shelagh; Swagemakers, Sigrid M A; Douzgou, Sofia; Wall, Steven A; Küry, Sébastien; Calpena, Eduardo; Koelling, Nils; McGowan, Simon J; Twigg, Stephen R F; Mathijssen, Irene M J; Nellaker, Christoffer; Brunner, Han G; Wilkie, Andrew O M

2018-06-07

Next-generation sequencing is a powerful tool for the discovery of genes related to neurodevelopmental disorders (NDDs). Here, we report the identification of a distinct syndrome due to de novo or inherited heterozygous mutations in Tousled-like kinase 2 (TLK2) in 38 unrelated individuals and two affected mothers, using whole-exome and whole-genome sequencing technologies, matchmaker databases, and international collaborations. Affected individuals had a consistent phenotype, characterized by mild-borderline neurodevelopmental delay (86%), behavioral disorders (68%), severe gastro-intestinal problems (63%), and facial dysmorphism including blepharophimosis (82%), telecanthus (74%), prominent nasal bridge (68%), broad nasal tip (66%), thin vermilion of the upper lip (62%), and upslanting palpebral fissures (55%). Analysis of cell lines from three affected individuals showed that mutations act through a loss-of-function mechanism in at least two case subjects. Genotype-phenotype analysis and comparison of computationally modeled faces showed that phenotypes of these and other individuals with loss-of-function variants significantly overlapped with phenotypes of individuals with other variant types (missense and C-terminal truncating). This suggests that haploinsufficiency of TLK2 is the most likely underlying disease mechanism, leading to a consistent neurodevelopmental phenotype. This work illustrates the power of international data sharing, by the identification of 40 individuals from 26 different centers in 7 different countries, allowing the identification, clinical delineation, and genotype-phenotype evaluation of a distinct NDD caused by mutations in TLK2. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Quantitative Assessment of Eye Phenotypes for Functional Genetic Studies Using Drosophila melanogaster

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Janani Iyer

2016-05-01

Full Text Available About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net, to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions.

Bronchiolitis obliterans syndrome after allogeneic hematopoietic SCT: phenotypes and prognosis.

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Bergeron, A; Godet, C; Chevret, S; Lorillon, G; Peffault de Latour, R; de Revel, T; Robin, M; Ribaud, P; Socié, G; Tazi, A

2013-06-01

Bronchiolitis obliterans syndrome (BOS) after allogeneic hematopoietic SCT (HSCT) is recognized as a new-onset obstructive lung defect (OLD) in pulmonary function testing and is related to pulmonary chronic GVHD. Little is known about the different phenotypes of patients with BOS and their outcomes. We reviewed the data of all allogeneic HSCT recipients referred to our pulmonary department for a non-infectious bronchial disease between 1999 and 2010. We identified 103 patients (BOS (n=77), asthma (n=11) and chronic bronchitis (n=15)). In patients with BOS, we identified two functional phenotypes: a typical OLD, that is, forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio <0.7 (n=53), and an atypical OLD with a concomitant decrease in the FEV1 <80% and FVC <80% predicted with a normal total lung capacity (n=24). The typical OLD was characterized by more severe FEV1 and fewer centrilobular nodules on the computed tomography scan. The FEV1 was not significantly affected during the follow-up, regardless of the phenotype. In addition to acute and extensive chronic GVHD, only the occurrence of BOS soon after transplantation and the intentional treatment of BOS with steroids were associated with a poor survival. The determination of patient subgroups should be explored to improve the management of this condition.

Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies.

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Mueller, Silke C; Drewelow, Bernd

2013-05-01

The area under the concentration-time curve (AUC) after oral midazolam administration is commonly used for cytochrome P450 (CYP) 3A phenotyping studies. The aim of this investigation was to evaluate a limited sampling strategy for the prediction of AUC with oral midazolam. A total of 288 concentration-time profiles from 123 healthy volunteers who participated in four previously performed drug interaction studies with intense sampling after a single oral dose of 7.5 mg midazolam were available for evaluation. Of these, 45 profiles served for model building, which was performed by stepwise multiple linear regression, and the remaining 243 datasets served for validation. Mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were calculated to determine bias and precision The one- to four-sampling point models with the best coefficient of correlation were the one-sampling point model (8 h; r (2) = 0.84), the two-sampling point model (0.5 and 8 h; r (2) = 0.93), the three-sampling point model (0.5, 2, and 8 h; r (2) = 0.96), and the four-sampling point model (0.5,1, 2, and 8 h; r (2) = 0.97). However, the one- and two-sampling point models were unable to predict the midazolam AUC due to unacceptable bias and precision. Only the four-sampling point model predicted the very low and very high midazolam AUC of the validation dataset with acceptable precision and bias. The four-sampling point model was also able to predict the geometric mean ratio of the treatment phase over the baseline (with 90 % confidence interval) results of three drug interaction studies in the categories of strong, moderate, and mild induction, as well as no interaction. A four-sampling point limited sampling strategy to predict the oral midazolam AUC for CYP3A phenotyping is proposed. The one-, two- and three-sampling point models were not able to predict midazolam AUC accurately.

The GP problem: quantifying gene-to-phenotype relationships.

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Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Hyperandrogenemia predicts metabolic phenotype in polycystic ovary syndrome: the utility of serum androstenedione.

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O'Reilly, Michael W; Taylor, Angela E; Crabtree, Nicola J; Hughes, Beverly A; Capper, Farfia; Crowley, Rachel K; Stewart, Paul M; Tomlinson, Jeremy W; Arlt, Wiebke

2014-03-01

Polycystic ovary syndrome (PCOS) is a triad of anovulation, insulin resistance, and hyperandrogenism. Androgen excess may correlate with metabolic risk and PCOS consensus criteria define androgen excess on the basis of serum T. Here we studied the utility of the androgen precursor serum androstenedione (A) in conjunction with serum T for predicting metabolic dysfunction in PCOS. Eighty-six PCOS patients fulfilling Rotterdam diagnostic consensus criteria and 43 age- and body mass index-matched controls underwent measurement of serum androgens by tandem mass spectrometry and an oral glucose tolerance test with homeostatic model assessment of insulin resistance and insulin sensitivity index calculation. We analyzed 24-hour urine androgen excretion by gas chromatography/mass spectrometry. PCOS patients had higher levels of serum androgens and urinary androgen metabolites than controls (all P PCOS cohort, both serum A and T were positively correlated with the free androgen index (T × 100/SHBG) and total androgen metabolite excretion (all P androgen excretion than NA/NT (P androgen phenotype (NA/NT, 0%; HA/NT, 14%; HA/HT, 25%, P = .03). Simultaneous measurement of serum T and A represents a useful tool for predicting metabolic risk in PCOS women. HA levels are a sensitive indicator of PCOS-related androgen excess.

Invited review: overview of new traits and phenotyping strategies in dairy cattle with a focus on functional traits.

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Egger-Danner, C; Cole, J B; Pryce, J E; Gengler, N; Heringstad, B; Bradley, A; Stock, K F

2015-02-01

For several decades, breeding goals in dairy cattle focussed on increased milk production. However, many functional traits have negative genetic correlations with milk yield, and reductions in genetic merit for health and fitness have been observed. Herd management has been challenged to compensate for these effects and to balance fertility, udder health and metabolic diseases against increased production to maximize profit without compromising welfare. Functional traits, such as direct information on cow health, have also become more important because of growing concern about animal well-being and consumer demands for healthy and natural products. There are major concerns about the impact of drugs used in veterinary medicine on the spread of antibiotic-resistant strains of bacteria that can negatively impact human health. Sustainability and efficiency are also increasingly important because of the growing competition for high-quality, plant-based sources of energy and protein. Disruptions to global environments because of climate change may encourage yet more emphasis on these traits. To be successful, it is vital that there be a balance between the effort required for data recording and subsequent benefits. The motivation of farmers and other stakeholders involved in documentation and recording is essential to ensure good data quality. To keep labour costs reasonable, existing data sources should be used as much as possible. Examples include the use of milk composition data to provide additional information about the metabolic status or energy balance of the animals. Recent advances in the use of mid-infrared spectroscopy to measure milk have shown considerable promise, and may provide cost-effective alternative phenotypes for difficult or expensive-to-measure traits, such as feed efficiency. There are other valuable data sources in countries that have compulsory documentation of veterinary treatments and drug use. Additional sources of data outside of the farm

Functional characterization and phenotypic monitoring of human hematopoietic stem cell expansion and differentiation of monocytes and macrophages by whole-cell mass spectrometry

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Guido Vogel

2018-01-01

Full Text Available The different facets of macrophages allow them to play distinct roles in tissue homeostasis, tissue repair and in response to infections. Individuals displaying dysregulated macrophage functions are proposed to be prone to inflammatory disorders or infections. However, this being a cause or a consequence of the pathology remains often unclear. In this context, we isolated and expanded CD34+ HSCs from healthy blood donors and derived them into CD14+ myeloid progenitors which were further enriched and differentiated into macrophages. Aiming for a comprehensive phenotypic profiling, we generated whole-cell mass spectrometry (WCMS fingerprints of cell samples collected along the different stages of the differentiation process to build a predictive model using a linear discriminant analysis based on principal components. Through the capacity of the model to accurately predict sample's identity of a validation set, we demonstrate that WCMS profiles obtained from bona fide blood monocytes and respectively derived macrophages mirror profiles obtained from equivalent HSC derivatives. Finally, HSC-derived macrophage functionalities were assessed by quantifying cytokine and chemokine responses to a TLR agonist in a 34-plex luminex assay and by measuring their capacity to phagocytise mycobacteria. These functional read-outs could not discriminate blood monocytes-derived from HSC-derived macrophages. To conclude, we propose that this method opens new avenues to distinguish the impact of human genetics on the dysregulated biological properties of macrophages in pathological conditions.

SitesIdentify: a protein functional site prediction tool

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Doig Andrew J

2009-11-01

Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

Genomic Prediction of Sunflower Hybrids Oil Content

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Brigitte Mangin

2017-09-01

Full Text Available Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%. Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but

Elucidating the genotype–phenotype map by automatic enumeration and analysis of the phenotypic repertoire

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Lomnitz, Jason G; Savageau, Michael A

2015-01-01

Background: The gap between genotype and phenotype is filled by complex biochemical systems most of which are poorly understood. Because these systems are complex, it is widely appreciated that quantitative understanding can only be achieved with the aid of mathematical models. However, formulating models and measuring or estimating their numerous rate constants and binding constants is daunting. Here we present a strategy for automating difficult aspects of the process. Methods: The strategy, based on a system design space methodology, is applied to a class of 16 designs for a synthetic gene oscillator that includes seven designs previously formulated on the basis of experimentally measured and estimated parameters. Results: Our strategy provides four important innovations by automating: (1) enumeration of the repertoire of qualitatively distinct phenotypes for a system; (2) generation of parameter values for any particular phenotype; (3) simultaneous realization of parameter values for several phenotypes to aid visualization of transitions from one phenotype to another, in critical cases from functional to dysfunctional; and (4) identification of ensembles of phenotypes whose expression can be phased to achieve a specific sequence of functions for rationally engineering synthetic constructs. Our strategy, applied to the 16 designs, reproduced previous results and identified two additional designs capable of sustained oscillations that were previously missed. Conclusions: Starting with a system’s relatively fixed aspects, its architectural features, our method enables automated analysis of nonlinear biochemical systems from a global perspective, without first specifying parameter values. The examples presented demonstrate the efficiency and power of this automated strategy. PMID:26998346

GenomeRNAi: a database for cell-based RNAi phenotypes.

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Horn, Thomas; Arziman, Zeynep; Berger, Juerg; Boutros, Michael

2007-01-01

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible at http://rnai.dkfz.de.

PAF-receptor is preferentially expressed in a distinct synthetic phenotype of smooth muscle cells cloned from human internal thoracic artery: Functional implications in cell migration

International Nuclear Information System (INIS)

Stengel, Dominique; O'Neil, Caroline; Brocheriou, Isabelle; Karabina, Sonia-Athina; Durand, Herve; Caplice, Noel M.; Pickering, J. Geoffrey; Ninio, Ewa

2006-01-01

Platelet-activating-Factor (PAF) and its structural analogues formed upon low density lipoprotein oxidation are involved in atherosclerotic plaque formation and may signal through PAF-receptor (PAF-R) expressed in human macrophages and in certain smooth muscle cells (SMCs) in the media, but rarely in the intima of human plaques. Our aim was to determine which SMC phenotype expresses PAF-R and whether this receptor is functional in cell migration. Circulating SMC progenitors and two phenotypically distinct clones of proliferative, epithelioid phenotype vs contractile, spindle-shaped SMCs from the media of adult internal thoracic artery were studied for the presence of PAF-receptor (PAF-R). The levels of specific mRNA were obtained by reverse transcription/real-time PCR, the protein expression was deduced from immunohistochemistry staining, and the functional transmigration assay was performed by Boyden chamber-type chemotaxis assay. Only SMCs of spindle-shape and synthetic phenotype expressed both mRNA and PAF-R protein and in the functional test migrated at low concentrations of PAF. Two unrelated, specific PAF-R antagonists inhibited PAF-induced migration, but did not modify the migration initiated by PDGF. The presence of functional PAF-R in arterial spindle-shaped SMCs of synthetic phenotype may be important for their migration from the media into the intima and atherosclerotic plaques formation

Ecological transition predictably associated with gene degeneration.

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Wessinger, Carolyn A; Rausher, Mark D

2015-02-01

Gene degeneration or loss can significantly contribute to phenotypic diversification, but may generate genetic constraints on future evolutionary trajectories, potentially restricting phenotypic reversal. Such constraints may manifest as directional evolutionary trends when parallel phenotypic shifts consistently involve gene degeneration or loss. Here, we demonstrate that widespread parallel evolution in Penstemon from blue to red flowers predictably involves the functional inactivation and degeneration of the enzyme flavonoid 3',5'-hydroxylase (F3'5'H), an anthocyanin pathway enzyme required for the production of blue floral pigments. Other types of genetic mutations do not consistently accompany this phenotypic shift. This pattern may be driven by the relatively large mutational target size of degenerative mutations to this locus and the apparent lack of associated pleiotropic effects. The consistent degeneration of F3'5'H may provide a mechanistic explanation for the observed asymmetry in the direction of flower color evolution in Penstemon: Blue to red transitions are common, but reverse transitions have not been observed. Although phenotypic shifts in this system are likely driven by natural selection, internal constraints may generate predictable genetic outcomes and may restrict future evolutionary trajectories. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

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Ross, Mindy K; Yoon, Jinsung; van der Schaar, Auke; van der Schaar, Mihaela

2018-01-01

Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based on the relationship between treatment and clinical outcome has not been performed, and machine learning approaches for long-term outcome prediction in pediatric asthma have not been studied in depth. Our objectives were to use our novel machine learning algorithm, predictor pursuit (PP), to discover pediatric asthma phenotypes on the basis of asthma control in response to controller medications, to predict longitudinal asthma control among children with asthma, and to identify features associated with asthma control within each discovered pediatric phenotype. We applied PP to the Childhood Asthma Management Program study data (n = 1,019) to discover phenotypes on the basis of asthma control between assigned controller therapy groups (budesonide vs. nedocromil). We confirmed PP's ability to discover phenotypes using the Asthma Clinical Research Network/Childhood Asthma Research and Education network data. We next predicted children's asthma control over time and compared PP's performance with that of traditional prediction methods. Last, we identified clinical features most correlated with asthma control in the discovered phenotypes. Four phenotypes were discovered in both datasets: allergic not obese (A + /O - ), obese not allergic (A - /O + ), allergic and obese (A + /O + ), and not allergic not obese (A - /O - ). Of the children with well-controlled asthma in the Childhood Asthma Management Program dataset, we found more nonobese children treated with budesonide than with nedocromil (P = 0.015) and more obese children treated with nedocromil than with budesonide (P = 0.008). Within the obese group, more A + /O + children's asthma was well controlled with nedocromil than with budesonide (P = 0.022) or with placebo

Neural/Bayes network predictor for inheritable cardiac disease pathogenicity and phenotype.

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Burghardt, Thomas P; Ajtai, Katalin

2018-04-11

The cardiac muscle sarcomere contains multiple proteins contributing to contraction energy transduction and its regulation during a heartbeat. Inheritable heart disease mutants affect most of them but none more frequently than the ventricular myosin motor and cardiac myosin binding protein c (mybpc3). These co-localizing proteins have mybpc3 playing a regulatory role to the energy transducing motor. Residue substitution and functional domain assignment of each mutation in the protein sequence decides, under the direction of a sensible disease model, phenotype and pathogenicity. The unknown model mechanism is decided here using a method combing neural and Bayes networks. Missense single nucleotide polymorphisms (SNPs) are clues for the disease mechanism summarized in an extensive database collecting mutant sequence location and residue substitution as independent variables that imply the dependent disease phenotype and pathogenicity characteristics in 4 dimensional data points (4ddps). The SNP database contains entries with the majority having one or both dependent data entries unfulfilled. A neural network relating causes (mutant residue location and substitution) and effects (phenotype and pathogenicity) is trained, validated, and optimized using fulfilled 4ddps. It then predicts unfulfilled 4ddps providing the implicit disease model. A discrete Bayes network interprets fulfilled and predicted 4ddps with conditional probabilities for phenotype and pathogenicity given mutation location and residue substitution thus relating the neural network implicit model to explicit features of the motor and mybpc3 sequence and structural domains. Neural/Bayes network forecasting automates disease mechanism modeling by leveraging the world wide human missense SNP database that is in place and expanding. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

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Jeban Ganesalingam

2009-09-01

Full Text Available Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001.The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

Delineating the GRIN1 phenotypic spectrum

DEFF Research Database (Denmark)

Lemke, Johannes R; Geider, Kirsten; Helbig, Katherine L

2016-01-01

consequences of GRIN1 mutations were investigated in Xenopus laevis oocytes. RESULTS: We identified heterozygous de novo GRIN1 mutations in 14 individuals and reviewed the phenotypes of all 9 previously reported patients. These 23 individuals presented with a distinct phenotype of profound developmental delay......, severe intellectual disability with absent speech, muscular hypotonia, hyperkinetic movement disorder, oculogyric crises, cortical blindness, generalized cerebral atrophy, and epilepsy. Mutations cluster within transmembrane segments and result in loss of channel function of varying severity...... impairment as well as oculomotor and movement disorders being discriminating phenotypic features. Loss of NMDA receptor function appears to be the underlying disease mechanism. The identification of both heterozygous and homozygous mutations blurs the borders of dominant and recessive inheritance of GRIN1...

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth.

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Zhang, Xuehai; Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Xiong, Lizhong; Yang, Wanneng; Yan, Jianbing

2017-03-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize ( Zea mays ) recombinant inbred line population ( n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. © 2017 American Society of Plant Biologists. All Rights Reserved.

A mesenchymal-like phenotype and expression of CD44 predict lack of apoptotic response to sorafenib in liver tumor cells.

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Fernando, Joan; Malfettone, Andrea; Cepeda, Edgar B; Vilarrasa-Blasi, Roser; Bertran, Esther; Raimondi, Giulia; Fabra, Àngels; Alvarez-Barrientos, Alberto; Fernández-Salguero, Pedro; Fernández-Rodríguez, Conrado M; Giannelli, Gianluigi; Sancho, Patricia; Fabregat, Isabel

2015-02-15

The multikinase inhibitor sorafenib is the only effective drug in advanced cases of hepatocellular carcinoma (HCC). However, response differs among patients and effectiveness only implies a delay. We have recently described that sorafenib sensitizes HCC cells to apoptosis. In this work, we have explored the response to this drug of six different liver tumor cell lines to define a phenotypic signature that may predict lack of response in HCC patients. Results have indicated that liver tumor cells that show a mesenchymal-like phenotype, resistance to the suppressor effects of transforming growth factor beta (TGF-β) and high expression of the stem cell marker CD44 were refractory to sorafenib-induced cell death in in vitro studies, which correlated with lack of response to sorafenib in nude mice xenograft models of human HCC. In contrast, epithelial-like cells expressing the stem-related proteins EpCAM or CD133 were sensitive to sorafenib-induced apoptosis both in vitro and in vivo. A cross-talk between the TGF-β pathway and the acquisition of a mesenchymal-like phenotype with up-regulation of CD44 expression was found in the HCC cell lines. Targeted CD44 knock-down in the mesenchymal-like cells indicated that CD44 plays an active role in protecting HCC cells from sorafenib-induced apoptosis. However, CD44 effect requires a TGF-β-induced mesenchymal background, since the only overexpression of CD44 in epithelial-like HCC cells is not sufficient to impair sorafenib-induced cell death. In conclusion, a mesenchymal profile and expression of CD44, linked to activation of the TGF-β pathway, may predict lack of response to sorafenib in HCC patients. © 2014 UICC.

Phenotypic plasticity as an adaptive response to predictable and unpredictable environmental changes

DEFF Research Database (Denmark)

Manenti, Tommaso

Phenotypic plasticity is the ability of a genotype to modify its phenotype in response to environmental changes as a consequence of an interaction between genes and environment (Bradshaw, 1965). Plasticity contributes to the vast phenotypic variation observed in natural populations. Many examples...... of a plastic response are expected to depend on the environmental conditions experienced by organisms. Thus, in populations exposed to a non-changing environment, the plastic machinery might be a waste of resources. Contrary, in populations experiencing varying environmental conditions, plasticity is expected...... such as anti-predator behaviours or the activation of mechanisms to prevent thermal stress injuries suggest that plasticity is an adaptive response, favoured by natural selection. At the same time, organisms do show limited plastic responses, indicating that this ability is not for free. Costs and benefits...

A genome-wide gene function prediction resource for Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Han Yan

2010-08-01

Full Text Available Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease*

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Dewhurst, Henry; Sundararaman, Niveda

2016-01-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Proteome-wide Structural Analysis of PTM Hotspots Reveals Regulatory Elements Predicted to Impact Biological Function and Disease.

Science.gov (United States)

Torres, Matthew P; Dewhurst, Henry; Sundararaman, Niveda

2016-11-01

Post-translational modifications (PTMs) regulate protein behavior through modulation of protein-protein interactions, enzymatic activity, and protein stability essential in the translation of genotype to phenotype in eukaryotes. Currently, less than 4% of all eukaryotic PTMs are reported to have biological function - a statistic that continues to decrease with an increasing rate of PTM detection. Previously, we developed SAPH-ire (Structural Analysis of PTM Hotspots) - a method for the prioritization of PTM function potential that has been used effectively to reveal novel PTM regulatory elements in discrete protein families (Dewhurst et al., 2015). Here, we apply SAPH-ire to the set of eukaryotic protein families containing experimental PTM and 3D structure data - capturing 1,325 protein families with 50,839 unique PTM sites organized into 31,747 modified alignment positions (MAPs), of which 2010 (∼6%) possess known biological function. Here, we show that using an artificial neural network model (SAPH-ire NN) trained to identify MAP hotspots with biological function results in prediction outcomes that far surpass the use of single hotspot features, including nearest neighbor PTM clustering methods. We find the greatest enhancement in prediction for positions with PTM counts of five or less, which represent 98% of all MAPs in the eukaryotic proteome and 90% of all MAPs found to have biological function. Analysis of the top 1092 MAP hotspots revealed 267 of truly unknown function (containing 5443 distinct PTMs). Of these, 165 hotspots could be mapped to human KEGG pathways for normal and/or disease physiology. Many high-ranking hotspots were also found to be disease-associated pathogenic sites of amino acid substitution despite the lack of observable PTM in the human protein family member. Taken together, these experiments demonstrate that the functional relevance of a PTM can be predicted very effectively by neural network models, revealing a large but testable

Higher-order predictions for splitting functions and coefficient functions from physical evolution kernels

International Nuclear Information System (INIS)

Vogt, A; Soar, G.; Vermaseren, J.A.M.

2010-01-01

We have studied the physical evolution kernels for nine non-singlet observables in deep-inelastic scattering (DIS), semi-inclusive e + e - annihilation and the Drell-Yan (DY) process, and for the flavour-singlet case of the photon- and heavy-top Higgs-exchange structure functions (F 2 , F φ ) in DIS. All known contributions to these kernels show an only single-logarithmic large-x enhancement at all powers of (1-x). Conjecturing that this behaviour persists to (all) higher orders, we have predicted the highest three (DY: two) double logarithms of the higher-order non-singlet coefficient functions and of the four-loop singlet splitting functions. The coefficient-function predictions can be written as exponentiations of 1/N-suppressed contributions in Mellin-N space which, however, are less predictive than the well-known exponentiation of the ln k N terms. (orig.)

Modulation of phenotypic and functional maturation of murine dendritic cells (DCs) by purified Achyranthes bidentata polysaccharide (ABP).

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Zou, Yaxuan; Meng, Jingjuan; Chen, Wenna; Liu, Jingling; Li, Xuan; Li, Weiwei; Lu, Changlong; Shan, Fengping

2011-08-01

There are a large number of interactions at molecular and cellular levels between the plant polysaccharides and immune system. Plant polysaccharides present an interesting effects as immunomodulators, particularly in the induction of the cells both in innate and adaptive immune systems. Activation of DCs could improve antitumoral responses usually diminished in cancer patients, and natural adjuvants provide a possibility of inducing this activation. ABP is a purified polysaccharide isolated from Achyranthes bidentata, a traditional Chinese medicine (TCM). The aim of this study is to investigate modulation of phenotypic and functional maturation of murine DCs by ABP. Both phenotypic and functional activities were assessed with use of conventional scanning electronic microscopy (SEM) for the morphology of the DC, transmitted electron microscopy (TEM) for intracellular lysosomes inside the DC, cellular immunohistochemistry for phagocytosis by the DCs, flow cytometry (FCM) for the changes in key surface molecules, bio-assay for the activity of acidic phosphatases (ACP), and ELISA for the production of pro-inflammatory cytokine IL-12. In fact, we found that purified ABP induced phenotypic maturation revealed by increased expression of CD86, CD40, and MHC II. Functional experiments showed the down-regulation of ACP inside DCs (which occurs when phagocytosis of DCs is decreased, and antigen presentation increased with maturation). Finally, ABP increased the production of IL-12. These data reveal that ABP promotes effective activation of murine DCs. This adjuvant-like activity may have therapeutic applications in clinical settings where immune responses need boosting. It is therefore concluded that ABP can exert positive modulation to murine DCs. Copyright © 2011 Elsevier B.V. All rights reserved.

Quantifying small molecule phenotypic effects using mitochondrial morpho-functional fingerprinting and machine learning

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Blanchet, Lionel; Smeitink, Jan A. M.; van Emst-de Vries, Sjenet E.; Vogels, Caroline; Pellegrini, Mina; Jonckheere, An I.; Rodenburg, Richard J. T.; Buydens, Lutgarde M. C.; Beyrath, Julien; Willems, Peter H. G. M.; Koopman, Werner J. H.

2015-01-01

In primary fibroblasts from Leigh Syndrome (LS) patients, isolated mitochondrial complex I deficiency is associated with increased reactive oxygen species levels and mitochondrial morpho-functional changes. Empirical evidence suggests these aberrations constitute linked therapeutic targets for small chemical molecules. However, the latter generally induce multiple subtle effects, meaning that in vitro potency analysis or single-parameter high-throughput cell screening are of limited use to identify these molecules. We combine automated image quantification and artificial intelligence to discriminate between primary fibroblasts of a healthy individual and a LS patient based upon their mitochondrial morpho-functional phenotype. We then evaluate the effects of newly developed Trolox variants in LS patient cells. This revealed that Trolox ornithylamide hydrochloride best counterbalanced mitochondrial morpho-functional aberrations, effectively scavenged ROS and increased the maximal activity of mitochondrial complexes I, IV and citrate synthase. Our results suggest that Trolox-derived antioxidants are promising candidates in therapy development for human mitochondrial disorders.

COPRED: prediction of fold, GO molecular function and functional residues at the domain level.

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López, Daniel; Pazos, Florencio

2013-07-15

Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked. COPRED can be freely accessed at http://csbg.cnb.csic.es/copred. The interface works in all standard web browsers. WebGL (natively supported by most browsers) is required for the in-line preview and manipulation of protein 3D structures. The website includes a detailed help section and usage examples. pazos@cnb.csic.es.

Worm Phenotype Ontology: Integrating phenotype data within and beyond the C. elegans community

Directory of Open Access Journals (Sweden)

Yook Karen

2011-01-01

Full Text Available Abstract Background Caenorhabditis elegans gene-based phenotype information dates back to the 1970's, beginning with Sydney Brenner and the characterization of behavioral and morphological mutant alleles via classical genetics in order to understand nervous system function. Since then C. elegans has become an important genetic model system for the study of basic biological and biomedical principles, largely through the use of phenotype analysis. Because of the growth of C. elegans as a genetically tractable model organism and the development of large-scale analyses, there has been a significant increase of phenotype data that needs to be managed and made accessible to the research community. To do so, a standardized vocabulary is necessary to integrate phenotype data from diverse sources, permit integration with other data types and render the data in a computable form. Results We describe a hierarchically structured, controlled vocabulary of terms that can be used to standardize phenotype descriptions in C. elegans, namely the Worm Phenotype Ontology (WPO. The WPO is currently comprised of 1,880 phenotype terms, 74% of which have been used in the annotation of phenotypes associated with greater than 18,000 C. elegans genes. The scope of the WPO is not exclusively limited to C. elegans biology, rather it is devised to also incorporate phenotypes observed in related nematode species. We have enriched the value of the WPO by integrating it with other ontologies, thereby increasing the accessibility of worm phenotypes to non-nematode biologists. We are actively developing the WPO to continue to fulfill the evolving needs of the scientific community and hope to engage researchers in this crucial endeavor. Conclusions We provide a phenotype ontology (WPO that will help to facilitate data retrieval, and cross-species comparisons within the nematode community. In the larger scientific community, the WPO will permit data integration, and

A preliminary candidate genotype-intermediate phenotype study of satiation and gastric motor function in obesity.

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Papathanasopoulos, Athanasios; Camilleri, Michael; Carlson, Paula J; Vella, Adrian; Nord, Sara J Linker; Burton, Duane D; Odunsi, Suwebatu T; Zinsmeister, Alan R

2010-06-01

Stomach motility contributes significantly to fullness sensation while eating and cessation of food intake in humans. Genes controlling adrenergic and serotonergic mechanisms (ADRA2A, GNB3, and SLC6A4) affect gastric emptying (GE), volume (GV), and satiation. Fat mass and obesity-associated gene (FTO) is linked with satiety. Our aim was to examine the association of these candidate genes with stomach functions that signal postprandial fullness: GE, GV, and maximum tolerated volume (MTV). These biomarkers constitute a component of the intermediate phenotype of satiation. A total of 62 overweight or obese participants underwent genotyping of the candidate genes, and validated measurements of GE of solids and liquids by scintigraphy, fasting and postprandial change in GV by SPECT (single photon emission computed tomography), and MTV by nutrient drink test. These markers of satiation were compared for 38 genetic variants in ADRA2A, ADR2C, ADRB3, uncoupling protein (UCP)-2 and -3, GNB3, FTO, and SLC6A4 using a recessive model of inheritance. ADRA2A, ADR2C, UCP-3, GNB3, and FTO loci were significantly associated with the intermediate phenotype markers of satiation: ADR2C (Ins-Del322_325) with accelerated GE; GNB3 (rs1047776) with delayed GE; ADRA2A (rs491589 and rs553668) and GNB3 (rs2269355, rs10849527, and rs3759348) with decreased postprandial GV; ADRA2A (rs3750625) and GNB3 (rs4963517 and rs1129649) with increased postprandial GV; UCP-3 (rs1685356) with increased MTV, and FTO (rs9939609) decreased MTV. Genetic susceptibility to postprandial satiation can be identified through intermediate phenotype markers. With independent validation, these markers may guide patient selection of weight-loss therapies directed at gastric motor functions.

QCD dipole predictions for DIS and diffractive structure functions

International Nuclear Information System (INIS)

Royon, C.

1997-01-01

The proton structure function F 2 , the gluon density F G , and the longitudinal structure function F L are derived in the QCD dipole picture of BFKL dynamics. We use a three parameter fit to describe the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed within the same framework, and a new prediction for the proton diffractive structure function is obtained

Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

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Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

2018-02-23

Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

Lung perfusion SPECT in predicting postoperative pulmonary function in lung cancer

International Nuclear Information System (INIS)

Hirose, Yoshiaki; Imaeda, Takeyoshi; Doi, Hidetaka; Kokubo, Mitsuharu; Sakai, Satoshi; Hirose, Hajime

1993-01-01

The aim of this prospective study is to evaluate the availability of preoperative perfusion SPECT in predicting postoperative pulmonary function following resection. Twenty-three patients with lung cancer who were candidates for lobectomy were investigated preoperatively with spirometry, x-ray computed tomography and 99m Tc-macroaggregated albumin SPECT. Their postoperative pulmonary functions were predicted with these examinations. The forced vital capacity and the forced expiratory volume in one second were selected as parameters for overall pulmonary function. The postoperative pulmonary function was predicted by the following formula: Predicted postoperative value=observed preoperative value x precent perfusion of the lung not to be resected. The patients were reinvestigated with spirometry at 3 months and 6 months after lobectomy, and the values obtained were statistically compared with the predicted values. Close relationships were found between predicted and observed forced vital capacity (r=0.87, p<0.001), and predicted and observed forced expiratory volume in one second (r=0.90, p<0.001). The accurate prediction of pulmonary function after lobectomy could be achieved by means of lung perfusion SPECT. (author)

QCD dipole prediction for dis and diffractive structure functions

International Nuclear Information System (INIS)

Royon, CH.

1996-01-01

The F 2 , F G , R = F L /F T proton structure functions are derived in the QCD dipole picture of BFKL dynamics. We get a three parameter fit describing the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed, and a new prediction for the proton diffractive structure function is obtained. (author)

Fat oxidation at rest predicts peak fat oxidation during exercise and metabolic phenotype in overweight men

DEFF Research Database (Denmark)

Rosenkilde, M; Nordby, P; Nielsen, L B

2010-01-01

OBJECTIVE: To elucidate if fat oxidation at rest predicts peak fat oxidation during exercise and/or metabolic phenotype in moderately overweight, sedentary men. DESIGN: Cross-sectional study.Subjects:We measured respiratory exchange ratio (RER) at rest in 44 moderately overweight, normotensive...... the International Diabetes Federation criteria, we found that there was a lower accumulation of metabolic risk factors in L-RER than in H-RER (1.6 vs 3.5, P=0.028), and no subjects in L-RER and four of eight subjects in H-RER had the metabolic syndrome. Resting RER was positively correlated with plasma...... triglycerides (Pexercise was positively correlated with plasma free fatty acid concentration at rest (Pexercise and a healthy metabolic...

Delineation of C12orf65-related phenotypes: a genotype-phenotype relationship.

Science.gov (United States)

Spiegel, Ronen; Mandel, Hanna; Saada, Ann; Lerer, Issy; Burger, Ayala; Shaag, Avraham; Shalev, Stavit A; Jabaly-Habib, Haneen; Goldsher, Dorit; Gomori, John M; Lossos, Alex; Elpeleg, Orly; Meiner, Vardiella

2014-08-01

C12orf65 participates in the process of mitochondrial translation and has been shown to be associated with a spectrum of phenotypes, including early onset optic atrophy, progressive encephalomyopathy, peripheral neuropathy, and spastic paraparesis.We used whole-genome homozygosity mapping as well as exome sequencing and targeted gene sequencing to identify novel C12orf65 disease-causing mutations in seven affected individuals originating from two consanguineous families. In four family members affected with childhood-onset optic atrophy accompanied by slowly progressive peripheral neuropathy and spastic paraparesis, we identified a homozygous frame shift mutation c.413_417 delAACAA, which predicts a truncated protein lacking the C-terminal portion. In the second family, we studied three affected individuals who presented with early onset optic atrophy, peripheral neuropathy, and spastic gait in addition to moderate intellectual disability. Muscle biopsy in two of the patients revealed decreased activities of the mitochondrial respiratory chain complexes I and IV. In these patients, we identified a homozygous splice mutation, g.21043 T>A (c.282+2 T>A) which leads to skipping of exon 2. Our study broadens the phenotypic spectrum of C12orf65 defects and highlights the triad of optic atrophy, axonal neuropathy and spastic paraparesis as its key clinical features. In addition, a clear genotype-phenotype correlation is anticipated in which deleterious mutations which disrupt the GGQ-containing domain in the first coding exon are expected to result in a more severe phenotype, whereas down-stream C-terminal mutations may result in a more favorable phenotype, typically lacking cognitive impairment.

Genotype-phenotype associations in obesity dependent on definition of the obesity phenotype.

Science.gov (United States)

Kring, Sofia Inez Iqbal; Larsen, Lesli Hingstrup; Holst, Claus; Toubro, Søren; Hansen, Torben; Astrup, Arne; Pedersen, Oluf; Sørensen, Thorkild I A

2008-01-01

In previous studies of associations of variants in the genes UCP2, UCP3, PPARG2, CART, GRL, MC4R, MKKS, SHP, GHRL, and MCHR1 with obesity, we have used a case-control approach with cases defined by a threshold for BMI. In the present study, we assess the association of seven abdominal, peripheral, and overall obesity phenotypes, which were analyzed quantitatively, and thirteen candidate gene polymorphisms in these ten genes in the same cohort. Obese Caucasian men (n = 234, BMI >or= 31.0 kg/m(2)) and a randomly sampled non-obese group (n = 323), originally identified at the draft board examinations, were re-examined at median ages of 47.0 or 49.0 years by anthropometry and DEXA scanning. Obesity phenotypes included BMI, fat body mass index, waist circumference, waist for given BMI, intra-abdominal adipose tissue, hip circumference and lower body fat mass (%). Using logistic regression models, we estimated the odds for defined genotypes (dominant or recessive genetic transmission) in relation to z-scores of the phenotypes. The minor (rare) allele for SHP 512G>C (rs6659176) was associated with increased hip circumference. The minor allele for UCP2 Ins45bp was associated with increased BMI, increased abdominal obesity, and increased hip circumference. The minor allele for UCP2 -866G>A (rs6593669) was associated with borderline increased fat body mass index. The minor allele for MCHR1 100213G>A (rs133072) was associated with reduced abdominal obesity. None of the other genotype-phenotype combinations showed appreciable associations. If replicated in independent studies with focus on the specific phenotypes, our explorative studies suggest significant associations between some candidate gene polymorphisms and distinct obesity phenotypes, predicting beneficial and detrimental effects, depending on compartments for body fat accumulation. Copyright 2008 S. Karger AG, Basel.

Predicting rates of interspecific interaction from phylogenetic trees.

Science.gov (United States)

Nuismer, Scott L; Harmon, Luke J

2015-01-01

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction. © 2014 John Wiley & Sons Ltd/CNRS.

Scoring function to predict solubility mutagenesis

Directory of Open Access Journals (Sweden)

Deutsch Christopher

2010-10-01

Full Text Available Abstract Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM and the Lasso. Using statistics for leave-one-out (LOO, 10-fold, and 3-fold cross validations (CV for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

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Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Phenotypic and functional analysis of CD1a+ dendritic cells from cats chronically infected with feline immunodeficiency virus.

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Zhang, Lin; Reckling, Stacie; Dean, Gregg A

2015-10-01

Numerous studies suggest dendritic cell (DC) dysfunction is central to the dysregulated immune response during HIV infection; however, in vivo studies are lacking. In the present study we used feline immunodeficiency virus (FIV) infection of cats as a model for HIV-1 infection to assess the maturation and function of dendritic cells, in vivo and in vitro. We compared CD1a+ DC migration, surface phenotype, endocytosis, mixed leukocyte reaction (MLR) and regulatory T cell (Treg) phenotype induction by CD1a+ cells isolated from lymph nodes of FIV-infected and control cats. Results showed that resident CD1a+ DC in lymph nodes of chronically FIV-infected cats are phenotypically mature, can stimulate normal primary T cell proliferation, override Treg suppression and do not skew toward Treg induction. In contrast, FIV infection had deleterious effects on antigen presentation and migratory capacity of CD1a+ cells in tissues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Novel effector phenotype of Tim-3+ regulatory T cells leads to enhanced suppressive function in head and neck cancer patients.

Science.gov (United States)

Liu, Zhuqing; McMichael, Elizabeth L; Shayan, Gulidanna; Li, Jing; Chen, Kevin; Srivastava, Raghvendra M; Kane, Lawrence P; Lu, Binfeng; Ferris, Robert L

2018-04-30

Regulatory T (Treg) cells are important suppressive cells among tumor infiltrating lymphocytes (TIL). Treg express the well-known immune checkpoint receptor PD-1, which is reported to mark "exhausted" Treg with lower suppressive function. T cell immunoglobulin mucin (Tim)-3, a negative regulator of Th1 immunity, is expressed by a sizeable fraction of TIL Tregs, but the functional status of Tim-3+ Tregs remains unclear. CD4+CTLA-4+CD25high Treg were sorted from freshly excised head and neck squamous cell carcinoma (HNSCC) TIL based on Tim-3 expression. Functional and phenotypic features of these Tim-3+ and Tim-3- TIL Tregs were tested by in vitro suppression assays and multi-color flow cytometry. Gene expression profiling and NanoString analysis of Tim-3+ TIL Treg were performed. A murine HNSCC tumor model was used to test the effect of anti-PD-1 immunotherapy on Tim-3+ Treg.  Results: Despite high PD-1 expression, Tim-3+ TIL Treg displayed a greater capacity to inhibit naïve T cell proliferation than Tim-3- Treg. Tim-3+ Treg from human HNSCC TIL also displayed an effector-like phenotype, with more robust expression of CTLA-4, PD-1, CD39 and IFN-γ receptor. Exogenous IFN-γ treatment could partially reverse the suppressive function of Tim-3+ TIL Treg. Anti-PD-1 immunotherapy downregulated Tim-3 expression on Tregs isolated from murine HNSCC tumors, and this treatment reversed the suppressive function of HNSCC TIL Tregs. Tim-3+ Treg are functionally and phenotypically distinct in HNSCC TIL, and are highly effective at inhibiting T cell proliferation despite high PD-1 expression.  IFN-γ induced by anti-PD-1 immunotherapy may be beneficial by reversing Tim-3+ Treg suppression. Copyright ©2018, American Association for Cancer Research.

Predictability of Genetic Interactions from Functional Gene Modules

Directory of Open Access Journals (Sweden)

Jonathan H. Young

2017-02-01

Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

Predicting Hydrologic Function With Aquatic Gene Fragments

Science.gov (United States)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

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Kristiansson Erik

2009-12-01

Full Text Available Abstract Background Some upstream open reading frames (uORFs regulate gene expression (i.e., they are functional and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not yet fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of experimentally verified functional uORFs are needed. Unfortunately, wet-experiments to verify that uORFs are functional are expensive. Results In this paper, a new computational approach to predicting functional uORFs in the yeast Saccharomyces cerevisiae is presented. Our approach is based on inductive logic programming and makes use of a novel combination of knowledge about biological conservation, Gene Ontology annotations and genes' responses to different conditions. Our method results in a set of simple and informative hypotheses with an estimated sensitivity of 76%. The hypotheses predict 301 further genes to have 398 novel functional uORFs. Three (RPC11, TPK1, and FOL1 of these 301 genes have been hypothesised, following wet-experiments, by a related study to have functional uORFs. A comparison with another related study suggests that eleven of the predicted functional uORFs from genes LDB17, HEM3, CIN8, BCK2, PMC1, FAS1, APP1, ACC1, CKA2, SUR1, and ATH1 are strong candidates for wet-lab experimental studies. Conclusions Learning based prediction of functional uORFs can be done with a high sensitivity. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help to elucidate the regulatory roles of uORFs.

The genotype-phenotype map of an evolving digital organism.

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Miguel A Fortuna

2017-02-01

Full Text Available To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences, which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism.

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Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

Improving protein function prediction methods with integrated literature data

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Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Prediction of Chemical Function: Model Development and ...

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The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Longitudinal Patterns of Glycemic Control and Blood Pressure in Pregnant Women with Type 1 Diabetes Mellitus: Phenotypes from Functional Data Analysis.

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Szczesniak, Rhonda D; Li, Dan; Duan, Leo L; Altaye, Mekibib; Miodovnik, Menachem; Khoury, Jane C

2016-11-01

Objective  To identify phenotypes of type 1 diabetes control and associations with maternal/neonatal characteristics based on blood pressure (BP), glucose, and insulin curves during gestation, using a novel functional data analysis approach that accounts for sparse longitudinal patterns of medical monitoring during pregnancy. Methods  We performed a retrospective longitudinal cohort study of women with type 1 diabetes whose BP, glucose, and insulin requirements were monitored throughout gestation as part of a program-project grant. Scores from sparse functional principal component analysis (fPCA) were used to classify gestational profiles according to the degree of control for each monitored measure. Phenotypes created using fPCA were compared with respect to maternal and neonatal characteristics and outcome. Results  Most of the gestational profile variation in the monitored measures was explained by the first principal component (82-94%). Profiles clustered into three subgroups of high, moderate, or low heterogeneity, relative to the overall mean response. Phenotypes were associated with baseline characteristics, longitudinal changes in glycohemoglobin A1 and weight, and to pregnancy-related outcomes. Conclusion  Three distinct longitudinal patterns of glucose, insulin, and BP control were found. By identifying these phenotypes, interventions can be targeted for subgroups at highest risk for compromised outcome, to optimize diabetes management during pregnancy. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

The list of strains and growth conditions - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us The Rice Growth Monitoring for The Phenotypic Functional Analysis The list of strains and growth... conditions Data detail Data name The list of strains and growth conditions DOI 10.18908/lsdba.nbdc00945...-001 Description of data contents The list of strains and growth conditions for respective samples. Data fil...servation Intervals of imaging Intervals of imaging Growth data Graph of chronological changes in growth Ima...History of This Database Site Policy | Contact Us The list of strains and growth conditions - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive ...

De novo loss- or gain-of-function mutations in KCNA2 cause epileptic encephalopathy

DEFF Research Database (Denmark)

Syrbe, Steffen; Hedrich, Ulrike B S; Riesch, Erik

2015-01-01

disability, delayed speech development and sometimes ataxia. Functional studies of the two mutations associated with this phenotype showed almost complete loss of function with a dominant-negative effect. Two further individuals presented with a different and more severe epileptic encephalopathy phenotype....... They carried mutations inducing a drastic gain-of-function effect leading to permanently open channels. These results establish KCNA2 as a new gene involved in human neurodevelopmental disorders through two different mechanisms, predicting either hyperexcitability or electrical silencing of KV1.2-expressing...

Prediction of phenotypes of missense mutations in human proteins from biological assemblies.

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Wei, Qiong; Xu, Qifang; Dunbrack, Roland L

2013-02-01

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence-based and structure-based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure-based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X-ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease-associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e-5). When adding this information to sequence-based features such as the difference between wildtype and mutant position-specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence-based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease-associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Copyright © 2012 Wiley Periodicals, Inc.

Predicting gene function using hierarchical multi-label decision tree ensembles

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Kocev Dragi

2010-01-01

Full Text Available Abstract Background S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability. Results We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO. We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use. Conclusions Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.

High-Throughput Phenotyping and QTL Mapping Reveals the Genetic Architecture of Maize Plant Growth1[OPEN

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Huang, Chenglong; Wu, Di; Qiao, Feng; Li, Wenqiang; Duan, Lingfeng; Wang, Ke; Xiao, Yingjie; Chen, Guoxing; Liu, Qian; Yang, Wanneng

2017-01-01

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923

Executive function processes predict mobility outcomes in older adults.

Science.gov (United States)

Gothe, Neha P; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R; Olson, Erin A; Mullen, Sean P; Voss, Michelle; Erickson, Kirk I; Kramer, Arthur F; McAuley, Edward

2014-02-01

To examine the relationship between performance on executive function measures and subsequent mobility outcomes in community-dwelling older adults. Randomized controlled clinical trial. Champaign-Urbana, Illinois. Community-dwelling older adults (N = 179; mean age 66.4). A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group. Established cognitive tests of executive function (flanker task, task switching, and a dual-task paradigm) and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. Participants completed the cognitive tests at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted postintervention functional performance after controlling for age, sex, education, cardiorespiratory fitness, and baseline mobility levels. Selective baseline executive function measurements, particularly performance on the flanker task (β = 0.15-0.17) and the Wisconsin card sort test (β = 0.11-0.16) consistently predicted mobility outcomes at 12 months. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of intervention. Executive functions of inhibitory control, mental set shifting, and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality, these results are important for understanding the antecedents to poor mobility function that well-designed interventions to improve cognitive performance can attenuate. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

The evolution of human phenotypic plasticity: age and nutritional status at maturity.

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Gage, Timothy B

2003-08-01

Several evolutionary optimal models of human plasticity in age and nutritional status at reproductive maturation are proposed and their dynamics examined. These models differ from previously published models because fertility is not assumed to be a function of body size or nutritional status. Further, the models are based on explicitly human demographic patterns, that is, model human life-tables, model human fertility tables, and, a nutrient flow-based model of maternal nutritional status. Infant survival (instead of fertility as in previous models) is assumed to be a function of maternal nutritional status. Two basic models are examined. In the first the cost of reproduction is assumed to be a constant proportion of total nutrient flow. In the second the cost of reproduction is constant for each birth. The constant proportion model predicts a negative slope of age and nutritional status at maturation. The constant cost per birth model predicts a positive slope of age and nutritional status at maturation. Either model can account for the secular decline in menarche observed over the last several centuries in Europe. A search of the growth literature failed to find definitive empirical documentation of human phenotypic plasticity in age and nutritional status at maturation. Most research strategies confound genetics with phenotypic plasticity. The one study that reports secular trends suggests a marginally insignificant, but positive slope. This view tends to support the constant cost per birth model.

Retinal function in patients with the neuronal ceroid lipofuscinosis phenotype

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Elizabeth Maria Aparecida Barasnevicius Quagliato

Full Text Available ABSTRACT Purpose: To analyze the clinical features, visual acuity, and full-field electroretinogram (ERG findings of 15 patients with the neuronal ceroid lipofuscinosis (NCL phenotype and to establish the role of ERG testing in NCL diagnosis. Methods: The medical records of five patients with infantile NCL, five with Jansky-Bielschowsky disease, and five with juvenile NCL who underwent full-field ERG testing were retrospectively analyzed. Results: Progressive vision loss was the initial symptom in 66.7% of patients and was isolated or associated with ataxia, epilepsy, and neurodevelopmental involution. Epilepsy was present in 93.3% of patients, of whom 86.6% presented with neurodevelopmental involution. Fundus findings ranged from normal to pigmentary/atrophic abnormalities. Cone-rod, rod-cone, and both types of dysfunction were observed in six, one, and eight patients, respectively. Conclusion: In our study, all patients with the NCL phenotype had abnormal ERG findings, and the majority exhibited both cone-rod and rod-cone dysfunction. We conclude that ERG is a valuable tool for the characterization of visual dysfunction in patients with the NCL phenotype and is useful for diagnosis.

Lipid-laden cells differentially distributed in the aging brain are functionally active and correspond to distinct phenotypes

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Shimabukuro, Marilia Kimie; Langhi, Larissa Gutman Paranhos; Cordeiro, Ingrid; Brito, José M.; Batista, Claudia Maria de Castro; Mattson, Mark P.; de Mello Coelho, Valeria

2016-01-01

We characterized cerebral Oil Red O-positive lipid-laden cells (LLC) of aging mice evaluating their distribution, morphology, density, functional activities and inflammatory phenotype. We identified LLC in meningeal, cortical and neurogenic brain regions. The density of cerebral LLC increased with age. LLC presenting small lipid droplets were visualized adjacent to blood vessels or deeper in the brain cortical and striatal parenchyma of aging mice. LLC with larger droplets were asymmetrically distributed in the cerebral ventricle walls, mainly located in the lateral wall. We also found that LLC in the subventricular region co-expressed beclin-1 or LC3, markers for autophagosome or autophagolysosome formation, and perilipin (PLIN), a lipid droplet-associated protein, suggesting lipophagic activity. Some cerebral LLC exhibited β galactosidase activity indicating a senescence phenotype. Moreover, we detected production of the pro-inflammatory cytokine TNF-α in cortical PLIN+ LLC. Some cortical NeuN+ neurons, GFAP+ glia limitans astrocytes, Iba-1+ microglia and S100β+ ependymal cells expressed PLIN in the aging brain. Our findings suggest that cerebral LLC exhibit distinct cellular phenotypes and may participate in the age-associated neuroinflammatory processes. PMID:27029648

Lipid-laden cells differentially distributed in the aging brain are functionally active and correspond to distinct phenotypes.

Science.gov (United States)

Shimabukuro, Marilia Kimie; Langhi, Larissa Gutman Paranhos; Cordeiro, Ingrid; Brito, José M; Batista, Claudia Maria de Castro; Mattson, Mark P; Mello Coelho, Valeria de

2016-03-31

We characterized cerebral Oil Red O-positive lipid-laden cells (LLC) of aging mice evaluating their distribution, morphology, density, functional activities and inflammatory phenotype. We identified LLC in meningeal, cortical and neurogenic brain regions. The density of cerebral LLC increased with age. LLC presenting small lipid droplets were visualized adjacent to blood vessels or deeper in the brain cortical and striatal parenchyma of aging mice. LLC with larger droplets were asymmetrically distributed in the cerebral ventricle walls, mainly located in the lateral wall. We also found that LLC in the subventricular region co-expressed beclin-1 or LC3, markers for autophagosome or autophagolysosome formation, and perilipin (PLIN), a lipid droplet-associated protein, suggesting lipophagic activity. Some cerebral LLC exhibited β galactosidase activity indicating a senescence phenotype. Moreover, we detected production of the pro-inflammatory cytokine TNF-α in cortical PLIN(+) LLC. Some cortical NeuN(+) neurons, GFAP(+) glia limitans astrocytes, Iba-1(+) microglia and S100β(+) ependymal cells expressed PLIN in the aging brain. Our findings suggest that cerebral LLC exhibit distinct cellular phenotypes and may participate in the age-associated neuroinflammatory processes.

MECP2 variation in Rett syndrome-An overview of current coverage of genetic and phenotype data within existing databases.

Science.gov (United States)

Townend, Gillian S; Ehrhart, Friederike; van Kranen, Henk J; Wilkinson, Mark; Jacobsen, Annika; Roos, Marco; Willighagen, Egon L; van Enckevort, David; Evelo, Chris T; Curfs, Leopold M G

2018-04-27

Rett syndrome (RTT) is a monogenic rare disorder that causes severe neurological problems. In most cases, it results from a loss-of-function mutation in the gene encoding methyl-CPG-binding protein 2 (MECP2). Currently, about 900 unique MECP2 variations (benign and pathogenic) have been identified and it is suspected that the different mutations contribute to different levels of disease severity. For researchers and clinicians, it is important that genotype-phenotype information is available to identify disease-causing mutations for diagnosis, to aid in clinical management of the disorder, and to provide counseling for parents. In this study, 13 genotype-phenotype databases were surveyed for their general functionality and availability of RTT-specific MECP2 variation data. For each database, we investigated findability and interoperability alongside practical user functionality, and type and amount of genetic and phenotype data. The main conclusions are that, as well as being challenging to find these databases and specific MECP2 variants held within, interoperability is as yet poorly developed and requires effort to search across databases. Nevertheless, we found several thousand online database entries for MECP2 variations and their associated phenotypes, diagnosis, or predicted variant effects, which is a good starting point for researchers and clinicians who want to provide, annotate, and use the data. © 2018 The Authors. Human Mutation published by Wiley Periodicals, Inc.

Linear Prediction Using Refined Autocorrelation Function

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M. Shahidur Rahman

2007-07-01

Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

Predictive model for functional consequences of oral cavity tumour resections

NARCIS (Netherlands)

van Alphen, M.J.A.; Hageman, T.A.G.; Hageman, Tijmen Antoon Geert; Smeele, L.E.; Balm, Alfonsus Jacobus Maria; Balm, A.J.M.; van der Heijden, Ferdinand; Lemke, H.U.

2013-01-01

The prediction of functional consequences after treatment of large oral cavity tumours is mainly based on the size and location of the tumour. However, patient specific factors play an important role in the functional outcome, making the current predictions unreliable and subjective. An objective

Comparative Analyses of Phenotypic Trait Covariation within and among Populations.

Science.gov (United States)

Peiman, Kathryn S; Robinson, Beren W

2017-10-01

Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.

Mapping the functional landscape of frequent phenylalanine hydroxylase (PAH) genotypes promotes personalised medicine in phenylketonuria.

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Danecka, Marta K; Woidy, Mathias; Zschocke, Johannes; Feillet, François; Muntau, Ania C; Gersting, Søren W

2015-03-01

In phenylketonuria, genetic heterogeneity, frequent compound heterozygosity, and the lack of functional data for phenylalanine hydroxylase genotypes hamper reliable phenotype prediction and individualised treatment. A literature search revealed 690 different phenylalanine hydroxylase genotypes in 3066 phenylketonuria patients from Europe and the Middle East. We determined phenylalanine hydroxylase function of 30 frequent homozygous and compound heterozygous genotypes covering 55% of the study population, generated activity landscapes, and assessed the phenylalanine hydroxylase working range in the metabolic (phenylalanine) and therapeutic (tetrahydrobiopterin) space. Shared patterns in genotype-specific functional landscapes were linked to biochemical and pharmacological phenotypes, where (1) residual activity below 3.5% was associated with classical phenylketonuria unresponsive to pharmacological treatment; (2) lack of defined peak activity induced loss of response to tetrahydrobiopterin; (3) a higher cofactor need was linked to inconsistent clinical phenotypes and low rates of tetrahydrobiopterin response; and (4) residual activity above 5%, a defined peak of activity, and a normal cofactor need were associated with pharmacologically treatable mild phenotypes. In addition, we provide a web application for retrieving country-specific information on genotypes and genotype-specific phenylalanine hydroxylase function that warrants continuous extension, updates, and research on demand. The combination of genotype-specific functional analyses with biochemical, clinical, and therapeutic data of individual patients may serve as a powerful tool to enable phenotype prediction and to establish personalised medicine strategies for dietary regimens and pharmacological treatment in phenylketonuria. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predicting estuarine benthic production using functional diversity

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Marina Dolbeth

2014-05-01

Full Text Available We considered an estuarine system having naturally low levels of diversity, but attaining considerable high production levels, and being subjected to different sorts of anthropogenic impacts and climate events to investigate the relationship between diversity and secondary production. Functional diversity measures were used to predict benthic production, which is considered as a proxy of the ecosystem provisioning services. To this end, we used a 14-year dataset on benthic invertebrate community production from a seagrass and a sandflat habitat and we adopted a sequential modeling approach, where abiotic, trait community weighted means (CWM and functional diversity indices were tested by generalized linear models (GLM, and their significant variables were then combined to produce a final model. Almost 90% of variance of the benthic production could be predicted by combining the number of locomotion types, the absolute maximum atmospheric temperature (proxy of the heat waves occurrence, the type of habitat and the mean body mass, by order of importance. This result is in agreement with the mass ratio hypothesis, where ecosystem functions/services can be chiefly predicted by the dominant trait in the community, here measured as CWM. The increase of benthic production with the number of locomotion types may be seen as greater possibility of using the resources available in the system. Such greater efficiency would increase production. The other variables were also discussed in line of the previous hypothesis and taking into account the general positive relationship obtained between production and functional diversity indices. Overall, it was concluded that traits representative of wider possibilities of using available resources and higher functional diversity are related with higher benthic production.

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

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Kihara Daisuke

2010-05-01

Full Text Available Abstract Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria. The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP

Dissecting phenotypic variation among AIS patients

International Nuclear Information System (INIS)

Wang Minghua; Wang Jiucun; Zhang Zhen; Zhao Zhimin; Zhang Rongmei; Hu Xiaohua; Tan Tao; Luo Shijing; Luo Zewei

2005-01-01

We have created genital skin fibroblast cell lines directly from three patients in a Chinese family affected by androgen insensitivity syndrome (AIS). All patients in the family share an identical AR Arg 840 Cys mutant but show different disease phenotypes. By using the cell lines, we find that the mutation has not influenced a normal androgen-binding capacity at 37 deg C but has reduced the affinity for androgens and may cause thermolability of the androgen-receptor complex. The impaired nuclear trafficking of the androgen receptor in the cell lines is highly correlated with the severity of donors' disease phenotype. The transactivity of the mutant is substantially weakened and the extent of the reduced transactivity reflects severity of the donors' disease symptom. Our data reveal that although etiology of AIS is monogenic and the mutant may alter the major biological functions of its wild allele, the function of the mutant AR can also be influenced by the different genetic backgrounds and thus explains the divergent disease phenotypes

Phenotype modulation of airway smooth muscle in asthma

NARCIS (Netherlands)

Wright, David B.; Trian, Thomas; Siddiqui, Sana; Pascoe, Chris D.; Johnson, Jill R.; Dekkers, Bart G. J.; Dakshinamurti, Shyamala; Bagchi, Rushita; Burgess, Janette K.; Kanabar, Varsha; Ojo, Oluwaseun O.

The biological responses of airway smooth muscle (ASM) are diverse, in part due to ASM phenotype plasticity. ASM phenotype plasticity refers to the ability of ASM cells to change the degree of a variety of functions, including contractility, proliferation, migration and secretion of inflammatory

Ethnicity/culture modulates the relationships of the haptoglobin (Hp) 1-1 phenotype with cognitive function in older individuals with type 2 diabetes.

Science.gov (United States)

Guerrero-Berroa, Elizabeth; Ravona-Springer, Ramit; Heymann, Anthony; Schmeidler, James; Hoffman, Hadas; Preiss, Rachel; Koifmann, Keren; Greenbaum, Lior; Levy, Andrew; Silverman, Jeremy M; Leroith, Derek; Sano, Mary; Schnaider-Beeri, Michal

2016-05-01

The haptoglobin (Hp) genotype has been associated with cognitive function in type 2 diabetes. Because ethnicity/culture has been associated with both cognitive function and Hp genotype frequencies, we examined whether it modulates the association of Hp with cognitive function. This cross-sectional study evaluated 787 cognitively normal older individuals (>65 years of age) with type 2 diabetes participating in the Israel Diabetes and Cognitive Decline study. Interactions in two-way analyses of covariance compared Group (Non-Ashkenazi versus Ashkenazi Jews) on the associations of Hp phenotype (Hp 1-1 versus non- Hp 1-1) with five cognitive outcome measures. The primary control variables were age, gender, and education. Compared with Ashkenazi Jews, non-Ashkenazi Jews with the Hp 1-1 phenotype had significantly poorer cognitive function than non-Hp 1-1 in the domains of Attention/Working Memory (p = 0.035) and Executive Function (p = 0.023), but not in Language/Semantic Categorization (p = 0.432), Episodic Memory (p = 0.268), or Overall Cognition (p = 0.082). After controlling for additional covariates (type 2 diabetes-related characteristics, cardiovascular risk factors, Mini-mental State Examination, and extent of depressive symptoms), Attention/Working Memory (p = 0.038) and Executive Function (p = 0.013) remained significant. Older individuals from specific ethnic/cultural backgrounds with the Hp 1-1 phenotype may benefit more from treatment targeted at decreasing or halting the detrimental effects of Hp 1-1 on the brain. Future studies should examine differential associations of Hp 1-1 and cognitive impairment, especially for groups with high prevalence of both, such as African-Americans and Hispanics. Copyright © 2015 John Wiley & Sons, Ltd.

Phenotypic, ultra-structural, and functional characterization of bovine peripheral blood dendritic cell subsets.

Directory of Open Access Journals (Sweden)

Janet J Sei

Full Text Available Dendritic cells (DC are multi-functional cells that bridge the gap between innate and adaptive immune systems. In bovine, significant information is lacking on the precise identity and role of peripheral blood DC subsets. In this study, we identify and characterize bovine peripheral blood DC subsets directly ex vivo, without further in vitro manipulation. Multi-color flow cytometric analysis revealed that three DC subsets could be identified. Bovine plasmacytoid DC were phenotypically identified by a unique pattern of cell surface protein expression including CD4, exhibited an extensive endoplasmic reticulum and Golgi apparatus, efficiently internalized and degraded exogenous antigen, and were the only peripheral blood cells specialized in the production of type I IFN following activation with Toll-like receptor (TLR agonists. Conventional DC were identified by expression of a different pattern of cell surface proteins including CD11c, MHC class II, and CD80, among others, the display of extensive dendritic protrusions on their plasma membrane, expression of very high levels of MHC class II and co-stimulatory molecules, efficient internalization and degradation of exogenous antigen, and ready production of detectable levels of TNF-alpha in response to TLR activation. Our investigations also revealed a third novel DC subset that may be a precursor of conventional DC that were MHC class II+ and CD11c-. These cells exhibited a smooth plasma membrane with a rounded nucleus, produced TNF-alpha in response to TLR-activation (albeit lower than CD11c+ DC, and were the least efficient in internalization/degradation of exogenous antigen. These studies define three bovine blood DC subsets with distinct phenotypic and functional characteristics which can be analyzed during immune responses to pathogens and vaccinations of cattle.

Allelic Frequencies of 20 Visible Phenotype Variants in the Korean Population

Directory of Open Access Journals (Sweden)

Ji Eun Lim

2013-06-01

Full Text Available The prediction of externally visible characteristics from DNA has been studied for forensic genetics over the last few years. Externally visible characteristics include hair, skin, and eye color, height, and facial morphology, which have high heritability. Recent studies using genome-wide association analysis have identified genes and variations that correlate with human visible phenotypes and developed phenotype prediction programs. However, most prediction models were constructed and validated based on genotype and phenotype information on Europeans. Therefore, we need to validate prediction models in diverse ethnic populations. In this study, we selected potentially useful variations for forensic science that are associated with hair and eye color, iris pattern, and facial morphology, based on previous studies, and analyzed their frequencies in 1,920 Koreans. Among 20 single nucleotide polymorphisms (SNPs, 10 SNPs were polymorphic, 6 SNPs were very rare (minor allele frequency < 0.005, and 4 SNPs were monomorphic in the Korean population. Even though the usability of these SNPs should be verified by an association study in Koreans, this study provides 10 potential SNP markers for forensic science for externally visible characteristics in the Korean population.

Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: insulin/TOR and associated phenotypes in Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Harshman Lawrence G

2009-03-01

Full Text Available Abstract Background A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

Scoring protein relationships in functional interaction networks predicted from sequence data.

Directory of Open Access Journals (Sweden)

Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Phenotypic characterization of glioblastoma identified through shape descriptors

Science.gov (United States)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

Combining specificity determining and conserved residues improves functional site prediction

Directory of Open Access Journals (Sweden)

Gelfand Mikhail S

2009-06-01

Full Text Available Abstract Background Predicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core. Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities. Results Here we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs, as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples. Conclusion The results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

Chemical Function Predictions for Tox21 Chemicals

Data.gov (United States)

U.S. Environmental Protection Agency — Random forest chemical function predictions for Tox21 chemicals in personal care products uses and "other" uses. This dataset is associated with the following...

QCD predictions for weak neutral current structure functions

International Nuclear Information System (INIS)

Wu Jimin

1987-01-01

Employing the analytic expression (to the next leading order) for non-singlet component of structure function which the author got from QCD theory and putting recent experiment result of neutral current structure function at Q 2 = 11 (GeV/C) 2 as input, the QCD prediction for neutral current structure function of their scaling violation behaviours was given

The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data

Science.gov (United States)

Koscielny, Gautier; Yaikhom, Gagarine; Iyer, Vivek; Meehan, Terrence F.; Morgan, Hugh; Atienza-Herrero, Julian; Blake, Andrew; Chen, Chao-Kung; Easty, Richard; Di Fenza, Armida; Fiegel, Tanja; Grifiths, Mark; Horne, Alan; Karp, Natasha A.; Kurbatova, Natalja; Mason, Jeremy C.; Matthews, Peter; Oakley, Darren J.; Qazi, Asfand; Regnart, Jack; Retha, Ahmad; Santos, Luis A.; Sneddon, Duncan J.; Warren, Jonathan; Westerberg, Henrik; Wilson, Robert J.; Melvin, David G.; Smedley, Damian; Brown, Steve D. M.; Flicek, Paul; Skarnes, William C.; Mallon, Ann-Marie; Parkinson, Helen

2014-01-01

The International Mouse Phenotyping Consortium (IMPC) web portal (http://www.mousephenotype.org) provides the biomedical community with a unified point of access to mutant mice and rich collection of related emerging and existing mouse phenotype data. IMPC mouse clinics worldwide follow rigorous highly structured and standardized protocols for the experimentation, collection and dissemination of data. Dedicated ‘data wranglers’ work with each phenotyping center to collate data and perform quality control of data. An automated statistical analysis pipeline has been developed to identify knockout strains with a significant change in the phenotype parameters. Annotation with biomedical ontologies allows biologists and clinicians to easily find mouse strains with phenotypic traits relevant to their research. Data integration with other resources will provide insights into mammalian gene function and human disease. As phenotype data become available for every gene in the mouse, the IMPC web portal will become an invaluable tool for researchers studying the genetic contributions of genes to human diseases. PMID:24194600

Response predictions using the observed autocorrelation function

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

2018-01-01

This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

Characterization of Rod Function Phenotypes Across a Range of Age-Related Macular Degeneration Severities and Subretinal Drusenoid Deposits.

Science.gov (United States)

Flynn, Oliver J; Cukras, Catherine A; Jeffrey, Brett G

2018-05-01

To examine spatial changes in rod-mediated function in relationship to local structural changes across the central retina in eyes with a spectrum of age-related macular degeneration (AMD) disease severity. Participants were categorized into five AMD severity groups based on fundus features. Scotopic thresholds were measured at 14 loci spanning ±18° along the vertical meridian from one eye of each of 42 participants (mean = 71.7 ± 9.9 years). Following a 30% bleach, dark adaptation was measured at eight loci (±12°). Rod intercept time (RIT) was defined from the time to detect a -3.1 log cd/m2 stimulus. RITslope was defined from the linear fit of RIT with decreasing retinal eccentricity. The presence of subretinal drusenoid deposits (SDD), ellipsoid (EZ) band disruption, and drusen at the test loci was evaluated using optical coherence tomography. Scotopic thresholds indicated greater rod function loss in the macula, which correlated with increasing AMD group severity. RITslope, which captures the spatial change in the rate of dark adaptation, increased with AMD severity (P < 0.0001). Three rod function phenotypes emerged: RF1, normal rod function; RF2, normal scotopic thresholds but slowed dark adaptation; and RF3, elevated scotopic thresholds with slowed dark adaptation. Dark adaptation was slowed at all loci with SDD or EZ band disruption, and at 32% of loci with no local structural changes. Three rod function phenotypes were defined from combined measurement of scotopic threshold and dark adaptation. Spatial changes in dark adaptation across the macula were captured with RITslope, which may be a useful outcome measure for functional studies of AMD.

Parametric Bayesian priors and better choice of negative examples improve protein function prediction.

Science.gov (United States)

Youngs, Noah; Penfold-Brown, Duncan; Drew, Kevin; Shasha, Dennis; Bonneau, Richard

2013-05-01

Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction. We present a novel approach for choosing negative examples, using a parameterizable Bayesian prior computed from all observed annotation data, which also generates priors used during function prediction. We incorporate this new method into the GeneMANIA function prediction algorithm and demonstrate improved accuracy of our algorithm over current top-performing function prediction methods on the yeast and mouse proteomes across all metrics tested. Code and Data are available at: http://bonneaulab.bio.nyu.edu/funcprop.html

Prevalence of comorbidities according to predominant phenotype and severity of chronic obstructive pulmonary disease

Directory of Open Access Journals (Sweden)

Camiciottoli G

2016-09-01

Full Text Available Gianna Camiciottoli,1,2 Francesca Bigazzi,1 Chiara Magni,1 Viola Bonti,1 Stefano Diciotti,3 Maurizio Bartolucci,4 Mario Mascalchi,5 Massimo Pistolesi1 1Section of Respiratory Medicine, Department of Clinical and Experimental Medicine, 2Department of Clinical and Experimental Biomedical Sciences, University of Florence, Florence, 3Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi,” University of Bologna, Cesena, 4Department of Diagnostic Imaging, Careggi University Hospital, 5Radiodiagnostic Section, Department of Clinical and Experimental Biomedical Sciences, University of Florence, Florence, Italy Background: In addition to lung involvement, several other diseases and syndromes coexist in patients with chronic obstructive pulmonary disease (COPD. Our purpose was to investigate the prevalence of idiopathic arterial hypertension (IAH, ischemic heart disease, heart failure, peripheral vascular disease (PVD, diabetes, osteoporosis, and anxious depressive syndrome in a clinical setting of COPD outpatients whose phenotypes (predominant airway disease and predominant emphysema and severity (mild and severe diseases were determined by clinical and functional parameters. Methods: A total of 412 outpatients with COPD were assigned either a predominant airway disease or a predominant emphysema phenotype of mild or severe degree according to predictive models based on pulmonary functions (forced expiratory volume in 1 second/vital capacity; total lung capacity %; functional residual capacity %; and diffusing capacity of lung for carbon monoxide % and sputum characteristics. Comorbidities were assessed by objective medical records. Results: Eighty-four percent of patients suffered from at least one comorbidity and 75% from at least one cardiovascular comorbidity, with IAH and PVD being the most prevalent ones (62% and 28%, respectively. IAH prevailed significantly in predominant airway disease, osteoporosis prevailed

Monocyte-lymphocyte fusion induced by the HIV-1 envelope generates functional heterokaryons with an activated monocyte-like phenotype

International Nuclear Information System (INIS)

Martínez-Méndez, David; Rivera-Toledo, Evelyn; Ortega, Enrique; Licona-Limón, Ileana; Huerta, Leonor

2017-01-01

Enveloped viruses induce cell-cell fusion when infected cells expressing viral envelope proteins interact with target cells, or through the contact of cell-free viral particles with adjoining target cells. CD4"+ T lymphocytes and cells from the monocyte-macrophage lineage express receptors for HIV envelope protein. We have previously reported that lymphoid Jurkat T cells expressing the HIV-1 envelope protein (Env) can fuse with THP-1 monocytic cells, forming heterokaryons with a predominantly myeloid phenotype. This study shows that the expression of monocytic markers in heterokaryons is stable, whereas the expression of lymphoid markers is mostly lost. Like THP-1 cells, heterokaryons exhibited FcγR-dependent phagocytic activity and showed an enhanced expression of the activation marker ICAM-1 upon stimulation with PMA. In addition, heterokaryons showed morphological changes compatible with maturation, and high expression of the differentiation marker CD11b in the absence of differentiation-inducing agents. No morphological change nor increase in CD11b expression were observed when an HIV-fusion inhibitor blocked fusion, or when THP-1 cells were cocultured with Jurkat cells expressing a non-fusogenic Env protein, showing that differentiation was not induced merely by cell-cell interaction but required cell-cell fusion. Inhibition of TLR2/TLR4 signaling by a TIRAP inhibitor greatly reduced the expression of CD11b in heterokaryons. Thus, lymphocyte-monocyte heterokaryons induced by HIV-1 Env are stable and functional, and fusion prompts a phenotype characteristic of activated monocytes via intracellular TLR2/TLR4 signaling. - Highlights: • Jurkat T cells expressing the HIV-1 envelope fuse with THP-1 monocytes. • Heterokaryons display a dominant myeloid phenotype and monocyte function. • Heterokaryons exhibit activation features in the absence of activation agents. • Activation is not due to cell-cell interaction but requires cell-cell fusion. • The

Monocyte-lymphocyte fusion induced by the HIV-1 envelope generates functional heterokaryons with an activated monocyte-like phenotype

Energy Technology Data Exchange (ETDEWEB)

Martínez-Méndez, David; Rivera-Toledo, Evelyn; Ortega, Enrique; Licona-Limón, Ileana; Huerta, Leonor, E-mail: leonorhh@biomedicas.unam.mx

2017-03-01

Enveloped viruses induce cell-cell fusion when infected cells expressing viral envelope proteins interact with target cells, or through the contact of cell-free viral particles with adjoining target cells. CD4{sup +} T lymphocytes and cells from the monocyte-macrophage lineage express receptors for HIV envelope protein. We have previously reported that lymphoid Jurkat T cells expressing the HIV-1 envelope protein (Env) can fuse with THP-1 monocytic cells, forming heterokaryons with a predominantly myeloid phenotype. This study shows that the expression of monocytic markers in heterokaryons is stable, whereas the expression of lymphoid markers is mostly lost. Like THP-1 cells, heterokaryons exhibited FcγR-dependent phagocytic activity and showed an enhanced expression of the activation marker ICAM-1 upon stimulation with PMA. In addition, heterokaryons showed morphological changes compatible with maturation, and high expression of the differentiation marker CD11b in the absence of differentiation-inducing agents. No morphological change nor increase in CD11b expression were observed when an HIV-fusion inhibitor blocked fusion, or when THP-1 cells were cocultured with Jurkat cells expressing a non-fusogenic Env protein, showing that differentiation was not induced merely by cell-cell interaction but required cell-cell fusion. Inhibition of TLR2/TLR4 signaling by a TIRAP inhibitor greatly reduced the expression of CD11b in heterokaryons. Thus, lymphocyte-monocyte heterokaryons induced by HIV-1 Env are stable and functional, and fusion prompts a phenotype characteristic of activated monocytes via intracellular TLR2/TLR4 signaling. - Highlights: • Jurkat T cells expressing the HIV-1 envelope fuse with THP-1 monocytes. • Heterokaryons display a dominant myeloid phenotype and monocyte function. • Heterokaryons exhibit activation features in the absence of activation agents. • Activation is not due to cell-cell interaction but requires cell-cell fusion. • The

Edaphic history over seedling characters predicts integration and plasticity of integration across geologically variable populations of Arabidopsis thaliana.

Science.gov (United States)

Cousins, Elsa A; Murren, Courtney J

2017-12-01

Studies on phenotypic plasticity and plasticity of integration have uncovered functionally linked modules of aboveground traits and seedlings of Arabidopsis thaliana , but we lack details about belowground variation in adult plants. Functional modules can be comprised of additional suites of traits that respond to environmental variation. We assessed whether shoot and root responses to nutrient environments in adult A. thaliana were predictable from seedling traits or population-specific geologic soil characteristics at the site of origin. We compared 17 natural accessions from across the native range of A. thaliana using 14-day-old seedlings grown on agar or sand and plants grown to maturity across nutrient treatments in sand. We measured aboveground size, reproduction, timing traits, root length, and root diameter. Edaphic characteristics were obtained from a global-scale dataset and related to field data. We detected significant among-population variation in root traits of seedlings and adults and in plasticity in aboveground and belowground traits of adult plants. Phenotypic integration of roots and shoots varied by population and environment. Relative integration was greater in roots than in shoots, and integration was predicted by edaphic soil history, particularly organic carbon content, whereas seedling traits did not predict later ontogenetic stages. Soil environment of origin has significant effects on phenotypic plasticity in response to nutrients, and on phenotypic integration of root modules and shoot modules. Root traits varied among populations in reproductively mature individuals, indicating potential for adaptive and integrated functional responses of root systems in annuals. © 2017 Botanical Society of America.

Computer vision and machine learning for robust phenotyping in genome-wide studies.

Science.gov (United States)

Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R V Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K

2017-03-08

Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

Science.gov (United States)

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Circadian phenotype composition is a major predictor of diurnal physical performance in teams

Directory of Open Access Journals (Sweden)

Elise Rose Facer-Childs

2015-10-01

Full Text Available Team performance is a complex phenomenon involving numerous influencing factors including physiology, psychology, and management. Biological rhythms and the impact of circadian phenotype have not been studied for their contribution to this array of factors so far despite our knowledge of the circadian regulation of key physiological processes involved in physical and mental performance. This study involved 216 individuals from 12 different teams who were categorized into circadian phenotypes using the novel RBUB chronometric test. The composition of circadian phenotypes within each team was used to model predicted daily team performance profiles based on physical performance tests. Our results show that the composition of circadian phenotypes within teams is variable and unpredictable. Predicted physical peak performance ranged from 1.52pm to 8.59pm with performance levels fluctuating by up to 14.88% over the course of the day. The major predictor for peak performance time of day in a team is the occurrence of late circadian phenotypes. We conclude that circadian phenotype is a performance indicator in teams that allows new insight and a better understanding of team performance variation in the course of a day as often observed in different groupings of individuals.

The effect of oxcarbazepine in peripheral neuropathic pain depends on pain phenotype: a randomised, double-blind, placebo-controlled phenotype-stratified study

DEFF Research Database (Denmark)

Demant, Dyveke T; Lund, Karen; Vollert, Jan

2014-01-01

In neuropathic pain it has been suggested that pain phenotype based on putative pain mechanisms may predict response to treatment. This was a randomised, double-blind, placebo-controlled, and phenotype-stratified study with 2 6-week treatment periods of oxcarbazepine (1800-2400mg) and placebo...... patients: 31 with the irritable and 52 with the nonirritable nociceptor phenotype. In the total sample, oxcarbazepine relieved pain of 0.7 points (on a numeric rating scale 0-10; 95% confidence interval [CI] 0.4-1.4) more than placebo (P=0.015) and there was a significant interaction between treatment....... The primary efficacy measure was change in median pain intensity between baseline and the last week of treatment measured on an 11-point numeric rating scale, and the primary objective was to compare the effect of oxcarbazepine in patients with and without the irritable nociceptor phenotype as defined...

Flow cytometric monitoring of bacterioplankton phenotypic diversity predicts high population-specific feeding rates by invasive dreissenid mussels.

Science.gov (United States)

Props, Ruben; Schmidt, Marian L; Heyse, Jasmine; Vanderploeg, Henry A; Boon, Nico; Denef, Vincent J

2018-02-01

Species invasion is an important disturbance to ecosystems worldwide, yet knowledge about the impacts of invasive species on bacterial communities remains sparse. Using a novel approach, we simultaneously detected phenotypic and derived taxonomic change in a natural bacterioplankton community when subjected to feeding pressure by quagga mussels, a widespread aquatic invasive species. We detected a significant decrease in diversity within 1 h of feeding and a total diversity loss of 11.6 ± 4.1% after 3 h. This loss of microbial diversity was caused by the selective removal of high nucleic acid populations (29 ± 5% after 3 h). We were able to track the community diversity at high temporal resolution by calculating phenotypic diversity estimates from flow cytometry (FCM) data of minute amounts of sample. Through parallel FCM and 16S rRNA gene amplicon sequencing analysis of environments spanning a broad diversity range, we showed that the two approaches resulted in highly correlated diversity measures and captured the same seasonal and lake-specific patterns in community composition. Based on our results, we predict that selective feeding by invasive dreissenid mussels directly impacts the microbial component of the carbon cycle, as it may drive bacterioplankton communities toward less diverse and potentially less productive states. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.; Clarke, S. L.; Guturu, H.; Chen, J.; Schaar, B. T.; McLean, C. Y.; Bejerano, G.

2013-01-01

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

PRISM offers a comprehensive genomic approach to transcription factor function prediction

KAUST Repository

Wenger, A. M.

2013-02-04

The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

Science.gov (United States)

Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

2016-03-01

We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional phenotypic rescue of Caenorhabditis elegans neuroligin-deficient mutants by the human and rat NLGN1 genes.

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Fernando Calahorro

Full Text Available Neuroligins are cell adhesion proteins that interact with neurexins at the synapse. This interaction may contribute to differentiation, plasticity and specificity of synapses. In humans, single mutations in neuroligin encoding genes lead to autism spectrum disorder and/or mental retardation. Caenorhabditis elegans mutants deficient in nlg-1, an orthologue of human neuroligin genes, have defects in different behaviors. Here we show that the expression of human NLGN1 or rat Nlgn1 cDNAs in C. elegans nlg-1 mutants rescues the fructose osmotic strength avoidance and gentle touch response phenotypes. Two specific point mutations in NLGN3 and NLGN4 genes, involved in autistic spectrum disorder, were further characterized in this experimental system. The R451C allele described in NLGN3, was analyzed with both human NLGN1 (R453C and worm NLG-1 (R437C proteins, and both were not functional in rescuing the osmotic avoidance behavior and the gentle touch response phenotype. The D396X allele described in NLGN4, which produces a truncated protein, was studied with human NLGN1 (D432X and they did not rescue any of the behavioral phenotypes analyzed. In addition, RNAi feeding experiments measuring gentle touch response in wild type strain and worms expressing SID-1 in neurons (which increases the response to dsRNA, both fed with bacteria expressing dsRNA for nlg-1, provided evidence for a postsynaptic in vivo function of neuroligins both in muscle cells and neurons, equivalent to that proposed in mammals. This finding was further confirmed generating transgenic nlg-1 deficient mutants expressing NLG-1 under pan-neuronal (nrx-1 or pan-muscular (myo-3 specific promoters. All these results suggest that the nematode could be used as an in vivo model for studying particular synaptic mechanisms with proteins orthologues of humans involved in pervasive developmental disorders.

Phenotypic and functional characterization of earthworm coelomocyte subsets: Linking light scatter-based cell typing and imaging of the sorted populations.

Science.gov (United States)

Engelmann, Péter; Hayashi, Yuya; Bodó, Kornélia; Ernszt, Dávid; Somogyi, Ildikó; Steib, Anita; Orbán, József; Pollák, Edit; Nyitrai, Miklós; Németh, Péter; Molnár, László

2016-12-01

Flow cytometry is a common approach to study invertebrate immune cells including earthworm coelomocytes. However, the link between light-scatter- and microscopy-based phenotyping remains obscured. Here we show, by means of light scatter-based cell sorting, both subpopulations (amoebocytes and eleocytes) can be physically isolated with good sort efficiency and purity confirmed by downstream morphological and cytochemical applications. Immunocytochemical analysis using anti-EFCC monoclonal antibodies combined with phalloidin staining has revealed antigenically distinct, sorted subsets. Screening of lectin binding capacity indicated wheat germ agglutinin (WGA) as the strongest reactor to amoebocytes. This is further evidenced by WGA inhibition assays that suggest high abundance of N-acetyl-d-glucosamine in amoebocytes. Post-sort phagocytosis assays confirmed the functional differences between amoebocytes and eleocytes, with the former being in favor of bacterial engulfment. This study has proved successful in linking flow cytometry and microscopy analysis and provides further experimental evidence of phenotypic and functional heterogeneity in earthworm coelomocyte subsets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feature Selection and the Class Imbalance Problem in Predicting Protein Function from Sequence

NARCIS (Netherlands)

Al-Shahib, A.; Breitling, R.; Gilbert, D.

2005-01-01

Abstract: When the standard approach to predict protein function by sequence homology fails, other alternative methods can be used that require only the amino acid sequence for predicting function. One such approach uses machine learning to predict protein function directly from amino acid sequence

[Cloning, mutagenesis and symbiotic phenotype of three lipid transfer protein encoding genes from Mesorhizobium huakuii 7653R].

Science.gov (United States)

Li, Yanan; Zeng, Xiaobo; Zhou, Xuejuan; Li, Youguo

2016-12-04

Lipid transfer protein superfamily is involved in lipid transport and metabolism. This study aimed to construct mutants of three lipid transfer protein encoding genes in Mesorhizobium huakuii 7653R, and to study the phenotypes and function of mutations during symbiosis with Astragalus sinicus. We used bioinformatics to predict structure characteristics and biological functions of lipid transfer proteins, and conducted semi-quantitative and fluorescent quantitative real-time PCR to analyze the expression levels of target genes in free-living and symbiotic conditions. Using pK19mob insertion mutagenesis to construct mutants, we carried out pot plant experiments to observe symbiotic phenotypes. MCHK-5577, MCHK-2172 and MCHK-2779 genes encoding proteins belonged to START/RHO alpha_C/PITP/Bet_v1/CoxG/CalC (SRPBCC) superfamily, involved in lipid transport or metabolism, and were identical to M. loti at 95% level. Gene relative transcription level of the three genes all increased compared to free-living condition. We obtained three mutants. Compared with wild-type 7653R, above-ground biomass of plants and nodulenitrogenase activity induced by the three mutants significantly decreased. Results indicated that lipid transfer protein encoding genes of Mesorhizobium huakuii 7653R may play important roles in symbiotic nitrogen fixation, and the mutations significantly affected the symbiotic phenotypes. The present work provided a basis to study further symbiotic function mechanism associated with lipid transfer proteins from rhizobia.

Individualized Hydrocodone Therapy Based on Phenotype, Pharmacogenetics, and Pharmacokinetic Dosing.

Science.gov (United States)

Linares, Oscar A; Fudin, Jeffrey; Daly, Annemarie L; Boston, Raymond C

2015-12-01

(1) To quantify hydrocodone (HC) and hydromorphone (HM) metabolite pharmacokinetics with pharmacogenetics in CYP2D6 ultra-rapid metabolizer (UM), extensive metabolizer (EM), and poor metabolizer (PM) metabolizer phenotypes. (2) To develop an HC phenotype-specific dosing strategy for HC that accounts for HM production using clinical pharmacokinetics integrated with pharmacogenetics for patient safety. In silico clinical trial simulation. Healthy white men and women without comorbidities or history of opioid, or any other drug or nutraceutical use, age 26.3±5.7 years (mean±SD; range, 19 to 36 y) and weight 71.9±16.8 kg (range, 50 to 108 kg). CYP2D6 phenotype-specific HC clinical pharmacokinetic parameter estimates and phenotype-specific percentages of HM formed from HC. PMs had lower indices of HC disposition compared with UMs and EMs. Clearance was reduced by nearly 60% and the t1/2 was increased by about 68% compared with EMs. The canonical order for HC clearance was UM>EM>PM. HC elimination mainly by the liver, represented by ke, was reduced about 70% in PM. However, HC's apparent Vd was not significantly different among UMs, EMs, and PM. The canonical order of predicted plasma HM concentrations was UM>EM>PM. For each of the CYP2D6 phenotypes, the mean predicted HM levels were within HM's therapeutic range, which indicates HC has significant phenotype-dependent pro-drug effects. Our results demonstrate that pharmacogenetics afford clinicians an opportunity to individualize HC dosing, while adding enhanced opportunity to account for its conversion to HM in the body.

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

Predictive assessment of models for dynamic functional connectivity

DEFF Research Database (Denmark)

Nielsen, Søren Føns Vind; Schmidt, Mikkel Nørgaard; Madsen, Kristoffer Hougaard

2018-01-01

represent functional brain networks as a meta-stable process with a discrete number of states; however, there is a lack of consensus on how to perform model selection and learn the number of states, as well as a lack of understanding of how different modeling assumptions influence the estimated state......In neuroimaging, it has become evident that models of dynamic functional connectivity (dFC), which characterize how intrinsic brain organization changes over time, can provide a more detailed representation of brain function than traditional static analyses. Many dFC models in the literature...... dynamics. To address these issues, we consider a predictive likelihood approach to model assessment, where models are evaluated based on their predictive performance on held-out test data. Examining several prominent models of dFC (in their probabilistic formulations) we demonstrate our framework...

Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer

Directory of Open Access Journals (Sweden)

Yinhui Zhang

2015-01-01

Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.

Automatic single- and multi-label enzymatic function prediction by machine learning

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Shervine Amidi

2017-03-01

Full Text Available The number of protein structures in the PDB database has been increasing more than 15-fold since 1999. The creation of computational models predicting enzymatic function is of major importance since such models provide the means to better understand the behavior of newly discovered enzymes when catalyzing chemical reactions. Until now, single-label classification has been widely performed for predicting enzymatic function limiting the application to enzymes performing unique reactions and introducing errors when multi-functional enzymes are examined. Indeed, some enzymes may be performing different reactions and can hence be directly associated with multiple enzymatic functions. In the present work, we propose a multi-label enzymatic function classification scheme that combines structural and amino acid sequence information. We investigate two fusion approaches (in the feature level and decision level and assess the methodology for general enzymatic function prediction indicated by the first digit of the enzyme commission (EC code (six main classes on 40,034 enzymes from the PDB database. The proposed single-label and multi-label models predict correctly the actual functional activities in 97.8% and 95.5% (based on Hamming-loss of the cases, respectively. Also the multi-label model predicts all possible enzymatic reactions in 85.4% of the multi-labeled enzymes when the number of reactions is unknown. Code and datasets are available at https://figshare.com/s/a63e0bafa9b71fc7cbd7.

Functional Associations by Response Overlap (FARO, a functional genomics approach matching gene expression phenotypes.

Directory of Open Access Journals (Sweden)

Henrik Bjørn Nielsen

2007-08-01

Full Text Available The systematic comparison of transcriptional responses of organisms is a powerful tool in functional genomics. For example, mutants may be characterized by comparing their transcript profiles to those obtained in other experiments querying the effects on gene expression of many experimental factors including treatments, mutations and pathogen infections. Similarly, drugs may be discovered by the relationship between the transcript profiles effectuated or impacted by a candidate drug and by the target disease. The integration of such data enables systems biology to predict the interplay between experimental factors affecting a biological system. Unfortunately, direct comparisons of gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment-specific biases. Here we suggest a novel yet conceptually simple approach for deriving 'Functional Association(s by Response Overlap' (FARO between microarray gene expression studies. The transcriptional response is defined by the set of differentially expressed genes independent from the magnitude or direction of the change. This approach overcomes the limited comparability between studies that is typical for methods that rely on correlation in gene expression. We apply FARO to a compendium of 242 diverse Arabidopsis microarray experimental factors, including phyto-hormones, stresses and pathogens, growth conditions/stages, tissue types and mutants. We also use FARO to confirm and further delineate the functions of Arabidopsis MAP kinase 4 in disease and stress responses. Furthermore, we find that a large, well-defined set of genes responds in opposing directions to different stress conditions and predict the effects of different stress combinations. This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors. Finally, our

FeNO as biomarker for asthma phenotyping and management.

Science.gov (United States)

Ricciardolo, Fabio L M; Sorbello, Valentina; Ciprandi, Giorgio

2015-01-01

The current review aims to revisit literature on exhaled nitric oxide (FeNO) in asthma phenotyping and management to clarify the utility of this test in clinical practice. It is increasingly evident that multiple profiles characterize asthma as a complex disease for which is necessary to find tools able to discriminate among these phenotypes to achieve the best therapeutic strategy for all asthmatic patients. Current findings indicate that FeNO, a noninvasive and easy-to-obtain biomarker, can be considered a useful tool in predicting asthma developing and exacerbation, in identifying specific asthma phenotypes, in improving asthma diagnosis and management in a selected population, and in monitoring efficacy of standard corticosteroid and biologic therapy. Based on this evidence, FeNO might become an appropriate tool for physicians to better define specific asthma phenotypes and to better deal with asthma worsening.

EuroPhenome and EMPReSS: online mouse phenotyping resource.

Science.gov (United States)

Mallon, Ann-Marie; Blake, Andrew; Hancock, John M

2008-01-01

EuroPhenome (http://www.europhenome.org) and EMPReSS (http://empress.har.mrc.ac.uk/) form an integrated resource to provide access to data and procedures for mouse phenotyping. EMPReSS describes 96 Standard Operating Procedures for mouse phenotyping. EuroPhenome contains data resulting from carrying out EMPReSS protocols on four inbred laboratory mouse strains. As well as web interfaces, both resources support web services to enable integration with other mouse phenotyping and functional genetics resources, and are committed to initiatives to improve integration of mouse phenotype databases. EuroPhenome will be the repository for a recently initiated effort to carry out large-scale phenotyping on a large number of knockout mouse lines (EUMODIC).

Phenotype Instance Verification and Evaluation Tool (PIVET): A Scaled Phenotype Evidence Generation Framework Using Web-Based Medical Literature

Science.gov (United States)

Ke, Junyuan; Ho, Joyce C; Ghosh, Joydeep; Wallace, Byron C

2018-01-01

which PheKnow-Cloud was originally developed, but PIVET’s analysis is an order of magnitude faster than that of PheKnow-Cloud. Not only is PIVET much faster, it can be scaled to a larger corpus and still retain speed. We evaluated multiple classification models on top of the PIVET framework and found ridge regression to perform best, realizing an average F1 score of 0.91 when predicting clinically relevant phenotypes. Conclusions Our study shows that PIVET improves on the most notable existing computational tool for phenotype validation in terms of speed and automation and is comparable in terms of accuracy. PMID:29728351

Functional validation of candidate genes detected by genomic feature models

DEFF Research Database (Denmark)

Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

2018-01-01

Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated...

Hsp90 selectively modulates phenotype in vertebrate development.

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Patricia L Yeyati

2007-03-01

Full Text Available Compromised heat shock protein 90 (Hsp90 function reveals cryptic phenotypes in flies and plants. These observations were interpreted to suggest that this molecular stress-response chaperone has a capacity to buffer underlying genetic variation. Conversely, the protective role of Hsp90 could account for the variable penetrance or severity of some heritable developmental malformations in vertebrates. Using zebrafish as a model, we defined Hsp90 inhibitor levels that did not induce a heat shock response or perturb phenotype in wild-type strains. Under these conditions the severity of the recessive eye phenotype in sunrise, caused by a pax6b mutation, was increased, while in dreumes, caused by a sufu mutation, it was decreased. In another strain, a previously unobserved spectrum of severe structural eye malformations, reminiscent of anophthalmia, microphthalmia, and nanophthalmia complex in humans, was uncovered by this limited inhibition of Hsp90 function. Inbreeding of offspring from selected unaffected carrier parents led to significantly elevated malformation frequencies and revealed the oligogenic nature of this phenotype. Unlike in Drosophila, Hsp90 inhibition can decrease developmental stability in zebrafish, as indicated by increased asymmetric presentation of anophthalmia, microphthalmia, and nanophthalmia and sunrise phenotypes. Analysis of the sunrise pax6b mutation suggests a molecular mechanism for the buffering of mutations by Hsp90. The zebrafish studies imply that mild perturbation of Hsp90 function at critical developmental stages may underpin the variable penetrance and expressivity of many developmental anomalies where the interaction between genotype and environment plays a major role.

Phenotypic spectrum of GABRA1

DEFF Research Database (Denmark)

Johannesen, Katrine; Marini, Carla; Pfeffer, Siona

2016-01-01

OBJECTIVE: To delineate phenotypic heterogeneity, we describe the clinical features of a cohort of patients with GABRA1 gene mutations. METHODS: Patients with GABRA1 mutations were ascertained through an international collaboration. Clinical, EEG, and genetic data were collected. Functional analy...

Noise genetics: inferring protein function by correlating phenotype with protein levels and localization in individual human cells.

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Shlomit Farkash-Amar

2014-03-01

Full Text Available To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.

Phenotypic and Functional Changes Induced in Hematopoietic Stem/Progenitor Cells After Gamma-Ray Radiation Exposure

International Nuclear Information System (INIS)

Simonnet, A.J.; Nehme, J.; Leboulch, Ph.; Tronik-Le Roux, D.; Simonnet, A.J.; Nehme, J.; Leboulch, Ph.; Tronik-Le Roux, D.; Vaigot, P.; Vaigot, P.; Barroca, V.; Barroca, V.; Leboulch, Ph.

2009-01-01

Ionizing radiation (IR) exposure causes rapid and acute bone marrow (BM) suppression that is reversible for nonlethal doses. Evidence is accumulating that IR can also provoke long-lasting residual hematopoietic injury. To better understand these effects, we analyzed phenotypic and functional changes in the stem/progenitor compartment of irradiated mice over a 10-week period. We found that hematopoietic stem cells (HSCs) identified by their repopulating ability continued to segregate within the Hoechst dye excluding 'side population (SP)' early after IR exposure. However, transient phenotypic changes were observed within this cell population: Sca-1 (S) and c-Kit (K) expression levels were increased and severely reduced, respectively, with a concurrent increase in the proportion of SPSK cells positive for established indicators of the presence of HSCs: CD150 and CD105. Ten weeks after IR exposure, expression of Sca-1 and c-Kit at the SP cell surface returned to control levels, and BM cellularity of irradiated mice was restored. However, the c-Kit + Sca-1 + Lin -/low (KSL) stem/progenitor compartment displayed major phenotypic modifications, including an increase and a severe decrease in the frequencies of CD150 + Flk2 - and CD150 - Flk2 + cells, respectively. CD150 + KSL cells also showed impaired reconstituting ability, an increased tendency to apoptosis, and accrued DNA damage. Finally, 15 weeks after exposure, irradiated mice, but not age matched controls, allowed engraftment and significant hematopoietic contribution from transplanted con-genic HSCs without additional host conditioning. These results provide novel insight in our understanding of immediate and delayed IR-induced hematopoietic injury and highlight similarities between HSCs of young irradiated and old mice. (authors)

Concomitant prediction of function and fold at the domain level with GO-based profiles.

Science.gov (United States)

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Circadian Phenotype Composition is a Major Predictor of Diurnal Physical Performance in Teams.

Science.gov (United States)

Facer-Childs, Elise; Brandstaetter, Roland

2015-01-01

Team performance is a complex phenomenon involving numerous influencing factors including physiology, psychology, and management. Biological rhythms and the impact of circadian phenotype have not been studied for their contribution to this array of factors so far despite our knowledge of the circadian regulation of key physiological processes involved in physical and mental performance. This study involved 216 individuals from 12 different teams who were categorized into circadian phenotypes using the novel RBUB chronometric test. The composition of circadian phenotypes within each team was used to model predicted daily team performance profiles based on physical performance tests. Our results show that the composition of circadian phenotypes within teams is variable and unpredictable. Predicted physical peak performance ranged from 1:52 to 8:59 p.m. with performance levels fluctuating by up to 14.88% over the course of the day. The major predictor for peak performance time in the course of a day in a team is the occurrence of late circadian phenotypes. We conclude that circadian phenotype is a performance indicator in teams that allows new insight and a better understanding of team performance variation in the course of a day as often observed in different groupings of individuals.

Mutations in PIGY: expanding the phenotype of inherited glycosylphosphatidylinositol deficiencies.

Science.gov (United States)

Ilkovski, Biljana; Pagnamenta, Alistair T; O'Grady, Gina L; Kinoshita, Taroh; Howard, Malcolm F; Lek, Monkol; Thomas, Brett; Turner, Anne; Christodoulou, John; Sillence, David; Knight, Samantha J L; Popitsch, Niko; Keays, David A; Anzilotti, Consuelo; Goriely, Anne; Waddell, Leigh B; Brilot, Fabienne; North, Kathryn N; Kanzawa, Noriyuki; Macarthur, Daniel G; Taylor, Jenny C; Kini, Usha; Murakami, Yoshiko; Clarke, Nigel F

2015-11-01

Glycosylphosphatidylinositol (GPI)-anchored proteins are ubiquitously expressed in the human body and are important for various functions at the cell surface. Mutations in many GPI biosynthesis genes have been described to date in patients with multi-system disease and together these constitute a subtype of congenital disorders of glycosylation. We used whole exome sequencing in two families to investigate the genetic basis of disease and used RNA and cellular studies to investigate the functional consequences of sequence variants in the PIGY gene. Two families with different phenotypes had homozygous recessive sequence variants in the GPI biosynthesis gene PIGY. Two sisters with c.137T>C (p.Leu46Pro) PIGY variants had multi-system disease including dysmorphism, seizures, severe developmental delay, cataracts and early death. There were significantly reduced levels of GPI-anchored proteins (CD55 and CD59) on the surface of patient-derived skin fibroblasts (∼20-50% compared with controls). In a second, consanguineous family, two siblings had moderate development delay and microcephaly. A homozygous PIGY promoter variant (c.-540G>A) was detected within a 7.7 Mb region of autozygosity. This variant was predicted to disrupt a SP1 consensus binding site and was shown to be associated with reduced gene expression. Mutations in PIGY can occur in coding and non-coding regions of the gene and cause variable phenotypes. This article contributes to understanding of the range of disease phenotypes and disease genes associated with deficiencies of the GPI-anchor biosynthesis pathway and also serves to highlight the potential importance of analysing variants detected in 5'-UTR regions despite their typically low coverage in exome data. © The Author 2015. Published by Oxford University Press.

Disorganized Symptoms and Executive Functioning Predict Impaired Social Functioning in Subjects at Risk for Psychosis

OpenAIRE

Eslami, Ali; Jahshan, Carol; Cadenhead, Kristin S.

2011-01-01

Predictors of social functioning deficits were assessed in 22 individuals “at risk” for psychosis. Disorganized symptoms and executive functioning predicted social functioning at follow-up. Early intervention efforts that focus on social and cognitive skills are indicated in this vulnerable population.

Patient-specific prediction of functional recovery after stroke.

Science.gov (United States)

Douiri, Abdel; Grace, Justin; Sarker, Shah-Jalal; Tilling, Kate; McKevitt, Christopher; Wolfe, Charles DA; Rudd, Anthony G

2017-07-01

Background and aims Clinical predictive models for stroke recovery could offer the opportunity of targeted early intervention and more specific information for patients and carers. In this study, we developed and validated a patient-specific prognostic model for monitoring recovery after stroke and assessed its clinical utility. Methods Four hundred and ninety-five patients from the population-based South London Stroke Register were included in a substudy between 2002 and 2004. Activities of daily living were assessed using Barthel Index) at one, two, three, four, six, eight, 12, 26, and 52 weeks after stroke. Penalized linear mixed models were developed to predict patients' functional recovery trajectories. An external validation cohort included 1049 newly registered stroke patients between 2005 and 2011. Prediction errors on discrimination and calibration were assessed. The potential clinical utility was evaluated using prognostic accuracy measurements and decision curve analysis. Results Predictive recovery curves showed good accuracy, with root mean squared deviation of 3 Barthel Index points and a R 2 of 83% up to one year after stroke in the external cohort. The negative predictive values of the risk of poor recovery (Barthel Index <8) at three and 12 months were also excellent, 96% (95% CI [93.6-97.4]) and 93% [90.8-95.3], respectively, with a potential clinical utility measured by likelihood ratios (LR+:17 [10.8-26.8] at three months and LR+:11 [6.5-17.2] at 12 months). Decision curve analysis showed an increased clinical benefit, particularly at threshold probabilities of above 5% for predictive risk of poor outcomes. Conclusions A recovery curves tool seems to accurately predict progression of functional recovery in poststroke patients.

Molecular Mechanisms Modulating the Phenotype of Macrophages and Microglia

Directory of Open Access Journals (Sweden)

Stephanie A. Amici

2017-11-01

Full Text Available Macrophages and microglia play crucial roles during central nervous system development, homeostasis and acute events such as infection or injury. The diverse functions of tissue macrophages and microglia are mirrored by equally diverse phenotypes. A model of inflammatory/M1 versus a resolution phase/M2 macrophages has been widely used. However, the complexity of macrophage function can only be achieved by the existence of varied, plastic and tridimensional macrophage phenotypes. Understanding how tissue macrophages integrate environmental signals via molecular programs to define pathogen/injury inflammatory responses provides an opportunity to better understand the multilayered nature of macrophages, as well as target and modulate cellular programs to control excessive inflammation. This is particularly important in MS and other neuroinflammatory diseases, where chronic inflammatory macrophage and microglial responses may contribute to pathology. Here, we perform a comprehensive review of our current understanding of how molecular pathways modulate tissue macrophage phenotype, covering both classic pathways and the emerging role of microRNAs, receptor-tyrosine kinases and metabolism in macrophage phenotype. In addition, we discuss pathway parallels in microglia, novel markers helpful in the identification of peripheral macrophages versus microglia and markers linked to their phenotype.

Effects of HIV infection and ART on phenotype and function of circulating monocytes, natural killer, and innate lymphoid cells.

Science.gov (United States)

Nabatanzi, Rose; Cose, Stephen; Joloba, Moses; Jones, Sarah Rowland; Nakanjako, Damalie

2018-03-15

HIV infection causes upregulation of markers of inflammation, immune activation and apoptosis of host adaptive, and innate immune cells particularly monocytes, natural killer (NK) and innate lymphoid cells (ILCs). Although antiretroviral therapy (ART) restores CD4 T-cell counts, the persistent aberrant activation of monocytes, NK and ILCs observed likely contributes to the incomplete recovery of T-cell effector functions. A better understanding of the effects of HIV infection and ART on the phenotype and function of circulating monocytes, NK, and ILCs is required to guide development of novel therapeutic interventions to optimize immune recovery.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

Phenotypic approaches to gene mapping in platelet function disorders - identification of new variant of P2Y12, TxA2 and GPVI receptors.

Science.gov (United States)

Watson, S; Daly, M; Dawood, B; Gissen, P; Makris, M; Mundell, S; Wilde, J; Mumford, A

2010-01-01

Platelet number or function disorders cause a range of bleeding symptoms from mild to severe. Patients with platelet dysfunction but normal platelet number are the most prevalent and typically have mild bleeding symptoms. The study of this group of patients is particularly difficult because of the lack of a gold-standard test of platelet function and the variable penetrance of the bleeding phenotype among affected individuals. The purpose of this short review is to discuss the way in which this group of patients can be investigated through platelet phenotyping in combination with targeted gene sequencing. This approach has been used recently to identify patients with mutations in key platelet activation receptors, namely those for ADP, collagen and thromboxane A2 (TxA2). One interesting finding from this work is that for some patients, mild bleeding is associated with heterozygous mutations in platelet proteins that are co-inherited with other genetic disorders of haemostasis such as type 1 von Willebrand's disease. Thus, the phenotype of mild bleeding may be multifactorial in some patients and may be considered to be a complex trait.

Arsenic (+3 oxidation state) methyltransferase and the inorganic arsenic methylation phenotype

International Nuclear Information System (INIS)

Li Jiaxin; Waters, Stephen B.; Drobna, Zuzana; Devesa, Vicenta; Styblo, Miroslav; Thomas, David J.

2005-01-01

Inorganic arsenic is enzymatically methylated; hence, its ingestion results in exposure to the parent compound and various methylated arsenicals. Both experimental and epidemiological evidences suggest that some of the adverse health effects associated with chronic exposure to inorganic arsenic may be mediated by these methylated metabolites. If i As methylation is an activation process, then the phenotype for inorganic arsenic methylation may determine risk associated with exposure to this metalloid. We examined inorganic arsenic methylation phenotypes and arsenic (+3 oxidation state) methyltransferase genotypes in four species: three that methylate inorganic arsenic (human (Homo sapiens), rat (Rattus norwegicus), and mouse (Mus musculus)) and one that does not methylate inorganic arsenic (chimpanzee, Pan troglodytes). The predicted protein products from arsenic (+3 oxidation state) methyltransferase are similar in size for rat (369 amino acid residues), mouse (376 residues), and human (375 residues). By comparison, a 275-nucleotide deletion beginning at nucleotide 612 in the chimpanzee gene sequence causes a frameshift that leads to a nonsense mutation for a premature stop codon after amino acid 205. The null phenotype for inorganic arsenic methylation in the chimpanzee is likely due to the deletion in the gene for arsenic (+3 oxidation state) methyltransferase that yields an inactive truncated protein. This lineage-specific loss of function caused by the deletion event must have occurred in the Pan lineage after Homo-Pan divergence about 5 million years ago

Inference of gene-phenotype associations via protein-protein interaction and orthology.

Directory of Open Access Journals (Sweden)

Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

An Influence Function Method for Predicting Store Aerodynamic Characteristics during Weapon Separation,

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1981-05-14

8217 AO-Ail 777 GRUMMAN AEROSPACE CORP BETHPAGE NY F/G 20/4 AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC C--ETCCU) MAY 8 1 R MEYER, A...CENKO, S YARDS UNCLASSIFIED N ’.**~~N**n I EHEEKI j~j .25 Q~4 111110 111_L 5. AN INFLUENCE FUNCTION METHOD FOR PREDICTING STORE AERODYNAMIC...extended to their logical conclusion one is led quite naturally to consideration of an " Influence Function Method" for I predicting store aerodynamic

Onco-proteogenomics: Multi-omics level data integration for accurate phenotype prediction.

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Dimitrakopoulos, Lampros; Prassas, Ioannis; Diamandis, Eleftherios P; Charames, George S

2017-09-01

The overall goal of translational oncology is to identify molecular alterations indicative of cancer or of responsiveness to specific therapeutic regimens. While next-generation sequencing has played a pioneering role in this quest, the latest advances in proteomic technologies promise to provide a holistic approach to the further elucidation of tumor biology. Genetic information may be written in DNA and flow from DNA to RNA to protein, according to the central dogma of molecular biology, but the observed phenotype is dictated predominantly by the DNA protein coding region-derived proteotype. Proteomics holds the potential to bridge the gap between genotype and phenotype, because the powerful analytical tool of mass spectrometry has reached a point of maturity to serve this purpose effectively. This integration of "omics" data has given birth to the novel field of onco-proteogenomics, which has much to offer to precision medicine and personalized patient management. Here, we review briefly how each "omics" technology has individually contributed to cancer research, discuss technological and computational advances that have contributed to the realization of onco-proteogenomics, and summarize current and future translational applications.

Prediction of postoperative pulmonary function using 99mTc-MAA perfusion lung SPECT

International Nuclear Information System (INIS)

Hosokawa, Nobuyuki; Tanabe, Masatada; Satoh, Katashi; Takashima, Hitoshi; Ohkawa, Motoomi; Maeda, Masazumi; Tamai, Toyosato; Kojima, Kanji.

1995-01-01

In order to predict postoperative pulmonary function, 99m Tc-MAA perfusion lung SPECT and spirometry were performed preoperatively in 52 patients with resectable primary lung cancer; 44 underwent lobectomy, eight pneumonectomy. Local pulmonary function (called local effective volume) was evaluated according to the degree of radionuclide distribution of each voxel in the SPECT images. The total effective volume was defined as the sum of the local effective volume, and the residual effective volume was the total effective volume excluding loss after operation. Predicted pulmonary function (VC and FEV 1.0) was calculated by the following formula: Predicted value=preoperative value x percent of the residual effective volume. Postoperative pulmonary function was predicted in the same patients by means of 99m Tc-MAA perfusion lung planar scintigraphy and X-ray CT. The patients were reinvestigated with spirometry at one and four months after surgery, and the values were compared with the predicted values. The correlations between the predicted values using SPECT and measured postoperative pulmonary function were highly significant (VC: r=0.867, FEV1.0: r=0.864 one month after operation; VC: r=0.860, FEV1.0: r=0.907 4 months after operation). The predicted values calculated using SPECT were accurate compared with the predicted values calculated using planar scintigraphy or X-ray CT. The patients with predicted FEV1.0 of less than 0.8 liter required home oxygen therapy. This method is valuable for the prediction of postoperative pulmonary function before the surgical procedure. (author)

Regional differences in prediction models of lung function in Germany

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Schäper Christoph

2010-04-01

Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.

Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease

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Qi Lin

2018-04-01

Full Text Available Resting-state functional connectivity (rs-FC is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11 scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

Phenotype/genotype correlation in a case series of Stargardt's patients identifies novel mutations in the ABCA4 gene.

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Gemenetzi, M; Lotery, A J

2013-11-01

To investigate phenotypic variability in terms of best-corrected visual acuity (BCVA) in patients with Stargardt disease (STGD) and confirmed ABCA4 mutations. Entire coding region analysis of the ABCA4 gene by direct sequencing of seven patients with clinical findings of STGD seen in the Retina Clinics of Southampton Eye Unit between 2002 and 2011.Phenotypic variables recorded were BCVA, fluorescein angiographic appearance, electrophysiology, and visual fields. All patients had heterozygous amino acid-changing variants (missense mutations) in the ABCA4 gene. A splice sequence change was found in a 30-year-old patient with severly affected vision. Two novel sequence changes were identified: a missense mutation in a mildly affected 44-year-old patient and a frameshift mutation in a severly affected 34-year-old patient. The identified ABCA4 mutations were compatible with the resulting phenotypes in terms of BCVA. Higher BCVAs were recorded in patients with missense mutations. Sequence changes, predicted to have more deleterious effect on protein function, resulted in a more severe phenotype. This case series of STGD patients demonstrates novel genotype/phenotype correlations, which may be useful to counselling of patients. This information may prove useful in selection of candidates for clinical trials in ABCA4 disease.

Transgenerational transmission of a stress-coping phenotype programmed by early-life stress in the Japanese quail

Science.gov (United States)

Zimmer, Cédric; Larriva, Maria; Boogert, Neeltje J.; Spencer, Karen A.

2017-01-01

An interesting aspect of developmental programming is the existence of transgenerational effects that influence offspring characteristics and performance later in life. These transgenerational effects have been hypothesized to allow individuals to cope better with predictable environmental fluctuations and thus facilitate adaptation to changing environments. Here, we test for the first time how early-life stress drives developmental programming and transgenerational effects of maternal exposure to early-life stress on several phenotypic traits in their offspring in a functionally relevant context using a fully factorial design. We manipulated pre- and/or post-natal stress in both Japanese quail mothers and offspring and examined the consequences for several stress-related traits in the offspring generation. We show that pre-natal stress experienced by the mother did not simply affect offspring phenotype but resulted in the inheritance of the same stress-coping traits in the offspring across all phenotypic levels that we investigated, shaping neuroendocrine, physiological and behavioural traits. This may serve mothers to better prepare their offspring to cope with later environments where the same stressors are experienced. PMID:28387355

The hidden function of egg white antimicrobials: egg weight-dependent effects of avidin on avian embryo survival and hatchling phenotype

Czech Academy of Sciences Publication Activity Database

Krkavcová, E.; Kreisinger, J.; Hyánková, L.; Hyršl, P.; Javůrková, Veronika

2018-01-01

Roč. 7, č. 4 (2018), č. článku bio031518. ISSN 2046-6390 Keywords : biotin deficiency affects * growth-performance * binding protein * intraspecific variation * maternal testosterone * divergent selection * offspring phenotype * immune function * chi cken-embryo * precocial bird * Albumen * maternal effects * antimicrobials * Avidin-biotin complex * embryogenesis * plasma complement Impact factor: 2.095, year: 2016

Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach.

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Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah; Shahar, Suzana

2018-01-01

The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting.

Haptoglobin Phenotype Predicts a Low Heart Rate Variability in Patients with Chronic Kidney Disease

DEFF Research Database (Denmark)

Svensson, My; Strandhave, Charlotte; Krarup, H.B.

2009-01-01

whether Hp phenotyping in patients with CKD could identify a group of high-risk patients according to HRV measurements. Methods: Patients (n = 61) were recruited from our outpatient clinic. They were eligible if they had CKD, defined as a plasma creatinine level between 1.70 and 4.52 mg/dL, for more than...... 3 months. The Hp phenotype was determined using a high-performance liquid chromatography. Furthermore, a 24-hour Holter recording was obtained in each patient for analysis of 24-h HRV indices in the time domain. Results: The CKD patients in the three groups [phenotypes Hp 1-1 (n=12), Hp 2-1 (n=32......), and Hp 2-2 (n=17)] were comparable regarding clinical relevant parameters such as age, plasma creatinine, body mass index, PTH level, and haemoglobin. Furthermore, sodium-, potassium-, and calcium levels were within normal range in all patients. The HRV parameter SDNN (SD of all normal RR...

Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.

Directory of Open Access Journals (Sweden)

Christopher Y Park

Full Text Available A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction. We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics

Comparison between frailty index of deficit accumulation and phenotypic model to predict risk of falls: data from the global longitudinal study of osteoporosis in women (GLOW Hamilton cohort.

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Guowei Li

Full Text Available To compare the predictive accuracy of the frailty index (FI of deficit accumulation and the phenotypic frailty (PF model in predicting risks of future falls, fractures and death in women aged ≥55 years.Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW 3-year Hamilton cohort (n = 3,985, we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1 investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20% of the FI and PF; (2 trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail which were defined by the PF; (3 categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures.The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56 in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs for falls (AUCs ≥ 0.68 and death (AUCs ≥ 0.79, and c-indices for fractures (c-indices ≥ 0.69 respectively.The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings.

Comparison between frailty index of deficit accumulation and phenotypic model to predict risk of falls: data from the global longitudinal study of osteoporosis in women (GLOW) Hamilton cohort.

Science.gov (United States)

Li, Guowei; Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra; Adachi, Jonathan D

2015-01-01

To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged ≥55 years. Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs ≥ 0.68) and death (AUCs ≥ 0.79), and c-indices for fractures (c-indices ≥ 0.69) respectively. The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings.

Predicting restoration of kidney function during CRRT-free intervals

Directory of Open Access Journals (Sweden)

Heise Daniel

2012-01-01

Full Text Available Abstract Background Renal failure is common in critically ill patients and frequently requires continuous renal replacement therapy (CRRT. CRRT is discontinued at regular intervals for routine changes of the disposable equipment or for replacing clogged filter membrane assemblies. The present study was conducted to determine if the necessity to continue CRRT could be predicted during the CRRT-free period. Materials and methods In the period from 2003 to 2006, 605 patients were treated with CRRT in our ICU. A total of 222 patients with 448 CRRT-free intervals had complete data sets and were used for analysis. Of the total CRRT-free periods, 225 served as an evaluation group. Twenty-nine parameters with an assumed influence on kidney function were analyzed with regard to their potential to predict the restoration of kidney function during the CRRT-free interval. Using univariate analysis and logistic regression, a prospective index was developed and validated in the remaining 223 CRRT-free periods to establish its prognostic strength. Results Only three parameters showed an independent influence on the restoration of kidney function during CRRT-free intervals: the number of previous CRRT cycles (medians in the two outcome groups: 1 vs. 2, the "Sequential Organ Failure Assessment"-score (means in the two outcome groups: 8.3 vs. 9.2 and urinary output after the cessation of CRRT (medians in two outcome groups: 66 ml/h vs. 10 ml/h. The prognostic index, which was calculated from these three variables, showed a satisfactory potential to predict the kidney function during the CRRT-free intervals; Receiver operating characteristic (ROC analysis revealed an area under the curve of 0.798. Conclusion Restoration of kidney function during CRRT-free periods can be predicted with an index calculated from three variables. Prospective trials in other hospitals must clarify whether our results are generally transferable to other patient populations.

Phenotype Instance Verification and Evaluation Tool (PIVET): A Scaled Phenotype Evidence Generation Framework Using Web-Based Medical Literature.

Science.gov (United States)

Henderson, Jette; Ke, Junyuan; Ho, Joyce C; Ghosh, Joydeep; Wallace, Byron C

2018-05-04

PIVET's analysis is an order of magnitude faster than that of PheKnow-Cloud. Not only is PIVET much faster, it can be scaled to a larger corpus and still retain speed. We evaluated multiple classification models on top of the PIVET framework and found ridge regression to perform best, realizing an average F1 score of 0.91 when predicting clinically relevant phenotypes. Our study shows that PIVET improves on the most notable existing computational tool for phenotype validation in terms of speed and automation and is comparable in terms of accuracy. ©Jette Henderson, Junyuan Ke, Joyce C Ho, Joydeep Ghosh, Byron C Wallace. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 04.05.2018.

New genes as drivers of phenotypic evolution

Science.gov (United States)

Chen, Sidi; Krinsky, Benjamin H.; Long, Manyuan

2014-01-01

During the course of evolution, genomes acquire novel genetic elements as sources of functional and phenotypic diversity, including new genes that originated in recent evolution. In the past few years, substantial progress has been made in understanding the evolution and phenotypic effects of new genes. In particular, an emerging picture is that new genes, despite being present in the genomes of only a subset of species, can rapidly evolve indispensable roles in fundamental biological processes, including development, reproduction, brain function and behaviour. The molecular underpinnings of how new genes can develop these roles are starting to be characterized. These recent discoveries yield fresh insights into our broad understanding of biological diversity at refined resolution. PMID:23949544

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm.

Science.gov (United States)

Reinbolt, Raquel E; Sonis, Stephen; Timmers, Cynthia D; Fernández-Martínez, Juan Luis; Cernea, Ana; de Andrés-Galiana, Enrique J; Hashemi, Sepehr; Miller, Karin; Pilarski, Robert; Lustberg, Maryam B

2018-01-01

Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor-related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm (NAA) to predict AIA using germline single nucleotide polymorphisms (SNP) data obtained before treatment initiation. Systematic chart review of 700 AI-treated patients with stage I-III BC identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. SNP clusters that most closely defined AIA risk were discovered using an NAA that sequentially combined statistical filtering and a machine-learning algorithm. NCBI PhenGenI and Ensemble databases defined gene attribution of the most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Demographics were similar in cases and controls. A cluster of 70 SNPs, correlating to 57 genes, was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally consistent. Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Similarity-based search of model organism, disease and drug effect phenotypes

KAUST Repository

Hoehndorf, Robert; Gruenberger, Michael; Gkoutos, Georgios V; Schofield, Paul N

2015-01-01

Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions

Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Omics Analysis Tool for Clinical Phenotype Prediction.

Science.gov (United States)

Yu, Kun-Hsing; Fitzpatrick, Michael R; Pappas, Luke; Chan, Warren; Kung, Jessica; Snyder, Michael

2017-09-12

Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general-purpose data-mining tool exists for physicians, medical researchers, and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data, and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including mesothelioma and adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans. This web-based tool is available at http://tinyurl.com/oasispro ;source codes are available at http://tinyurl.com/oasisproSourceCode . © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Phenotypic and Functional Changes Induced in Hematopoietic Stem/Progenitor Cells After Gamma-Ray Radiation Exposure

Energy Technology Data Exchange (ETDEWEB)

Simonnet, A.J.; Nehme, J.; Leboulch, Ph.; Tronik-Le Roux, D. [Institute of Emerging Diseases and Innovative Therapies, Functional Bioengineering Laboratory, Commissariat a l' Energie Atomique (CEA), Evry (France); Simonnet, A.J.; Nehme, J.; Leboulch, Ph.; Tronik-Le Roux, D. [Institut National de la Sante et de la Recherche Medicale (INSERM) U733 (Unite Mixte de Recherche) - UMR INSERM CEA Paris XI (France); Vaigot, P. [Institute of Cellular and Molecular Radiation Biology, Department of Genetic Instability, Recombination and Repair, Commissariat a l' Energie Atomique, Fontenay-aux-Roses (France); Vaigot, P. [UMR 217, UMR-CEA-Centre National de la Recherche Scientifique (France); Barroca, V. [Laboratory of Gametogenesis, Apoptosis, Genotoxicity, Institute of Cellular and Molecular Radiation Biology, Commissariat a l' Energie Atomique, Fontenay-aux-Roses (France); Barroca, V. [Institut National de la Sante et de la Recherche Medicale U566 - UMR INSERM-CEA-PARIS VII (France); Leboulch, Ph. [Genetics Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts (US)

2009-07-01

Ionizing radiation (IR) exposure causes rapid and acute bone marrow (BM) suppression that is reversible for nonlethal doses. Evidence is accumulating that IR can also provoke long-lasting residual hematopoietic injury. To better understand these effects, we analyzed phenotypic and functional changes in the stem/progenitor compartment of irradiated mice over a 10-week period. We found that hematopoietic stem cells (HSCs) identified by their repopulating ability continued to segregate within the Hoechst dye excluding 'side population (SP)' early after IR exposure. However, transient phenotypic changes were observed within this cell population: Sca-1 (S) and c-Kit (K) expression levels were increased and severely reduced, respectively, with a concurrent increase in the proportion of SPSK cells positive for established indicators of the presence of HSCs: CD150 and CD105. Ten weeks after IR exposure, expression of Sca-1 and c-Kit at the SP cell surface returned to control levels, and BM cellularity of irradiated mice was restored. However, the c-Kit{sup +}Sca-1{sup +}Lin{sup -/low} (KSL) stem/progenitor compartment displayed major phenotypic modifications, including an increase and a severe decrease in the frequencies of CD150{sup +}Flk2{sup -} and CD150{sup -}Flk2{sup +} cells, respectively. CD150{sup +} KSL cells also showed impaired reconstituting ability, an increased tendency to apoptosis, and accrued DNA damage. Finally, 15 weeks after exposure, irradiated mice, but not age matched controls, allowed engraftment and significant hematopoietic contribution from transplanted con-genic HSCs without additional host conditioning. These results provide novel insight in our understanding of immediate and delayed IR-induced hematopoietic injury and highlight similarities between HSCs of young irradiated and old mice. (authors)

Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis.

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Bos, L D; Schouten, L R; van Vught, L A; Wiewel, M A; Ong, D S Y; Cremer, O; Artigas, A; Martin-Loeches, I; Hoogendijk, A J; van der Poll, T; Horn, J; Juffermans, N; Calfee, C S; Schultz, M J

2017-10-01

We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Two phenotypes were identified in 454 patients, which we named 'uninflamed' (N=218) and 'reactive' (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The 'reactive phenotype' was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31). Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please

Predicting functional decline and survival in amyotrophic lateral sclerosis.

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Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

2017-01-01

Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

Protein function prediction using neighbor relativity in protein-protein interaction network.

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Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

How Phenotypic Screening Influenced Drug Discovery: Lessons from Five Years of Practice.

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Haasen, Dorothea; Schopfer, Ulrich; Antczak, Christophe; Guy, Chantale; Fuchs, Florian; Selzer, Paul

Since 2011, phenotypic screening has been a trend in the pharmaceutical industry as well as in academia. This renaissance was triggered by analyses that suggested that phenotypic screening is a superior strategy to discover first-in-class drugs. Despite these promises and considerable investments, pharmaceutical research organizations have encountered considerable challenges with the approach. Few success stories have emerged in the past 5 years and companies are questioning their investment in this area. In this contribution, we outline what we have learned about success factors and challenges of phenotypic screening. We then describe how our efforts in phenotypic screening have influenced our approach to drug discovery in general. We predict that concepts from phenotypic screening will be incorporated into target-based approaches and will thus remain influential beyond the current trend.

Similarity-based search of model organism, disease and drug effect phenotypes

KAUST Repository

Hoehndorf, Robert

2015-02-19

Background: Semantic similarity measures over phenotype ontologies have been demonstrated to provide a powerful approach for the analysis of model organism phenotypes, the discovery of animal models of human disease, novel pathways, gene functions, druggable therapeutic targets, and determination of pathogenicity. Results: We have developed PhenomeNET 2, a system that enables similarity-based searches over a large repository of phenotypes in real-time. It can be used to identify strains of model organisms that are phenotypically similar to human patients, diseases that are phenotypically similar to model organism phenotypes, or drug effect profiles that are similar to the phenotypes observed in a patient or model organism. PhenomeNET 2 is available at http://aber-owl.net/phenomenet. Conclusions: Phenotype-similarity searches can provide a powerful tool for the discovery and investigation of molecular mechanisms underlying an observed phenotypic manifestation. PhenomeNET 2 facilitates user-defined similarity searches and allows researchers to analyze their data within a large repository of human, mouse and rat phenotypes.

A Regulatory RNA Inducing Transgenerationally Inherited Phenotypes

DEFF Research Database (Denmark)

Jensen, Lea Møller

. The variation in Arabidopsis enables different regulatory networks and mechanisms to shape the phenotypic characteristics. The thesis describes the identification of regulatory RNA encoded by an enzyme encoding gene. The RNA regulates by inducing transgenerationally inherited phenotypes. The function of the RNA...... is dependent on the genetic background illustrating that polymorphisms are found in either interactors or target genes of the RNA. Furthermore, the RNA provides a mechanistic link between accumulation of glucosinolate and onset of flowering....

A Bystander Mechanism Explains the Specific Phenotype of a Broadly Expressed Misfolded Protein.

Directory of Open Access Journals (Sweden)

Lauren Klabonski

2016-12-01

Full Text Available Misfolded proteins in transgenic models of conformational diseases interfere with proteostasis machinery and compromise the function of many structurally and functionally unrelated metastable proteins. This collateral damage to cellular proteins has been termed 'bystander' mechanism. How a single misfolded protein overwhelms the proteostasis, and how broadly-expressed mutant proteins cause cell type-selective phenotypes in disease are open questions. We tested the gain-of-function mechanism of a R37C folding mutation in an endogenous IGF-like C.elegans protein DAF-28. DAF-28(R37C is broadly expressed, but only causes dysfunction in one specific neuron, ASI, leading to a distinct developmental phenotype. We find that this phenotype is caused by selective disruption of normal biogenesis of an unrelated endogenous protein, DAF-7/TGF-β. The combined deficiency of DAF-28 and DAF-7 biogenesis, but not of DAF-28 alone, explains the gain-of-function phenotype-deficient pro-growth signaling by the ASI neuron. Using functional, fluorescently-tagged protein, we find that, in animals with mutant DAF-28/IGF, the wild-type DAF-7/TGF-β is mislocalized to and accumulates in the proximal axon of the ASI neuron. Activation of two different branches of the unfolded protein response can modulate both the developmental phenotype and DAF-7 mislocalization in DAF-28(R37C animals, but appear to act through divergent mechanisms. Our finding that bystander targeting of TGF-β explains the phenotype caused by a folding mutation in an IGF-like protein suggests that, in conformational diseases, bystander misfolding may specify the distinct phenotypes caused by different folding mutations.

Renal F4/80+ CD11c+ mononuclear phagocytes display phenotypic and functional characteristics of macrophages in health and in adriamycin nephropathy.

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Cao, Qi; Wang, Yiping; Wang, Xin Maggie; Lu, Junyu; Lee, Vincent W S; Ye, Qianling; Nguyen, Hanh; Zheng, Guoping; Zhao, Ye; Alexander, Stephen I; Harris, David C H

2015-02-01

Conventional markers of macrophages (Mфs) and dendritic cells (DCs) lack specificity and often overlap, leading to confusion and controversy regarding the precise function of these cells in kidney and other diseases. This study aimed to identify the phenotype and function of renal mononuclear phagocytes (rMPs) expressing key markers of both Mфs and DCs. F4/80(+)CD11c(+) cells accounted for 45% of total rMPs in normal kidneys and in those from mice with Adriamycin nephropathy (AN). Despite expression of the DC marker CD11c, these double-positive rMPs displayed the features of Mфs, including Mф-like morphology, high expression of CD68, CD204, and CD206, and high phagocytic ability but low antigen-presenting ability. F4/80(+)CD11c(+) cells were found in the cortex but not in the medulla of the kidney. In AN, F4/80(+)CD11c(+) cells displayed an M1 Mф phenotype with high expression of inflammatory mediators and costimulatory factors. Adoptive transfer of F4/80(+)CD11c(+) cells separated from diseased kidney aggravated renal injury in AN mice. Furthermore, adoptive transfer of common progenitors revealed that kidney F4/80(+)CD11c(+) cells were derived predominantly from monocytes, but not from pre-DCs. In conclusion, renal F4/80(+)CD11c(+) cells are a major subset of rMPs and display Mф-like phenotypic and functional characteristics in health and in AN. Copyright © 2015 by the American Society of Nephrology.

Genomic Prediction of Manganese Efficiency in Winter Barley

Directory of Open Access Journals (Sweden)

Florian Leplat

2016-07-01

Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.

Weaknesses in executive functioning predict the initiating of adolescents' alcohol use.

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Peeters, Margot; Janssen, Tim; Monshouwer, Karin; Boendermaker, Wouter; Pronk, Thomas; Wiers, Reinout; Vollebergh, Wilma

2015-12-01

Recently, it has been suggested that impairments in executive functioning might be risk factors for the onset of alcohol use rather than a result of heavy alcohol use. In the present study, we examined whether two aspects of executive functioning, working memory and response inhibition, predicted the first alcoholic drink and first binge drinking episode in young adolescents using discrete survival analyses. Adolescents were selected from several Dutch secondary schools including both mainstream and special education (externalizing behavioral problems). Participants were 534 adolescents between 12 and 14 years at baseline. Executive functioning and alcohol use were assessed four times over a period of two years. Working memory uniquely predicted the onset of first drink (p=.01) and first binge drinking episode (p=.04) while response inhibition only uniquely predicted the initiating of the first drink (p=.01). These results suggest that the association of executive functioning and alcohol consumption found in former studies cannot simply be interpreted as an effect of alcohol consumption, as weaknesses in executive functioning, found in alcohol naïve adolescents, predict the initiating of (binge) drinking. Though, prolonged and heavy alcohol use might further weaken already existing deficiencies. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Association Between the Probability of Autism Spectrum Disorder and Normative Sex-Related Phenotypic Diversity in Brain Structure

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Andrews, Derek S.; Gudbrandsen, Christina M.; Marquand, Andre F.; Ginestet, Cedric E.; Daly, Eileen M.; Murphy, Clodagh M.; Lai, Meng-Chuan; Lombardo, Michael V.; Ruigrok, Amber N. V.; Bullmore, Edward T.; Suckling, John; Williams, Steven C. R.; Baron-Cohen, Simon; Craig, Michael C.; Murphy, Declan G. M.

2017-01-01

Importance Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive. Objectives To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD. Design, Setting, and Participants This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016. Main Outcomes and Measures Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals. Results Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For

Cyclic hydrostatic pressure promotes a stable cartilage phenotype and enhances the functional development of cartilaginous grafts engineered using multipotent stromal cells isolated from bone marrow and infrapatellar fat pad.

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Carroll, S F; Buckley, C T; Kelly, D J

2014-06-27

The objective of this study was to investigate how joint specific biomechanical loading influences the functional development and phenotypic stability of cartilage grafts engineered in vitro using stem/progenitor cells isolated from different source tissues. Porcine bone marrow derived multipotent stromal cells (BMSCs) and infrapatellar fat pad derived multipotent stromal cells (FPSCs) were seeded in agarose hydrogels and cultured in chondrogenic medium, while simultaneously subjected to 10MPa of cyclic hydrostatic pressure (HP). To mimic the endochondral phenotype observed in vivo with cartilaginous tissues engineered using BMSCs, the culture media was additionally supplemented with hypertrophic factors, while the loss of phenotype observed in vivo with FPSCs was induced by withdrawing transforming growth factor (TGF)-β3 from the media. The application of HP was found to enhance the functional development of cartilaginous tissues engineered using both BMSCs and FPSCs. In addition, HP was found to suppress calcification of tissues engineered using BMSCs cultured in chondrogenic conditions and acted to maintain a chondrogenic phenotype in cartilaginous grafts engineered using FPSCs. The results of this study point to the importance of in vivo specific mechanical cues for determining the terminal phenotype of chondrogenically primed multipotent stromal cells. Furthermore, demonstrating that stem or progenitor cells will appropriately differentiate in response to such biophysical cues might also be considered as an additional functional assay for evaluating their therapeutic potential. Copyright © 2013 Elsevier Ltd. All rights reserved.

PhenoTips: patient phenotyping software for clinical and research use.

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Girdea, Marta; Dumitriu, Sergiu; Fiume, Marc; Bowdin, Sarah; Boycott, Kym M; Chénier, Sébastien; Chitayat, David; Faghfoury, Hanna; Meyn, M Stephen; Ray, Peter N; So, Joyce; Stavropoulos, Dimitri J; Brudno, Michael

2013-08-01

We have developed PhenoTips: open source software for collecting and analyzing phenotypic information for patients with genetic disorders. Our software combines an easy-to-use interface, compatible with any device that runs a Web browser, with a standardized database back end. The PhenoTips' user interface closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. Collected data include demographics, medical history, family history, physical and laboratory measurements, physical findings, and additional notes. Phenotypic information is represented using the Human Phenotype Ontology; however, the complexity of the ontology is hidden behind a user interface, which combines simple selection of common phenotypes with error-tolerant, predictive search of the entire ontology. PhenoTips supports accurate diagnosis by analyzing the entered data, then suggesting additional clinical investigations and providing Online Mendelian Inheritance in Man (OMIM) links to likely disorders. By collecting, classifying, and analyzing phenotypic information during the patient encounter, PhenoTips allows for streamlining of clinic workflow, efficient data entry, improved diagnosis, standardization of collected patient phenotypes, and sharing of anonymized patient phenotype data for the study of rare disorders. Our source code and a demo version of PhenoTips are available at http://phenotips.org. © 2013 WILEY PERIODICALS, INC.

Dynamic prediction of cumulative incidence functions by direct binomial regression.

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Grand, Mia K; de Witte, Theo J M; Putter, Hein

2018-03-25

In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights. We extend the approach by combining it with landmarking to enable dynamic prediction of the cumulative incidence function. The proposed models are very flexible, as they allow the covariates to have complex time-varying effects, and we illustrate how to investigate possible time-varying structures using Wald tests. The models are fitted using generalized estimating equations. The method is applied to bone marrow transplant data and the performance is investigated in a simulation study. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

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Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural

Evaluation of the genotypic prediction of HIV-1 coreceptor use versus a phenotypic assay and correlation with the virological response to maraviroc: the ANRS GenoTropism study.

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Recordon-Pinson, Patricia; Soulié, Cathia; Flandre, Philippe; Descamps, Diane; Lazrek, Mouna; Charpentier, Charlotte; Montes, Brigitte; Trabaud, Mary-Anne; Cottalorda, Jacqueline; Schneider, Véronique; Morand-Joubert, Laurence; Tamalet, Catherine; Desbois, Delphine; Macé, Muriel; Ferré, Virginie; Vabret, Astrid; Ruffault, Annick; Pallier, Coralie; Raymond, Stéphanie; Izopet, Jacques; Reynes, Jacques; Marcelin, Anne-Geneviève; Masquelier, Bernard

2010-08-01

Genotypic algorithms for prediction of HIV-1 coreceptor usage need to be evaluated in a clinical setting. We aimed at studying (i) the correlation of genotypic prediction of coreceptor use in comparison with a phenotypic assay and (ii) the relationship between genotypic prediction of coreceptor use at baseline and the virological response (VR) to a therapy including maraviroc (MVC). Antiretroviral-experienced patients were included in the MVC Expanded Access Program if they had an R5 screening result with Trofile (Monogram Biosciences). V3 loop sequences were determined at screening, and coreceptor use was predicted using 13 genotypic algorithms or combinations of algorithms. Genotypic predictions were compared to Trofile; dual or mixed (D/M) variants were considered as X4 variants. Both genotypic and phenotypic results were obtained for 189 patients at screening, with 54 isolates scored as X4 or D/M and 135 scored as R5 with Trofile. The highest sensitivity (59.3%) for detection of X4 was obtained with the Geno2pheno algorithm, with a false-positive rate set up at 10% (Geno2pheno10). In the 112 patients receiving MVC, a plasma viral RNA load of <50 copies/ml was obtained in 68% of cases at month 6. In multivariate analysis, the prediction of the X4 genotype at baseline with the Geno2pheno10 algorithm including baseline viral load and CD4 nadir was independently associated with a worse VR at months 1 and 3. The baseline weighted genotypic sensitivity score was associated with VR at month 6. There were strong arguments in favor of using genotypic coreceptor use assays for determining which patients would respond to CCR5 antagonist.

Macrophage Phenotypes Regulate Scar Formation and Chronic Wound Healing.

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Hesketh, Mark; Sahin, Katherine B; West, Zoe E; Murray, Rachael Z

2017-07-17

Macrophages and inflammation play a beneficial role during wound repair with macrophages regulating a wide range of processes, such as removal of dead cells, debris and pathogens, through to extracellular matrix deposition re-vascularisation and wound re-epithelialisation. To perform this range of functions, these cells develop distinct phenotypes over the course of wound healing. They can present with a pro-inflammatory M1 phenotype, more often found in the early stages of repair, through to anti-inflammatory M2 phenotypes that are pro-repair in the latter stages of wound healing. There is a continuum of phenotypes between these ranges with some cells sharing phenotypes of both M1 and M2 macrophages. One of the less pleasant consequences of quick closure, namely the replacement with scar tissue, is also regulated by macrophages, through their promotion of fibroblast proliferation, myofibroblast differentiation and collagen deposition. Alterations in macrophage number and phenotype disrupt this process and can dictate the level of scar formation. It is also clear that dysregulated inflammation and altered macrophage phenotypes are responsible for hindering closure of chronic wounds. The review will discuss our current knowledge of macrophage phenotype on the repair process and how alterations in the phenotypes might alter wound closure and the final repair quality.

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H)

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Boezeman, Edwin J.; Nieuwenhuijsen, Karen; Sluiter, Judith K.

2016-01-01

Objectives: To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Methods: Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. Results: The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (pvalue and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers. PMID:27010085

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

Science.gov (United States)

Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

2016-05-25

To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (ppredictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping.

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Durand, Jean-Baptiste; Allard, Alix; Guitton, Baptiste; van de Weg, Eric; Bink, Marco C A M; Costes, Evelyne

2017-01-01

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

Phenotypically and functionally distinct CD8+ lymphocyte populations in long-term drug-free tolerance and chronic rejection in human kidney graft recipients

NARCIS (Netherlands)

Baeten, Dominique; Louis, Stéphanie; Braud, Christophe; Braudeau, Cécile; Ballet, Caroline; Moizant, Frédéric; Pallier, Annaik; Giral, Magali; Brouard, Sophie; Soulillou, Jean-Paul

2006-01-01

A substantial proportion of long-term kidney graft recipients, including those with a stable renal function in the absence of immunosuppressive therapy, present a skewed T cell receptor (TCR) Vbeta chain usage, essentially in the CD8+ subset. This study analyzed in more detail phenotypical and

Ortholog prediction of the Aspergillus genus applicable for synthetic biology

DEFF Research Database (Denmark)

Rasmussen, Jane Lind Nybo; Vesth, Tammi Camilla; Theobald, Sebastian

of genotype-to-phenotype. To achieve this, we have developed orthologous protein prediction software that utilizes genus-wide genetic diversity. The approach is optimized for large data sets, based on BLASTp considering protein identity and alignment coverage, and clustering using single linkage of bi......The Aspergillus genus contains leading industrial microorganisms, excelling in producing bioactive compounds and enzymes. Using synthetic biology and bioinformatics, we aim to re-engineer these organisms for applications within human health, pharmaceuticals, environmental engineering, and food......-directional hits. The result is orthologous protein families describing the genomic and functional features of individual species, clades and the core/pan genome of Aspergillus; and applicable to genotype-to-phenotype analyses in other microbial genera....

Distinct genetic architectures for phenotype means and plasticities in Zea mays.

Science.gov (United States)

Kusmec, Aaron; Srinivasan, Srikant; Nettleton, Dan; Schnable, Patrick S

2017-09-01

Phenotypic plasticity describes the phenotypic variation of a trait when a genotype is exposed to different environments. Understanding the genetic control of phenotypic plasticity in crops such as maize is of paramount importance for maintaining and increasing yields in a world experiencing climate change. Here, we report the results of genome-wide association analyses of multiple phenotypes and two measures of phenotypic plasticity in a maize nested association mapping (US-NAM) population grown in multiple environments and genotyped with ~2.5 million single-nucleotide polymorphisms. We show that across all traits the candidate genes for mean phenotype values and plasticity measures form structurally and functionally distinct groups. Such independent genetic control suggests that breeders will be able to select semi-independently for mean phenotype values and plasticity, thereby generating varieties with both high mean phenotype values and levels of plasticity that are appropriate for the target performance environments.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

International Nuclear Information System (INIS)

Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

2016-01-01

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

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Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

2016-02-15

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

Functional modules, mutational load and human genetic disease.

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Zaghloul, Norann A; Katsanis, Nicholas

2010-04-01

The ability to generate a massive amount of sequencing and genotyping data is transforming the study of human genetic disorders. Driven by such innovation, it is likely that whole exome and whole-genome resequencing will replace regionally focused approaches for gene discovery and clinical testing in the next few years. However, this opportunity brings a significant interpretative challenge to assigning function and phenotypic variance to common and rare alleles. Understanding the effect of individual mutations in the context of the remaining genomic variation represents a major challenge to our interpretation of disease. Here, we discuss the challenges of assigning mutation functionality and, drawing from the examples of ciliopathies as well as cohesinopathies and channelopathies, discuss possibilities for the functional modularization of the human genome. Functional modularization in addition to the development of physiologically relevant assays to test allele functionality will accelerate our understanding of disease architecture and enable the use of genome-wide sequence data for disease diagnosis and phenotypic prediction in individuals. Copyright 2010 Elsevier Ltd. All rights reserved.

Study the Relationship of Executive Functions with Behavioral Symptoms in Children with High-Functioning Autism

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Vali Shiri

2015-10-01

Full Text Available Objective: The relation between autism disorder’s symptoms and cognitive capabilities can help with a better phenotype description of this disorder and can facilitate its pathological evaluation and treatment. Destruction of executive functions seems to be one of the cognitive reasons of potential phenotype in autism disorder. Thus, the present paper aims to study the relationship between executive dysfunction and autism disorder’s symptoms. Materials & Methods: In this cross-sectional research, 50 children with high-functioning autism were selected using convenience sampling method from Behara, Tehranpars and Roshd centers. Then, the GARS test and Autism Spectrum Screening Questionnaire was completed by therapists and neuropsychological tests of Strop and continuous performance test and shift attention were taken by the subjects. Pearson correlation coefficient and multi-variant regression were used for data analysis. Results: There is a significant positive relationship between selective attention with communicative and social interaction symptoms, sustained attention with social interaction symptoms and repetitive behaviors, shifting attention with communicative, social interaction and repetitive behavior symptoms (P<0.001 (P<0.01 (P<0.05. In addition, the results of regression analysis also revealed that selective attention and shifting attention can predict communication, and sustained attention can predict social interaction and repetitive behaviors symptoms (P<0.01 (P<0.05. Conclusion: The results obtained by this study indicate the significant role of executive functions in autistic symptoms. Thus, it is recommended to consider new treatment interventions in repairing executive functions for treatment of children with autistic disorder.

Evidence for a Broad Autism Phenotype

NARCIS (Netherlands)

K. de Groot (Kristel); J.W. van Strien (Jan)

2017-01-01

textabstractThe broad autism phenotype implies the existence of a continuum ranging from individuals displaying almost no autistic traits to severely impaired diagnosed individuals. Recent studies have linked this variation in autistic traits to several domains of functioning. However, studies

Improving acute kidney injury diagnostics using predictive analytics.

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Basu, Rajit K; Gist, Katja; Wheeler, Derek S

2015-12-01

Acute kidney injury (AKI) is a multifactorial syndrome affecting an alarming proportion of hospitalized patients. Although early recognition may expedite management, the ability to identify patients at-risk and those suffering real-time injury is inconsistent. The review will summarize the recent reports describing advancements in the area of AKI epidemiology, specifically focusing on risk scoring and predictive analytics. In the critical care population, the primary underlying factors limiting prediction models include an inability to properly account for patient heterogeneity and underperforming metrics used to assess kidney function. Severity of illness scores demonstrate limited AKI predictive performance. Recent evidence suggests traditional methods for detecting AKI may be leveraged and ultimately replaced by newer, more sophisticated analytical tools capable of prediction and identification: risk stratification, novel AKI biomarkers, and clinical information systems. Additionally, the utility of novel biomarkers may be optimized through targeting using patient context, and may provide more granular information about the injury phenotype. Finally, manipulation of the electronic health record allows for real-time recognition of injury. Integrating a high-functioning clinical information system with risk stratification methodology and novel biomarker yields a predictive analytic model for AKI diagnostics.

Improved survival prediction from lung function data in a large population sample

DEFF Research Database (Denmark)

Miller, M.R.; Pedersen, O.F.; Lange, P.

2008-01-01

Studies relating tung function to survival commonly express lung function impairment as a percent of predicted but this retains age, height and sex bias. We have studied alternative methods of expressing forced expiratory volume in 1 s (FEV1) for predicting all cause and airway related lung disease.......1 respectively. Cut levels of lung function were used to categorise impairment and the HR for multivariate prediction of all cause and airway related lung disease mortality were 10 and 2044 respectively for the worst category of FEV1/ht(2) compared to 5 and 194 respectively for the worst category of FEV1PP....... In univariate predictions of all cause mortality the HR for FEV1/ht(2) categories was 2-4 times higher than those for FEV1PP and 3-10 times higher for airway related tung disease mortality. We conclude that FEV1/ht(2) is superior to FEV1PP for predicting survival. in a general population and this method...

Intraspecific variation in flight metabolic rate in the bumblebee Bombus impatiens: repeatability and functional determinants in workers and drones.

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Darveau, Charles-A; Billardon, Fannie; Bélanger, Kasandra

2014-02-15

The evolution of flight energetics requires that phenotypes be variable, repeatable and heritable. We studied intraspecific variation in flight energetics in order to assess the repeatability of flight metabolic rate and wingbeat frequency, as well as the functional basis of phenotypic variation in workers and drones of the bumblebee species Bombus impatiens. We showed that flight metabolic rate and wingbeat frequency were highly repeatable in workers, even when controlling for body mass variation using residual analysis. We did not detect significant repeatability in drones, but a smaller range of variation might have prevented us from finding significant values in our sample. Based on our results and previous findings, we associated the high repeatability of flight phenotypes in workers to the functional links between body mass, thorax mass, wing size, wingbeat frequency and metabolic rate. Moreover, differences between workers and drones were as predicted from these functional associations, where drones had larger wings for their size, lower wingbeat frequency and lower flight metabolic rate. We also investigated thoracic muscle metabolic phenotypes by measuring the activity of carbohydrate metabolism enzymes, and we found positive correlations between mass-independent metabolic rate and the activity of all enzymes measured, but in workers only. When comparing workers and drones that differ in flight metabolic rate, only the activity of the enzymes hexokinase and trehalase showed the predicted differences. Overall, our study indicates that there should be correlated evolution among physiological phenotypes at multiple levels of organization and morphological traits associated with flight.

Do functional tests predict low back pain?

Science.gov (United States)

Takala, E P; Viikari-Juntura, E

2000-08-15

A cohort of 307 nonsymptomatic workers and another cohort of 123 workers with previous episodes of low back pain were followed up for 2 years. The outcomes were measured by symptoms, medical consultations, and sick leaves due to low back disorders. To study the predictive value of a set of tests measuring the physical performance of the back in a working population. The hypothesis was that subjects with poor functional capacity are liable to back disorders. Reduced functional performance has been associated with back pain. There are few data to show whether reduced functional capacity is a cause or a consequence of pain. Mobility of the trunk in forward and side bending, maximal isokinetic trunk extension, flexion and lifting strength, and static endurance of back extension were measured. Standing balance and foot reaction time were recorded with a force plate. Clinical tests for the provocation of back or leg pain were performed. Gender, workload, age, and anthropometrics were managed as potential confounders in the analysis. Marked overlapping was seen in the measures of the subjects with different outcomes. Among the nonsymptomatic subjects, low performance in tests of mobility and standing balance was associated with future back disorders. Among workers with previous episodes of back pain, low isokinetic extension strength, poor standing balance, and positive clinical signs predicted future pain. Some associations were found between the functional tests and future low back pain. The wide variation in the results questions the value of the tests in health examinations (e.g., in screening or surveillance of low back disorders).

Clinical spectrum and genotype-phenotype associations of KCNA2-related encephalopathies.

Science.gov (United States)

Masnada, Silvia; Hedrich, Ulrike B S; Gardella, Elena; Schubert, Julian; Kaiwar, Charu; Klee, Eric W; Lanpher, Brendan C; Gavrilova, Ralitza H; Synofzik, Matthis; Bast, Thomas; Gorman, Kathleen; King, Mary D; Allen, Nicholas M; Conroy, Judith; Ben Zeev, Bruria; Tzadok, Michal; Korff, Christian; Dubois, Fanny; Ramsey, Keri; Narayanan, Vinodh; Serratosa, Jose M; Giraldez, Beatriz G; Helbig, Ingo; Marsh, Eric; O'Brien, Margaret; Bergqvist, Christina A; Binelli, Adrian; Porter, Brenda; Zaeyen, Eduardo; Horovitz, Dafne D; Wolff, Markus; Marjanovic, Dragan; Caglayan, Hande S; Arslan, Mutluay; Pena, Sergio D J; Sisodiya, Sanjay M; Balestrini, Simona; Syrbe, Steffen; Veggiotti, Pierangelo; Lemke, Johannes R; Møller, Rikke S; Lerche, Holger; Rubboli, Guido

2017-09-01

Recently, de novo mutations in the gene KCNA2, causing either a dominant-negative loss-of-function or a gain-of-function of the voltage-gated K+ channel Kv1.2, were described to cause a new molecular entity within the epileptic encephalopathies. Here, we report a cohort of 23 patients (eight previously described) with epileptic encephalopathy carrying either novel or known KCNA2 mutations, with the aim to detail the clinical phenotype associated with each of them, to characterize the functional effects of the newly identified mutations, and to assess genotype-phenotype associations. We identified five novel and confirmed six known mutations, three of which recurred in three, five and seven patients, respectively. Ten mutations were missense and one was a truncation mutation; de novo occurrence could be shown in 20 patients. Functional studies using a Xenopus oocyte two-microelectrode voltage clamp system revealed mutations with only loss-of-function effects (mostly dominant-negative current amplitude reduction) in eight patients or only gain-of-function effects (hyperpolarizing shift of voltage-dependent activation, increased amplitude) in nine patients. In six patients, the gain-of-function was diminished by an additional loss-of-function (gain-and loss-of-function) due to a hyperpolarizing shift of voltage-dependent activation combined with either decreased amplitudes or an additional hyperpolarizing shift of the inactivation curve. These electrophysiological findings correlated with distinct phenotypic features. The main differences were (i) predominant focal (loss-of-function) versus generalized (gain-of-function) seizures and corresponding epileptic discharges with prominent sleep activation in most cases with loss-of-function mutations; (ii) more severe epilepsy, developmental problems and ataxia, and atrophy of the cerebellum or even the whole brain in about half of the patients with gain-of-function mutations; and (iii) most severe early-onset phenotypes

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

Science.gov (United States)

Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

2015-07-01

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

Directory of Open Access Journals (Sweden)

Douglas D Thompson

Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

Clinical and functional criteria for predicting asthma in infants

Directory of Open Access Journals (Sweden)

Yu. L. Mizemitskiy

2015-01-01

Full Text Available Objective: to determine clinical and functional criteria for predicting asthma in children who have sustained acute obstructive bronchitis in infancy. Subjects and methods. A total of 125 infants aged 2 to 36 months who had experienced 1 -2 episodes of acute obstructive bronchitis and treated at hospital were examined when bronchial obstruction syndrome was being relieved. In addition to physical examination, functional studies (computerized bronchophonography and heart rate variability assessment were used. Immunological examination included determination of the serum levels of immunoglobulin E and interleuMn-17A. The infants who had sustained acute obstructive bronchitis were followed up for 12-36 months. Results. The infants who had sustained acute obstructive bronchitis in the presence of mild perinatal CNS damage caused by hypoxia were typified by high respiratory morbidity; early-onset bronchial obstruction; long-term bronchial obstruction relief; high incidence of grade 2 respiratory failure in acute obstructive bronchitis. These patients developed asthma more often than twice and repeated episodes of bronchial obstruction. ROC analysis was used to elaborate clinical and functional criteria for predicting the development of asthma in infants. Conclusion. The proposed additional clinical and functional criteria characterizing external respiratory dysfunction and autonomic homeostatic changes contribute to the early diagnosis of asthma and substantially increase the validity of prediction of its development in children younger than 3 years, which is of great importance for goal-oriented preventive measures.

Phenotypes in defined genotypes including siblings with Usher syndrome.

Science.gov (United States)

Malm, Eva; Ponjavic, Vesna; Möller, Claes; Kimberling, William J; Andréasson, Sten

2011-06-01

To characterize visual function in defined genotypes including siblings with Usher syndrome. Thirteen patients with phenotypically different subtypes of Usher syndrome, including 3 families with affected siblings, were selected. Genetic analysis and ophthalmological examinations including visual fields, full-field electroretinography (ERG), multifocal electroretinography (mf ERG), and optical coherence tomography (OCT) were assessed. The patients' degree of visual handicap was evaluated by a questionnaire (ADL). Twelve of thirteen patients were genotyped as Usher 1B, 1D, 1F, 2A, 2C or 3A. In 12 of 13 patients examined with ERG the 30 Hz flickering light response revealed remaining cone function. In 3 of the patients with Usher type 1 mf ERG demonstrated a specific pattern, with a sharp distinction between the area with reduced function and the central area with remaining macular function and normal peak time. OCT demonstrated loss of foveal depression with distortion of the foveal architecture in the macula in all patients. The foveal thickness ranged from 159 to 384 µm and was not correlated to retinal function. Three siblings shared the same mutation for Usher 2C but in contrast to previous reports regarding this genotype, 1 of them diverged in phenotype with substantially normal visual fields, almost normal OCT and mf ERG findings, and only moderately reduced rod and cone function according to ERG. Evaluation of visual function comprising both the severity of the rod cone degeneration and the function in the macular region confirm phenotypical heterogeneity within siblings and between different genotypes of Usher syndrome.

Perichondrium phenotype and border function are regulated by Ext1 and heparan sulfate in developing long bones: a mechanism likely deranged in Hereditary Multiple Exostoses.

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Huegel, Julianne; Mundy, Christina; Sgariglia, Federica; Nygren, Patrik; Billings, Paul C; Yamaguchi, Yu; Koyama, Eiki; Pacifici, Maurizio

2013-05-01

During limb skeletogenesis the cartilaginous long bone anlagen and their growth plates become delimited by perichondrium with which they interact functionally. Yet, little is known about how, despite being so intimately associated with cartilage, perichondrium acquires and maintains its distinct phenotype and exerts its border function. Because perichondrium becomes deranged and interrupted by cartilaginous outgrowths in Hereditary Multiple Exostoses (HME), a pediatric disorder caused by EXT mutations and consequent heparan sulfate (HS) deficiency, we asked whether EXT genes and HS normally have roles in establishing its phenotype and function. Indeed, conditional Ext1 ablation in perichondrium and lateral chondrocytes flanking the epiphyseal region of mouse embryo long bone anlagen - a region encompassing the groove of Ranvier - caused ectopic cartilage formation. A similar response was observed when HS function was disrupted in long bone anlagen explants by genetic, pharmacological or enzymatic means, a response preceded by ectopic BMP signaling within perichondrium. These treatments also triggered excess chondrogenesis and cartilage nodule formation and overexpression of chondrogenic and matrix genes in limb bud mesenchymal cells in micromass culture. Interestingly, the treatments disrupted the peripheral definition and border of the cartilage nodules in such a way that many nodules overgrew and fused with each other into large amorphous cartilaginous masses. Interference with HS function reduced the physical association and interactions of BMP2 with HS and increased the cell responsiveness to endogenous and exogenous BMP proteins. In sum, Ext genes and HS are needed to establish and maintain perichondrium's phenotype and border function, restrain pro-chondrogenic signaling proteins including BMPs, and restrict chondrogenesis. Alterations in these mechanisms may contribute to exostosis formation in HME, particularly at the expense of regions rich in progenitor

FUNCTIONAL SUBCLONE PROFILING FOR PREDICTION OF TREATMENT-INDUCED INTRA-TUMOR POPULATION SHIFTS AND DISCOVERY OF RATIONAL DRUG COMBINATIONS IN HUMAN GLIOBLASTOMA

Science.gov (United States)

Reinartz, Roman; Wang, Shanshan; Kebir, Sied; Silver, Daniel J.; Wieland, Anja; Zheng, Tong; Küpper, Marius; Rauschenbach, Laurèl; Fimmers, Rolf; Shepherd, Timothy M.; Trageser, Daniel; Till, Andreas; Schäfer, Niklas; Glas, Martin; Hillmer, Axel M.; Cichon, Sven; Smith, Amy A.; Pietsch, Torsten; Liu, Ying; Reynolds, Brent A.; Yachnis, Anthony; Pincus, David W.; Simon, Matthias; Brüstle, Oliver; Steindler, Dennis A.; Scheffler, Björn

2016-01-01

Purpose Investigation of clonal heterogeneity may be key to understanding mechanisms of therapeutic failure in human cancer. However, little is known on the consequences of therapeutic intervention on the clonal composition of solid tumors. Experimental Design Here, we used 33 single cell-derived subclones generated from five clinical glioblastoma specimens for exploring intra- and inter-individual spectra of drug resistance profiles in vitro. In a personalized setting, we explored whether differences in pharmacological sensitivity among subclones could be employed to predict drug-dependent changes to the clonal composition of tumors. Results Subclones from individual tumors exhibited a remarkable heterogeneity of drug resistance to a library of potential anti-glioblastoma compounds. A more comprehensive intra-tumoral analysis revealed that stable genetic and phenotypic characteristics of co-existing subclones could be correlated with distinct drug sensitivity profiles. The data obtained from differential drug response analysis could be employed to predict clonal population shifts within the naïve parental tumor in vitro and in orthotopic xenografts. Furthermore, the value of pharmacological profiles could be shown for establishing rational strategies for individualized secondary lines of treatment. Conclusions Our data provide a previously unrecognized strategy for revealing functional consequences of intra-tumor heterogeneity by enabling predictive modeling of treatment-related subclone dynamics in human glioblastoma. PMID:27521447

Individualized performance prediction during total sleep deprivation: accounting for trait vulnerability to sleep loss.

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Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Thorsley, David; Wesensten, Nancy J; Balkin, Thomas J; Reifman, Jaques

2012-01-01

Individual differences in vulnerability to sleep loss can be considerable, and thus, recent efforts have focused on developing individualized models for predicting the effects of sleep loss on performance. Individualized models constructed using a Bayesian formulation, which combines an individual's available performance data with a priori performance predictions from a group-average model, typically need at least 40 h of individual data before showing significant improvement over the group-average model predictions. Here, we improve upon the basic Bayesian formulation for developing individualized models by observing that individuals may be classified into three sleep-loss phenotypes: resilient, average, and vulnerable. For each phenotype, we developed a phenotype-specific group-average model and used these models to identify each individual's phenotype. We then used the phenotype-specific models within the Bayesian formulation to make individualized predictions. Results on psychomotor vigilance test data from 48 individuals indicated that, on average, ∼85% of individual phenotypes were accurately identified within 30 h of wakefulness. The percentage improvement of the proposed approach in 10-h-ahead predictions was 16% for resilient subjects and 6% for vulnerable subjects. The trade-off for these improvements was a slight decrease in prediction accuracy for average subjects.

A Dual Phenotype of Periventricular Nodular Heterotopia and Frontometaphyseal Dysplasia in One Patient Caused by a Single FLNA Mutation Leading to Two Functionally Different Aberrant Transcripts

Science.gov (United States)

Zenker, Martin; Rauch, Anita; Winterpacht, Andreas; Tagariello, Andreas; Kraus, Cornelia; Rupprecht, Thomas; Sticht, Heinrich; Reis, André

2004-01-01

Two disorders, periventricular nodular heterotopia (PVNH) and a group of skeletal dysplasias belonging to the oto-palato-digital (OPD) spectrum, are caused by FLNA mutations. They are considered mutually exclusive because of the different presumed effects of the respective FLNA gene mutations, leading to loss of function (PVNH) and gain of function (OPD), respectively. We describe here the first patient manifesting PVNH in combination with frontometaphyseal dysplasia, a skeletal dysplasia of the OPD-spectrum. A novel de novo mutation, 7315C→A in exon 45 of the FLNA gene, was identified. It leads to two aberrant transcripts, one full-length transcript with the point mutation causing a substitution of a highly conserved leucine residue (L2439M) and a second shortened transcript lacking 21 bp due to the creation of an ectopic splice donor site in exon 45. We propose that the dual phenotype is caused by two functionally different, aberrant filamin A proteins and therefore represents an exceptional model case of allelic gain-of-function and loss-of-function phenotypes due to a single mutational event. PMID:14988809

A mathematical model of cancer cells with phenotypic plasticity

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Da Zhou

2015-12-01

Full Text Available Purpose: The phenotypic plasticity of cancer cells is recently becoming a cutting-edge research area in cancer, which challenges the cellular hierarchy proposed by the conventional cancer stem cell theory. In this study, we establish a mathematical model for describing the phenotypic plasticity of cancer cells, based on which we try to find some salient features that can characterize the dynamic behavior of the phenotypic plasticity especially in comparison to the hierarchical model of cancer cells. Methods: We model cancer as population dynamics composed of different phenotypes of cancer cells. In this model, not only can cancer cells divide (symmetrically and asymmetrically and die, but they can also convert into other cellular phenotypes. According to the Law of Mass Action, the cellular processes can be captured by a system of ordinary differential equations (ODEs. On one hand, we can analyze the long-term stability of the model by applying qualitative method of ODEs. On the other hand, we are also concerned about the short-term behavior of the model by studying its transient dynamics. Meanwhile, we validate our model to the cell-state dynamics in published experimental data.Results: Our results show that the phenotypic plasticity plays important roles in both stabilizing the distribution of different phenotypic mixture and maintaining the cancer stem cells proportion. In particular, the phenotypic plasticity model shows decided advantages over the hierarchical model in predicting the phenotypic equilibrium and cancer stem cells’ overshoot reported in previous biological experiments in cancer cell lines.Conclusion: Since the validity of the phenotypic plasticity paradigm and the conventional cancer stem cell theory is still debated in experimental biology, it is worthy of theoretically searching for good indicators to distinguish the two models through quantitative methods. According to our study, the phenotypic equilibrium and overshoot

Prediction of postoperative respiratory function of lung cancer patients using 99mTc-MAA SPECT

International Nuclear Information System (INIS)

Kokubo, Mitsuharu; Sakai, Satoshi; Miyata, Tomoyuki

1991-01-01

In this study, we evaluated the correlation between the predicted postoperative respiratory function using 99m Tc-MAA SPECT with chest CT and the postoperative respiratory function. 99m Tc-MAA SPECT were performed in 10 patients with lung cancer who underwent lobectomy. We measured the fractional loss in the pulmonary flow of the lobe to be resected using 99m Tc-MAA SPECT with chest CT. The value of predicted postoperative respiratory function was measured as follows: the value of predicted postoperative respiratory function=the value of preoperative respiratory function x (1-the fractional loss in the pulmonary flow of the lobe to be resected). Postoperative forced vital capacity (FVC), forced expiratory volume in the first second (FEV 1.0 ) and % vital capacity (%VC) were predicted in this study, and were compared to the respiratory function at three months and six months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function. (author)

Protein change in plant evolution: tracing one thread connecting molecular and phenotypic diversity

Directory of Open Access Journals (Sweden)

Madelaine eBartlett

2013-10-01

Full Text Available Proteins change over the course of evolutionary time. New protein-coding genes and gene families emerge and diversify, ultimately affecting an organism’s phenotype and interactions with its environment. Here we survey the range of structural protein change observed in plants and review the role these changes have had in the evolution of plant form and function. Verified examples tying evolutionary change in protein structure to phenotypic change remain scarce. We will review the existing examples, as well as draw from investigations into domestication, and quantitative trait locus (QTL cloning studies searching for the molecular underpinnings of natural variation. The evolutionary significance of many cloned QTL has not been assessed, but all the examples identified so far have begun to reveal the extent of protein structural diversity tolerated in natural systems. This molecular (and phenotypic diversity could come to represent part of natural selection’s source material in the adaptive evolution of novel traits. Protein structure and function can change in many distinct ways, but the changes we identified in studies of natural diversity and protein evolution were predicted to fall primarily into one of six categories: altered active and binding sites; hypomorphic and hypermorphic alleles; altered protein-protein interactions; altered domain content; altered protein stability; and altered activity as an activator or repressor. Variability was also observed in the evolutionary scale at which particular changes were observed. Some changes were detected at both micro- and macroevolutionary timescales, while others were observed primarily at deep or shallow phylogenetic levels. This variation might be used to determine the trajectory of future investigations in structural molecular evolution.

NF1 Neuronal Genotype Phenotype Relationships

Science.gov (United States)

2017-06-01

interesting results from the Drosophila functional assays, at present we have decided to focus our attention on selected NF1 patient missense mutations...complexity of NF1 disease phenotypes in different tissues, age and sex dependency of symptoms, impact of environmental factors and genetic heterogeneity...suggesting the role of modifier genes [12]. This work aims to shed light on this issue by studying the functional consequences of selected NF1

Characterizing visible and invisible cell wall mutant phenotypes

Energy Technology Data Exchange (ETDEWEB)

Carpita, Nicholas C.; McCann, Maureen C.

2015-04-06

About 10% of a plant's genome is devoted to generating the protein machinery to synthesize, remodel, and deconstruct the cell wall. High-throughput genome sequencing technologies have enabled a reasonably complete inventory of wall-related genes that can be assembled into families of common evolutionary origin. Assigning function to each gene family member has been aided immensely by identification of mutants with visible phenotypes or by chemical and spectroscopic analysis of mutants with ‘invisible’ phenotypes of modified cell wall composition and architecture that do not otherwise affect plant growth or development. This review connects the inference of gene function on the basis of deviation from the wild type in genetic functional analyses to insights provided by modern analytical techniques that have brought us ever closer to elucidating the sequence structures of the major polysaccharide components of the plant cell wall.

Phenotypic and functional analyses show stem cell-derived hepatocyte-like cells better mimic fetal rather than adult hepatocytes.

Science.gov (United States)

Baxter, Melissa; Withey, Sarah; Harrison, Sean; Segeritz, Charis-Patricia; Zhang, Fang; Atkinson-Dell, Rebecca; Rowe, Cliff; Gerrard, Dave T; Sison-Young, Rowena; Jenkins, Roz; Henry, Joanne; Berry, Andrew A; Mohamet, Lisa; Best, Marie; Fenwick, Stephen W; Malik, Hassan; Kitteringham, Neil R; Goldring, Chris E; Piper Hanley, Karen; Vallier, Ludovic; Hanley, Neil A

2015-03-01

Hepatocyte-like cells (HLCs), differentiated from pluripotent stem cells by the use of soluble factors, can model human liver function and toxicity. However, at present HLC maturity and whether any deficit represents a true fetal state or aberrant differentiation is unclear and compounded by comparison to potentially deteriorated adult hepatocytes. Therefore, we generated HLCs from multiple lineages, using two different protocols, for direct comparison with fresh fetal and adult hepatocytes. Protocols were developed for robust differentiation. Multiple transcript, protein and functional analyses compared HLCs to fresh human fetal and adult hepatocytes. HLCs were comparable to those of other laboratories by multiple parameters. Transcriptional changes during differentiation mimicked human embryogenesis and showed more similarity to pericentral than periportal hepatocytes. Unbiased proteomics demonstrated greater proximity to liver than 30 other human organs or tissues. However, by comparison to fresh material, HLC maturity was proven by transcript, protein and function to be fetal-like and short of the adult phenotype. The expression of 81% phase 1 enzymes in HLCs was significantly upregulated and half were statistically not different from fetal hepatocytes. HLCs secreted albumin and metabolized testosterone (CYP3A) and dextrorphan (CYP2D6) like fetal hepatocytes. In seven bespoke tests, devised by principal components analysis to distinguish fetal from adult hepatocytes, HLCs from two different source laboratories consistently demonstrated fetal characteristics. HLCs from different sources are broadly comparable with unbiased proteomic evidence for faithful differentiation down the liver lineage. This current phenotype mimics human fetal rather than adult hepatocytes. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Effects of blood transportation on human peripheral mononuclear cell yield, phenotype and function: implications for immune cell biobanking.

Directory of Open Access Journals (Sweden)

Anita Posevitz-Fejfár

Full Text Available Human biospecimen collection, processing and preservation are rapidly emerging subjects providing essential support to clinical as well as basic researchers. Unlike collection of other biospecimens (e.g. DNA and serum, biobanking of viable immune cells, such as peripheral blood mononuclear cells (PBMC and/or isolated immune cell subsets is still in its infancy. While certain aspects of processing and freezing conditions have been studied in the past years, little is known about the effect of blood transportation on immune cell survival, phenotype and specific functions. However, especially for multicentric and cooperative projects it is vital to precisely know those effects. In this study we investigated the effect of blood shipping and pre-processing delay on immune cell phenotype and function both on cellular and subcellular levels. Peripheral blood was collected from healthy volunteers (n = 9: at a distal location (shipped overnight and in the central laboratory (processed immediately. PBMC were processed in the central laboratory and analyzed post-cryopreservation. We analyzed yield, major immune subset distribution, proliferative capacity of T cells, cytokine pattern and T-cell receptor signal transduction. Results show that overnight transportation of blood samples does not globally compromise T- cell subsets as they largely retain their phenotype and proliferative capacity. However, NK and B cell frequencies, the production of certain PBMC-derived cytokines and IL-6 mediated cytokine signaling pathway are altered due to transportation. Various control experiments have been carried out to compare issues related to shipping versus pre-processing delay on site. Our results suggest the implementation of appropriate controls when using multicenter logistics for blood transportation aiming at subsequent isolation of viable immune cells, e.g. in multicenter clinical trials or studies analyzing immune cells/subsets. One important conclusion might

Prediction of postoperative lung function after pulmonary resection

International Nuclear Information System (INIS)

Yoshikawa, Koichi

1988-01-01

Lung scintigraphy and ordinary lung function test as well as split lung function test by using bronchospirometry was performed in 78 patients with primary lung cancer and clinical significance of ventilation and perfusion scintigraphy was evaluated. Results obtained from this study are as follows. 1) The ratio of right VC to total VC obtained by preoperative bronchospirometry was well correlated to the ratio of right lung count to the total lung count obtained by ventiration and/or perfusion scintigraphy (r = 0.84, r = 0.69). 2) Evaluation of the data obtained from the patients undergoing pneumonectomy indicated that the right and left VC obtained preoperatively by bronchospirometry have their clinical significance only in the form of left to right ratio not in the form their absolure value. 3) As to the reliability of predicting the residual vital capacity after pneumonectomy on the basis of left-to-right of lung scintigraphy, ventilation scintigraphy is more reliable than perfusion scintigraphy. 4) Irrespective of using ventilation scintigraphy or perfusion scintigraphy, Ali's formular showed high reliability in predicting the residual vital capacity as well as FEV 1.0 after lobectomy. 5) Reduction of the perfusion rate in the operated side of the lung is more marked than of the ventilation rate, resulting in a significant elevation of ventilation/perfusion ratio of the operated side of the lung. From the results descrived above, it can be said that lung ventilation and perfusion scintigraphy are very useful method to predict the residual lung function as well as the change of ventilation/perfusion ratio after pulmonary resection. (author)

Mechanisms by Which Phenotypic Plasticity Affects Adaptive Divergence and Ecological Speciation.

Science.gov (United States)

Nonaka, Etsuko; Svanbäck, Richard; Thibert-Plante, Xavier; Englund, Göran; Brännström, Åke

2015-11-01

Phenotypic plasticity is the ability of one genotype to produce different phenotypes depending on environmental conditions. Several conceptual models emphasize the role of plasticity in promoting reproductive isolation and, ultimately, speciation in populations that forage on two or more resources. These models predict that plasticity plays a critical role in the early stages of speciation, prior to genetic divergence, by facilitating fast phenotypic divergence. The ability to plastically express alternative phenotypes may, however, interfere with the early phase of the formation of reproductive barriers, especially in the absence of geographic barriers. Here, we quantitatively investigate mechanisms under which plasticity can influence progress toward adaptive genetic diversification and ecological speciation. We use a stochastic, individual-based model of a predator-prey system incorporating sexual reproduction and mate choice in the predator. Our results show that evolving plasticity promotes the evolution of reproductive isolation under diversifying environments when individuals are able to correctly select a more profitable habitat with respect to their phenotypes (i.e., adaptive habitat choice) and to assortatively mate with relatively similar phenotypes. On the other hand, plasticity facilitates the evolution of plastic generalists when individuals have a limited capacity for adaptive habitat choice. We conclude that plasticity can accelerate the evolution of a reproductive barrier toward adaptive diversification and ecological speciation through enhanced phenotypic differentiation between diverging phenotypes.

Predicting plant biomass accumulation from image-derived parameters

Science.gov (United States)

Chen, Dijun; Shi, Rongli; Pape, Jean-Michel; Neumann, Kerstin; Graner, Andreas; Chen, Ming; Klukas, Christian

2018-01-01

Abstract Background Image-based high-throughput phenotyping technologies have been rapidly developed in plant science recently, and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologists. However, it is a great challenge to find a predictive biomass model across experiments. Results In the present study, we constructed 4 predictive models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to 3 consecutive barley (Hordeum vulgare) experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based parameters using a random forest model. The high prediction accuracy based on this model will contribute to relieving the phenotyping bottleneck in biomass measurement in breeding applications. The prediction performance is still relatively high across experiments under similar conditions. The relative contribution of individual features for predicting biomass was further quantified, revealing new insights into the phenotypic determinants of the plant biomass outcome. Furthermore, methods could also be used to determine the most important image-based features related to plant biomass accumulation, which would be promising for subsequent genetic mapping to uncover the genetic basis of biomass. Conclusions We have developed quantitative models to accurately predict plant biomass accumulation from image data. We anticipate that the analysis results will be useful to advance our views of the phenotypic determinants of plant biomass outcome, and the statistical methods can be broadly used for other plant species. PMID:29346559

Structural and functional concepts in current mouse phenotyping and archiving facilities

Czech Academy of Sciences Publication Activity Database

Kollmus, H.; Post, R.; Brielmeier, M.; Fernandez, J.; Fuchs, H.; McKerlie, C.; Montoliu, L.; Otaegui, P.J.; Rebelo, M.; Riedesel, H.; Ruberte, J.; Sedláček, Radislav; de Angelis, M.H.; Schughart, K.

2012-01-01

Roč. 51, č. 4 (2012), s. 418-435 ISSN 1559-6109 Grant - others:7.RP EU(XE) 211404 Program:FP7 Institutional support: RVO:68378050 Keywords : Infrafrontier * phenotyping * archiving * animal facility design Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.145, year: 2012

XmnI polymorphism: Relation to β-thalassemia phenotype and ...

African Journals Online (AJOL)

Conclusions and recommendations: In conclusion, molecular determination of genetic markers in childhood will help to identify phenotypes of our patients and to avoid over or under treatment strategies. Further prospective studies concerning the genetic markers that could predict the response to hemoglobin F inducers like ...

Water hammer prediction and control: the Green's function method

Science.gov (United States)

Xuan, Li-Jun; Mao, Feng; Wu, Jie-Zhi

2012-04-01

By Green's function method we show that the water hammer (WH) can be analytically predicted for both laminar and turbulent flows (for the latter, with an eddy viscosity depending solely on the space coordinates), and thus its hazardous effect can be rationally controlled and minimized. To this end, we generalize a laminar water hammer equation of Wang et al. (J. Hydrodynamics, B2, 51, 1995) to include arbitrary initial condition and variable viscosity, and obtain its solution by Green's function method. The predicted characteristic WH behaviors by the solutions are in excellent agreement with both direct numerical simulation of the original governing equations and, by adjusting the eddy viscosity coefficient, experimentally measured turbulent flow data. Optimal WH control principle is thereby constructed and demonstrated.

Integration of relational and hierarchical network information for protein function prediction

Directory of Open Access Journals (Sweden)

Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment.

Science.gov (United States)

Lande, R

2014-05-01

Quantitative genetic models of evolution of phenotypic plasticity are used to derive environmental tolerance curves for a population in a changing environment, providing a theoretical foundation for integrating physiological and community ecology with evolutionary genetics of plasticity and norms of reaction. Plasticity is modelled for a labile quantitative character undergoing continuous reversible development and selection in a fluctuating environment. If there is no cost of plasticity, a labile character evolves expected plasticity equalling the slope of the optimal phenotype as a function of the environment. This contrasts with previous theory for plasticity influenced by the environment at a critical stage of early development determining a constant adult phenotype on which selection acts, for which the expected plasticity is reduced by the environmental predictability over the discrete time lag between development and selection. With a cost of plasticity in a labile character, the expected plasticity depends on the cost and on the environmental variance and predictability averaged over the continuous developmental time lag. Environmental tolerance curves derived from this model confirm traditional assumptions in physiological ecology and provide new insights. Tolerance curve width increases with larger environmental variance, but can only evolve within a limited range. The strength of the trade-off between tolerance curve height and width depends on the cost of plasticity. Asymmetric tolerance curves caused by male sterility at high temperature are illustrated. A simple condition is given for a large transient increase in plasticity and tolerance curve width following a sudden change in average environment. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Behavioral phenotype relates to physiological differences in immunological and stress responsiveness in reactive and proactive birds.

Science.gov (United States)

Pusch, Elizabeth A; Navara, Kristen J

2018-05-15

It has now been demonstrated in many species that individuals display substantial variation in coping styles, generally separating into two major behavioral phenotypes that appear to be linked to the degree of physiological stress responsiveness. Laying hens are perfect examples of these dichotomous phenotypes; white laying hens are reactive, flighty, and exhibit large hormonal and behavioral responses to both acute and chronic stress, while brown laying hens are proactive, exploratory, and exhibit low hormonal and behavioral responses to stress. Given the linkages between stress physiology and many other body systems, we hypothesized that behavioral phenotype would correspond to additional physiological responses beyond the stress response, in this case, immunological responses. Because corticosterone is widely known to be immunosuppressive, we predicted that the reactive white hens would show more dampened immune responses than the proactive brown hens due to their exposure to higher levels of corticosterone throughout life. To assess immune function in white and brown hens, we compared febrile responses, corticosterone elevations, feed consumption, and egg production that occurred in response an injection of lipopolysaccharide (LPS) or saline, inflammatory responses to phytohemagglutinin (PHA) injection in the toe web, innate phagocytic activity in whole blood, and antibody responses to an injection of Sheep Red Blood Cells (SRBCs). Contrary to our predictions, white hens had significantly greater swelling of the toe web in response to PHA and showed a greater inhibition of feeding and reproductive output in response to LPS. These results indicated that reactive individuals are more reactive in both stress and immunological responsiveness. Copyright © 2018 Elsevier Inc. All rights reserved.

Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

Directory of Open Access Journals (Sweden)

Jiangang Liu

Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

Directory of Open Access Journals (Sweden)

Jean-Baptiste Durand

2017-06-01

Full Text Available Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI with an autoregressive coefficient (γg efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γg and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

FIG4 regulates lysosome membrane homeostasis independent of phosphatase function.

Science.gov (United States)

Bharadwaj, Rajnish; Cunningham, Kathleen M; Zhang, Ke; Lloyd, Thomas E

2016-02-15

FIG4 is a phosphoinositide phosphatase that is mutated in several diseases including Charcot-Marie-Tooth Disease 4J (CMT4J) and Yunis-Varon syndrome (YVS). To investigate the mechanism of disease pathogenesis, we generated Drosophila models of FIG4-related diseases. Fig4 null mutant animals are viable but exhibit marked enlargement of the lysosomal compartment in muscle cells and neurons, accompanied by an age-related decline in flight ability. Transgenic animals expressing Drosophila Fig4 missense mutations corresponding to human pathogenic mutations can partially rescue lysosomal expansion phenotypes, consistent with these mutations causing decreased FIG4 function. Interestingly, Fig4 mutations predicted to inactivate FIG4 phosphatase activity rescue lysosome expansion phenotypes, and mutations in the phosphoinositide (3) phosphate kinase Fab1 that performs the reverse enzymatic reaction also causes a lysosome expansion phenotype. Since FIG4 and FAB1 are present together in the same biochemical complex, these data are consistent with a model in which FIG4 serves a phosphatase-independent biosynthetic function that is essential for lysosomal membrane homeostasis. Lysosomal phenotypes are suppressed by genetic inhibition of Rab7 or the HOPS complex, demonstrating that FIG4 functions after endosome-to-lysosome fusion. Furthermore, disruption of the retromer complex, implicated in recycling from the lysosome to Golgi, does not lead to similar phenotypes as Fig4, suggesting that the lysosomal defects are not due to compromised retromer-mediated recycling of endolysosomal membranes. These data show that FIG4 plays a critical noncatalytic function in maintaining lysosomal membrane homeostasis, and that this function is disrupted by mutations that cause CMT4J and YVS. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Factor VII Deficiency: Clinical Phenotype, Genotype and Therapy.

Science.gov (United States)

Napolitano, Mariasanta; Siragusa, Sergio; Mariani, Guglielmo

2017-03-28

Factor VII deficiency is the most common among rare inherited autosomal recessive bleeding disorders, and is a chameleon disease due to the lack of a direct correlation between plasma levels of coagulation Factor VII and bleeding manifestations. Clinical phenotypes range from asymptomatic condition-even in homozygous subjects-to severe life-threatening bleedings (central nervous system, gastrointestinal bleeding). Prediction of bleeding risk is thus based on multiple parameters that challenge disease management. Spontaneous or surgical bleedings require accurate treatment schedules, and patients at high risk of severe hemorrhages may need prophylaxis from childhood onwards. The aim of the current review is to depict an updated summary of clinical phenotype, laboratory diagnosis, and treatment of inherited Factor VII deficiency.

RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

Directory of Open Access Journals (Sweden)

Shmelev Gennadiy Dmitrievich

2017-11-01

Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

Mouse SNP Miner: an annotated database of mouse functional single nucleotide polymorphisms

Directory of Open Access Journals (Sweden)

Ramensky Vasily E

2007-01-01

Full Text Available Abstract Background The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci ( Description To help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at http://bioinfo.embl.it/SnpApplet/. For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function. Conclusion We have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously

Metabolic profiles to define the genome: can we hear the phenotypes?

OpenAIRE

Griffin, Julian L

2004-01-01

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified ...

Positional RNA-Seq identifies candidate genes for phenotypic engineering of sexual traits

NARCIS (Netherlands)

Arbore, Roberto; Sekii, Kiyono; Beisel, Christian; Ladurner, Peter; Berezikov, Eugene; Schaerer, Lukas

2015-01-01

Introduction: RNA interference (RNAi) of trait-specific genes permits the manipulation of specific phenotypic traits ("phenotypic engineering") and thus represents a powerful tool to test trait function in evolutionary studies. The identification of suitable candidate genes, however, often relies on

Plant functional traits predict green roof ecosystem services.

Science.gov (United States)

Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

2015-02-17

Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

The Phenotype/Genotype Correlation of Lactase Persistence among Omani Adults

Directory of Open Access Journals (Sweden)

Abdulrahim Al-Abri

2013-09-01

Full Text Available Objective: To examine the correlation of lactase persistence phenotype with genotype in Omani adults.Methods: Lactase persistence phenotype was tested by hydrogen breath test in 52 Omani Adults using the Micro H2 analyzer. Results were checked against genotyping using direct DNA sequencing.Results: Forty one individuals with C/C-13910 and T/T-13915 genotypes had positive breath tests (≥20 ppm; while eight of nine individuals with T/C-13910 or T/G-13915 genotypes had negative breath tests (<20 ppm and two subjects were non-hydrogen producers. The agreement between phenotype and genotype using Kappa value was very good (0.93.Conclusion: Genotyping both T/C-13910 and T/G-13915 alleles can be used to assist diagnosis and predict lactose intolerance in the Omani population.

Prediction of postoperative respiratory function of lung cancer patients using quantitative lung scans

International Nuclear Information System (INIS)

Konishi, Hiroshi

1982-01-01

Quantitative sup(99m)Tc-MISA inhalation scan and sup(99m)Tc-MAA perfusion scan were performed in 35 patients with lung cancer who underwent lobectomies. Quantitative 133 Xe ventilation-perfusion scans were also performed in 34 patients with lung cancer who underwent lobectomies. To predict functional loss after lobectomy, the proportion of the No. of segments in the lobe to be resected to the No. of entire segments of that lung was provided for the study. Postoperative FVC, FEVsub(1.0) and MVV were predicted in the study, and which were compared to the respiratory function at one month after operation and more than four months after operation. The predicted postoperative respiratory function was highly correlated with the actually observed postoperative respiratory function (0.7413 lt r lt 0.9278, p lt 0.001). In this study, the postoperative respiratory function was proven to be quite accurately predicted preoperatively with combination of quantitative lung scans and spirometric respiratory function. Therefore this method is useful not only for judgement of operative indication but also for choice of operative method and for counterplan of postoperative respiratory insufficiency. (J.P.N.)

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

Science.gov (United States)

Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

DIANA-microT web server: elucidating microRNA functions through target prediction.

Science.gov (United States)

Maragkakis, M; Reczko, M; Simossis, V A; Alexiou, P; Papadopoulos, G L; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, A G

2009-07-01

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

Warped linear mixed models for the genetic analysis of transformed phenotypes.

Science.gov (United States)

Fusi, Nicolo; Lippert, Christoph; Lawrence, Neil D; Stegle, Oliver

2014-09-19

Linear mixed models (LMMs) are a powerful and established tool for studying genotype-phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction.

The phenotypic equilibrium of cancer cells: From average-level stability to path-wise convergence.

Science.gov (United States)

Niu, Yuanling; Wang, Yue; Zhou, Da

2015-12-07

The phenotypic equilibrium, i.e. heterogeneous population of cancer cells tending to a fixed equilibrium of phenotypic proportions, has received much attention in cancer biology very recently. In the previous literature, some theoretical models were used to predict the experimental phenomena of the phenotypic equilibrium, which were often explained by different concepts of stabilities of the models. Here we present a stochastic multi-phenotype branching model by integrating conventional cellular hierarchy with phenotypic plasticity mechanisms of cancer cells. Based on our model, it is shown that: (i) our model can serve as a framework to unify the previous models for the phenotypic equilibrium, and then harmonizes the different kinds of average-level stabilities proposed in these models; and (ii) path-wise convergence of our model provides a deeper understanding to the phenotypic equilibrium from stochastic point of view. That is, the emergence of the phenotypic equilibrium is rooted in the stochastic nature of (almost) every sample path, the average-level stability just follows from it by averaging stochastic samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parasitism and the biodiversity-functioning relationship

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Frainer, André; McKie, Brendan G.; Amundsen, Per-Arne; Knudsen, Rune; Lafferty, Kevin D.

2018-01-01

Biodiversity affects ecosystem functioning.Biodiversity may decrease or increase parasitism.Parasites impair individual hosts and affect their role in the ecosystem.Parasitism, in common with competition, facilitation, and predation, could regulate BD-EF relationships.Parasitism affects host phenotypes, including changes to host morphology, behavior, and physiology, which might increase intra- and interspecific functional diversity.The effects of parasitism on host abundance and phenotypes, and on interactions between hosts and the remaining community, all have potential to alter community structure and BD-EF relationships.Global change could facilitate the spread of invasive parasites, and alter the existing dynamics between parasites, communities, and ecosystems.Species interactions can influence ecosystem functioning by enhancing or suppressing the activities of species that drive ecosystem processes, or by causing changes in biodiversity. However, one important class of species interactions – parasitism – has been little considered in biodiversity and ecosystem functioning (BD-EF) research. Parasites might increase or decrease ecosystem processes by reducing host abundance. Parasites could also increase trait diversity by suppressing dominant species or by increasing within-host trait diversity. These different mechanisms by which parasites might affect ecosystem function pose challenges in predicting their net effects. Nonetheless, given the ubiquity of parasites, we propose that parasite–host interactions should be incorporated into the BD-EF framework.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

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Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

2017-09-01

Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

STRING 8--a global view on proteins and their functional interactions in 630 organisms

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Kuhn, Michael; Stark, Manuel

2008-01-01

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein inter......Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein......-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set...... of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures...

Computational prediction of drug-drug interactions based on drugs functional similarities.

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Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

Fungal NRPS-dependent siderophores: From function to prediction

DEFF Research Database (Denmark)

Sørensen, Jens Laurids; Knudsen, Michael; Hansen, Frederik Teilfeldt

2014-01-01

discuss the function of siderophores in relation to fungal iron uptake mechanisms and their importance for coexistence with host organisms. The chemical nature of the major groups of siderophores and their regulation is described along with the function and architecture of the large multi-domain enzymes...... responsible for siderophore synthesis, namely the non-ribosomal peptide synthetases (NRPSs). Finally, we present the most recent advances in our understanding of the structural biology of fungal NRPSs and discuss opportunities for the development of a fungal NRPS prediction server...

Characterization and Prediction of Chemical Functions and ...

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Assessing exposures from the thousands of chemicals in commerce requires quantitative information on the chemical constituents of consumer products. Unfortunately, gaps in available composition data prevent assessment of exposure to chemicals in many products. Here we propose filling these gaps via consideration of chemical functional role. We obtained function information for thousands of chemicals from public sources and used a clustering algorithm to assign chemicals into 35 harmonized function categories (e.g., plasticizers, antimicrobials, solvents). We combined these functions with weight fraction data for 4115 personal care products (PCPs) to characterize the composition of 66 different product categories (e.g., shampoos). We analyzed the combined weight fraction/function dataset using machine learning techniques to develop quantitative structure property relationship (QSPR) classifier models for 22 functions and for weight fraction, based on chemical-specific descriptors (including chemical properties). We applied these classifier models to a library of 10196 data-poor chemicals. Our predictions of chemical function and composition will inform exposure-based screening of chemicals in PCPs for combination with hazard data in risk-based evaluation frameworks. As new information becomes available, this approach can be applied to other classes of products and the chemicals they contain in order to provide essential consumer product data for use in exposure-b

No predictive value of GC phenotypes for HIV infection and progression to AIDS

NARCIS (Netherlands)

Pronk, J. C.; Frants, R. R.; Crusius, B.; Eriksson, A. W.; de Wolf, F.; Boucher, C. A.; Bakker, M.; Goudsmit, J.

1988-01-01

The genetic polymorphism of group-specific component (GC) was investigated with isoelectric focusing in 351 homosexual men at risk for HIV infection, 96 male patients with AIDS, and 86 heterosexual controls. No significant differences in GC phenotype distribution were seen between controls and any

Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

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Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina M.; Mawn, Louise A.; Landman, Bennett A.

2017-03-01

We examine imaging and electronic medical records (EMR) of 588 subjects over five major disease groups that affect optic nerve function. An objective evaluation of the role of imaging and EMR data in diagnosis of these conditions would improve understanding of these diseases and help in early intervention. We developed an automated image processing pipeline that identifies the orbital structures within the human eyes from computed tomography (CT) scans, calculates structural size, and performs volume measurements. We customized the EMR-based phenome-wide association study (PheWAS) to derive diagnostic EMR phenotypes that occur at least two years prior to the onset of the conditions of interest from a separate cohort of 28,411 ophthalmology patients. We used random forest classifiers to evaluate the predictive power of image-derived markers, EMR phenotypes, and clinical visual assessments in identifying disease cohorts from a control group of 763 patients without optic nerve disease. Image-derived markers showed more predictive power than clinical visual assessments or EMR phenotypes. However, the addition of EMR phenotypes to the imaging markers improves the classification accuracy against controls: the AUC improved from 0.67 to 0.88 for glaucoma, 0.73 to 0.78 for intrinsic optic nerve disease, 0.72 to 0.76 for optic nerve edema, 0.72 to 0.77 for orbital inflammation, and 0.81 to 0.85 for thyroid eye disease. This study illustrates the importance of diagnostic context for interpretation of image-derived markers and the proposed PheWAS technique provides a flexible approach for learning salient features of patient history and incorporating these data into traditional machine learning analyses.

Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.

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Cáceda, Ricardo; James, G Andrew; Gutman, David A; Kilts, Clinton D

2015-10-01

Reciprocation of trust exchanges is central to the development of interpersonal relationships and societal well-being. Understanding how humans make pro-social and self-centered decisions in dyadic interactions and how to predict these choices has been an area of great interest in social neuroscience. A functional magnetic resonance imaging (fMRI) based technology with potential clinical application is the study of resting state brain connectivity. We tested if resting state connectivity may predict choice behavior in a social context. Twenty-nine healthy adults underwent resting state fMRI before performing the Trust Game, a two person monetary exchange game. We assessed the ability of patterns of resting-state functional brain organization, demographic characteristics and a measure of moral development, the Defining Issues Test (DIT-2), to predict individuals' decisions to reciprocate money during the Trust Game. Subjects reciprocated in 74.9% of the trials. Independent component analysis identified canonical resting-state networks. Increased functional connectivity between the salience (bilateral insula/anterior cingulate) and central executive (dorsolateral prefrontal cortex/ posterior parietal cortex) networks significantly predicted the choice to reciprocate pro-social behavior (R(2) = 0.20, p = 0.015). Stepwise linear regression analysis showed that functional connectivity between these two networks (p = 0.002), age (p = 0.007) and DIT-2 personal interest schema score (p = 0.032) significantly predicted reciprocity behavior (R(2) = 0.498, p = 0.001). Intrinsic functional connectivity between neural networks in conjunction with other individual characteristics may be a valuable tool for predicting performance during social interactions. Future replication and temporal extension of these findings may bolster the understanding of decision making in clinical, financial and marketing settings. Copyright © 2015 Elsevier B.V. All rights reserved.

Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

Science.gov (United States)

Takahashi, Yuma; Kagawa, Kotaro; Svensson, Erik I; Kawata, Masakado

2014-07-18

The effect of evolutionary changes in traits and phenotypic/genetic diversity on ecological dynamics has received much theoretical attention; however, the mechanisms and ecological consequences are usually unknown. Female-limited colour polymorphism in damselflies is a counter-adaptation to male mating harassment, and thus, is expected to alter population dynamics through relaxing sexual conflict. Here we show the side effect of the evolution of female morph diversity on population performance (for example, population productivity and sustainability) in damselflies. Our theoretical model incorporating key features of the sexual interaction predicts that the evolution of increased phenotypic diversity will reduce overall fitness costs to females from sexual conflict, which in turn will increase productivity, density and stability of a population. Field data and mesocosm experiments support these model predictions. Our study suggests that increased phenotypic diversity can enhance population performance that can potentially reduce extinction rates and thereby influence macroevolutionary processes.

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change.

Science.gov (United States)

Stenlid, Jan; Oliva, Jonàs

2016-12-05

Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host-pathogen interactions when predicting disease impacts. We emphasize the need to consider host-tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host-pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host-pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Author(s).

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change

Science.gov (United States)

2016-01-01

Invasive pathogens can cause considerable damage to forest ecosystems. Lack of coevolution is generally thought to enable invasive pathogens to bypass the defence and/or recognition systems in the host. Although mostly true, this argument fails to predict intermittent outcomes in space and time, underlining the need to include the roles of the environment and the phenotype in host–pathogen interactions when predicting disease impacts. We emphasize the need to consider host–tree imbalances from a phenotypic perspective, considering the lack of coevolutionary and evolutionary history with the pathogen and the environment, respectively. We describe how phenotypic plasticity and plastic responses to environmental shifts may become maladaptive when hosts are faced with novel pathogens. The lack of host–pathogen and environmental coevolution are aligned with two global processes currently driving forest damage: globalization and climate change, respectively. We suggest that globalization and climate change act synergistically, increasing the chances of both genotypic and phenotypic imbalances. Short moves on the same continent are more likely to be in balance than if the move is from another part of the world. We use Gremmeniella abietina outbreaks in Sweden to exemplify how host–pathogen phenotypic interactions can help to predict the impacts of specific invasive and emergent diseases. This article is part of the themed issue ‘Tackling emerging fungal threats to animal health, food security and ecosystem resilience’. PMID:28080981

Idiopathic Pulmonary Fibrosis: Gender-Age-Physiology Index Stage for Predicting Future Lung Function Decline.

Science.gov (United States)

Salisbury, Margaret L; Xia, Meng; Zhou, Yueren; Murray, Susan; Tayob, Nabihah; Brown, Kevin K; Wells, Athol U; Schmidt, Shelley L; Martinez, Fernando J; Flaherty, Kevin R

2016-02-01

Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage. Patients with idiopathic pulmonary fibrosis (N = 657) were identified retrospectively at three tertiary referral centers, and baseline GAP stages were assessed. Mixed models were used to describe average trajectories of FVC and diffusing capacity of the lung for carbon monoxide (Dlco). Multivariable Cox proportional hazards models were used to assess whether declines in pulmonary function ≥ 10% in 6 months predict mortality after accounting for GAP stage. Over a 2-year period, GAP stage was not associated with differences in yearly lung function decline. After accounting for stage, a 10% decrease in FVC or Dlco over 6 months independently predicted death or transplantation (FVC hazard ratio, 1.37; Dlco hazard ratio, 1.30; both, P ≤ .03). Patients with GAP stage 2 with declining pulmonary function experienced a survival profile similar to patients with GAP stage 3, with 1-year event-free survival of 59.3% (95% CI, 49.4-67.8) vs 56.9% (95% CI, 42.2-69.1). Baseline GAP stage predicted death or lung transplantation but not the rate of future pulmonary function decline. After accounting for GAP stage, a decline of ≥ 10% over 6 months independently predicted death or lung transplantation. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Connectomic intermediate phenotypes for psychiatric disorders

Directory of Open Access Journals (Sweden)

Alex eFornito

2012-04-01

Full Text Available Psychiatric disorders are phenotypically heterogeneous entities with a complex genetic basis. To mitigate this complexity, many investigators study so-called intermediate phenotypes that putatively provide a more direct index of the physiological effects of candidate genetic risk variants than overt psychiatric syndromes. Magnetic resonance imaging (MRI is a particularly popular technique for measuring such phenotypes because it allows interrogation of diverse aspects of brain structure and function in vivo. Much of this work however, has focused on relatively simple measures that quantify variations in the physiology or tissue integrity of specific brain regions in isolation, contradicting an emerging consensus that most major psychiatric disorders do not arise from isolated dysfunction in one or a few brain regions, but rather from disturbed interactions within and between distributed neural circuits; i.e., they are disorders of brain connectivity. The recent proliferation of new MRI techniques for comprehensively mapping the entire connectivity architecture of the brain, termed the human connectome, has provided a rich repertoire of tools for understanding how genetic variants implicated in mental disorder impact distinct neural circuits. In this article, we review research using these connectomic techniques to understand how genetic variation influences the connectivity and topology of human brain networks. We highlight recent evidence from twin and imaging genetics studies suggesting that the penetrance of candidate risk variants for mental illness, such as those in SLC6A4, MAOA, ZNF804A and APOE, may be higher for intermediate phenotypes characterised at the level of distributed neural systems than at the level of spatially localised brain regions. The findings indicate that imaging connectomics provides a powerful framework for understanding how genetic risk for psychiatric disease is expressed through altered structure and function of

Challenges in microbial ecology: Building predictive understanding of community function and dynamics

DEFF Research Database (Denmark)

Widder, Stefanie; Allen, Rosalind J.; Pfeiffer, Thomas

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly...... complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development...... is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved....

PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.