The pharmacogenetics of body odor: as easy as ABCC?

PubMed

Brown, Sara

2013-07-01

ABCC11 genotype affects apocrine secretory cell function and determines individual body odor phenotype. Rodriguez et al. have applied genetic epidemiology using predetermined phenotype data to demonstrate an association between a single-nucleotide polymorphism (rs17822931) and the human behavior of deodorant application. Individuals with the ABCC11 genotype predicting a nonodorous phenotype report a significantly lower frequency of deodorant use.

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

PubMed

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 phenotype from genotype: Improving accuracy through more robust experimental and computational modeling

PubMed Central

Gallion, Jonathan; Koire, Amanda; Katsonis, Panagiotis; Schoenegge, Anne‐Marie; Bouvier, Michel

2017-01-01

Abstract Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predictions are sensitive to protein alignment construction and can be customized to maximize relevance of predictions to a specific experimental question. We conclude that inconsistencies between computation and experiment can often be attributed to the fact that they do not test identical hypotheses. Aligning the design of the computational input with the design of the experimental output will require cooperation between computational and biological scientists, but will also lead to improved estimations of computational prediction accuracy and a better understanding of the genotype–phenotype relationship. PMID:28230923

Predicting phenotype from genotype: Improving accuracy through more robust experimental and computational modeling.

PubMed

Gallion, Jonathan; Koire, Amanda; Katsonis, Panagiotis; Schoenegge, Anne-Marie; Bouvier, Michel; Lichtarge, Olivier

2017-05-01

Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predictions are sensitive to protein alignment construction and can be customized to maximize relevance of predictions to a specific experimental question. We conclude that inconsistencies between computation and experiment can often be attributed to the fact that they do not test identical hypotheses. Aligning the design of the computational input with the design of the experimental output will require cooperation between computational and biological scientists, but will also lead to improved estimations of computational prediction accuracy and a better understanding of the genotype-phenotype relationship. © 2017 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Relationship between endophenotype and phenotype in ADHD

PubMed Central

Rommelse, Nanda NJ; Altink, Marieke E; Martin, Neilson C; Buschgens, Cathelijne JM; Faraone, Stephen V; Buitelaar, Jan K; Sergeant, Joseph A; Oosterlaan, Jaap

2008-01-01

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 factors may be crucial and aggravate the ADHD symptoms in affected children. PMID:18234079

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

PubMed

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.

DNM1 encephalopathy

PubMed Central

von Spiczak, Sarah; Helbig, Katherine L.; Shinde, Deepali N.; Huether, Robert; Pendziwiat, Manuela; Lourenço, Charles; Nunes, Mark E.; Sarco, Dean P.; Kaplan, Richard A.; Dlugos, Dennis J.; Kirsch, Heidi; Slavotinek, Anne; Cilio, Maria R.; Cervenka, Mackenzie C.; Cohen, Julie S.; McClellan, Rebecca; Fatemi, Ali; Yuen, Amy; Sagawa, Yoshimi; Littlejohn, Rebecca; McLean, Scott D.; Hernandez-Hernandez, Laura; Maher, Bridget; Møller, Rikke S.; Palmer, Elizabeth; Lawson, John A.; Campbell, Colleen A.; Joshi, Charuta N.; Kolbe, Diana L.; Hollingsworth, Georgie; Neubauer, Bernd A.; Muhle, Hiltrud; Stephani, Ulrich; Scheffer, Ingrid E.; Pena, Sérgio D.J.; Sisodiya, Sanjay M.

2017-01-01

Objective: To evaluate the phenotypic spectrum caused by mutations in dynamin 1 (DNM1), encoding the presynaptic protein DNM1, and to investigate possible genotype-phenotype correlations and predicted functional consequences based on structural modeling. Methods: We reviewed phenotypic data of 21 patients (7 previously published) with DNM1 mutations. We compared mutation data to known functional data and undertook biomolecular modeling to assess the effect of the mutations on protein function. Results: We identified 19 patients with de novo mutations in DNM1 and a sibling pair who had an inherited mutation from a mosaic parent. Seven patients (33.3%) carried the recurrent p.Arg237Trp mutation. A common phenotype emerged that included severe to profound intellectual disability and muscular hypotonia in all patients and an epilepsy characterized by infantile spasms in 16 of 21 patients, frequently evolving into Lennox-Gastaut syndrome. Two patients had profound global developmental delay without seizures. In addition, we describe a single patient with normal development before the onset of a catastrophic epilepsy, consistent with febrile infection-related epilepsy syndrome at 4 years. All mutations cluster within the GTPase or middle domains, and structural modeling and existing functional data suggest a dominant-negative effect on DMN1 function. Conclusions: The phenotypic spectrum of DNM1-related encephalopathy is relatively homogeneous, in contrast to many other genetic epilepsies. Up to one-third of patients carry the recurrent p.Arg237Trp variant, which is now one of the most common recurrent variants in epileptic encephalopathies identified to date. Given the predicted dominant-negative mechanism of this mutation, this variant presents a prime target for therapeutic intervention. PMID:28667181

Genotypic richness predicts phenotypic variation in an endangered clonal plant

PubMed Central

Sinclair, Elizabeth A.; Poore, Alistair G.B.; Bain, Keryn F.; Vergés, Adriana

2016-01-01

Declines in genetic diversity within a species can affect the stability and functioning of populations. The conservation of genetic diversity is thus a priority, especially for threatened or endangered species. The importance of genetic variation, however, is dependent on the degree to which it translates into phenotypic variation for traits that affect individual performance and ecological processes. This is especially important for predominantly clonal species, as no single clone is likely to maximise all aspects of performance. Here we show that intraspecific genotypic diversity as measured using microsatellites is a strong predictor of phenotypic variation in morphological traits and shoot productivity of the threatened, predominantly clonal seagrass Posidonia australis, on the east coast of Australia. Biomass and surface area variation was most strongly predicted by genotypic richness, while variation in leaf chemistry (phenolics and nitrogen) was unrelated to genotypic richness. Genotypic richness did not predict tissue loss to herbivores or epiphyte load, however we did find that increased herbivore damage was positively correlated with allelic richness. Although there was no clear relationship between higher primary productivity and genotypic richness, variation in shoot productivity within a meadow was significantly greater in more genotypically diverse meadows. The proportion of phenotypic variation explained by environmental conditions varied among different genotypes, and there was generally no variation in phenotypic traits among genotypes present in the same meadows. Our results show that genotypic richness as measured through the use of presumably neutral DNA markers does covary with phenotypic variation in functionally relevant traits such as leaf morphology and shoot productivity. The remarkably long lifespan of individual Posidonia plants suggests that plasticity within genotypes has played an important role in the longevity of the species. However, the strong link between genotypic and phenotypic variation suggests that a range of genotypes is still the best case scenario for adaptation to and recovery from predicted environmental change. PMID:26925313

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

PubMed

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.

Modeling thrombin generation: plasma composition based approach.

PubMed

Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas

2014-01-01

Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

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

PubMed

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.

VarMod: modelling the functional effects of non-synonymous variants

PubMed Central

Pappalardo, Morena; Wass, Mark N.

2014-01-01

Unravelling the genotype–phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in proteins the difficulties of the problem lie in first identifying those nsSNVs that result in a functional change in the protein among the many non-functional variants and in turn linking this functional change to phenotype. Here we present VarMod (Variant Modeller) a method that utilises both protein sequence and structural features to predict nsSNVs that alter protein function. VarMod develops recent observations that functional nsSNVs are enriched at protein–protein interfaces and protein–ligand binding sites and uses these characteristics to make predictions. In benchmarking on a set of nearly 3000 nsSNVs VarMod performance is comparable to an existing state of the art method. The VarMod web server provides extensive resources to investigate the sequence and structural features associated with the predictions including visualisation of protein models and complexes via an interactive JSmol molecular viewer. VarMod is available for use at http://www.wasslab.org/varmod. PMID:24906884

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2017-11-01

Integration Theory of intelligence (Jung and Haier, Behave Brain Sci, 2007...predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are heritable and highly sensitive to both normal and...pathological aging processes. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity

Many-to-one form-to-function mapping weakens parallel morphological evolution.

PubMed

Thompson, Cole J; Ahmed, Newaz I; Veen, Thor; Peichel, Catherine L; Hendry, Andrew P; Bolnick, Daniel I; Stuart, Yoel E

2017-11-01

Evolutionary ecologists aim to explain and predict evolutionary change under different selective regimes. Theory suggests that such evolutionary prediction should be more difficult for biomechanical systems in which different trait combinations generate the same functional output: "many-to-one mapping." Many-to-one mapping of phenotype to function enables multiple morphological solutions to meet the same adaptive challenges. Therefore, many-to-one mapping should undermine parallel morphological evolution, and hence evolutionary predictability, even when selection pressures are shared among populations. Studying 16 replicate pairs of lake- and stream-adapted threespine stickleback (Gasterosteus aculeatus), we quantified three parts of the teleost feeding apparatus and used biomechanical models to calculate their expected functional outputs. The three feeding structures differed in their form-to-function relationship from one-to-one (lower jaw lever ratio) to increasingly many-to-one (buccal suction index, opercular 4-bar linkage). We tested for (1) weaker linear correlations between phenotype and calculated function, and (2) less parallel evolution across lake-stream pairs, in the many-to-one systems relative to the one-to-one system. We confirm both predictions, thus supporting the theoretical expectation that increasing many-to-one mapping undermines parallel evolution. Therefore, sole consideration of morphological variation within and among populations might not serve as a proxy for functional variation when multiple adaptive trait combinations exist. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Hypogonadotropic Hypogonadism due to Novel FGFR1 Mutations.

PubMed

Akkuş, Gamze; Kotan, Leman Damla; Durmaz, Erdem; Mengen, Eda; Turan, İhsan; Ulubay, Ayça; Gürbüz, Fatih; Yüksel, Bilgin; Tetiker, Tamer; Topaloğlu, A Kemal

2017-06-01

The underlying genetic etiology of hypogonadotropic hypogonadism (HH) is heterogeneous. Fibroblast growth factor signaling is pivotal in the ontogeny of gonadotropin-releasing hormone neurons. Loss-of-function mutations in FGFR1 gene cause variable HH phenotypes encompassing pubertal delay to idiopathic HH (IHH) or Kallmann syndrome (KS). As FGFR1 mutations are common, recognizing mutations and associated phenotypes may enhance clinical management. Using a candidate gene approach, we screened 52 IHH/KS patients. We identified three novel (IVS3-1G>C and p.W2X, p.R209C) FGFR1 gene mutations. Despite predictive null protein function, patients from the novel mutation families had normosmic IHH without non-reproductive phenotype. These findings further emphasize the great variability of FGFR1 mutation phenotypes in IHH/KS.

Genome-wide prediction of childhood asthma and related phenotypes in a longitudinal birth cohort

PubMed Central

Spycher, Ben D.; Henderson, John; Granell, Raquel; Evans, David M.; Smith, George Davey; Timpson, Nicholas J.; Sterne, Jonathan A. C.

2016-01-01

Background Childhood wheezing and asthma vary greatly in clinical presentation and time course. The extent to which phenotypic variation reflects heterogeneity in disease pathways is unclear. Objective To assess the extent to which single nucleotide polymorphisms (SNPs) associated with childhood asthma in a genome-wide association study are predictive of asthma-related phenotypes. Methods In 8365 children from a population based birth cohort, the Avon Longitudinal Study of Parents and Children, allelic scores were derived based on between 10 and 215,443 SNPs ranked according to inverse of the p-value for their association with physician diagnosed asthma in an independent genome-wide association study (6176 cases and 7111 controls). We assessed the predictive value of allelic scores for asthma-related outcomes at age 7-9 years (physician’s diagnosis, longitudinal wheezing phenotypes, and measurements of pulmonary function, bronchial responsiveness and atopy). Results Scores based on the 46 highest-ranked SNPs were associated with the symptom-based phenotypes persistent (P<10-11, area under ROC curve (AUC)=0.59) and intermediate onset (P<10-3, AUC=0.58) wheeze. Among lower-ranked SNPs (ranks 21,545-46,416), there was evidence for associations with diagnosed asthma (P<10-4, AUC=0.54) and atopy (P<10-5, AUC=0.55). We found little evidence of associations with transient early wheezing, reduced pulmonary function or non-asthma phenotypes. Conclusion The genetic origins of asthma are diverse and: some pathways are specific to wheezing syndromes while others are shared with atopy and bronchial hyper-responsiveness. Out study also provides evidence of aetiological differences among wheezing syndromes. PMID:22846752

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants

PubMed Central

Weston, David J; Gunter, Lee E; Rogers, Alistair; Wullschleger, Stan D

2008-01-01

Background One of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Ecology currently lacks an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress duration and tolerance, fitness). Results Here, we demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying genes governing the phenotypic response. Using this approach, we confirm the existence of known stress responsive pathways and marker genes, report a common abiotic stress responsive transcriptome and relate phenotypic classification to stress duration. Conclusion Linking genomic signatures to gene coexpression analysis provides a unique method of relating an observed plant phenotype to changes in gene expression that underlie that phenotype. Such information is critical to current and future investigations in plant biology and, in particular, to evolutionary ecology, where a mechanistic understanding of adaptive physiological responses to abiotic stress can provide researchers with a tool of great predictive value in understanding species and population level adaptation to climate change. PMID:18248680

Integrating Evolutionary Game Theory into Mechanistic Genotype-Phenotype Mapping.

PubMed

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.

Envirotyping for deciphering environmental impacts on crop plants.

PubMed

Xu, Yunbi

2016-04-01

Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data.

PubMed

Huang, Yi-Fei; Gulko, Brad; Siepel, Adam

2017-04-01

Many genetic variants that influence phenotypes of interest are located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which, therefore, are likely to be phenotypically important. LINSIGHT combines a generalized linear model for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the 'big data' available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell type, tissue specificity, and constraints at associated promoters.

Network Hubs Buffer Environmental Variation in Saccharomyces cerevisiae

PubMed Central

Levy, Sasha F; Siegal, Mark L

2008-01-01

Regulatory and developmental systems produce phenotypes that are robust to environmental and genetic variation. A gene product that normally contributes to this robustness is termed a phenotypic capacitor. When a phenotypic capacitor fails, for example when challenged by a harsh environment or mutation, the system becomes less robust and thus produces greater phenotypic variation. A functional phenotypic capacitor provides a mechanism by which hidden polymorphism can accumulate, whereas its failure provides a mechanism by which evolutionary change might be promoted. The primary example to date of a phenotypic capacitor is Hsp90, a molecular chaperone that targets a large set of signal transduction proteins. In both Drosophila and Arabidopsis, compromised Hsp90 function results in pleiotropic phenotypic effects dependent on the underlying genotype. For some traits, Hsp90 also appears to buffer stochastic variation, yet the relationship between environmental and genetic buffering remains an important unresolved question. We previously used simulations of knockout mutations in transcriptional networks to predict that many gene products would act as phenotypic capacitors. To test this prediction, we use high-throughput morphological phenotyping of individual yeast cells from single-gene deletion strains to identify gene products that buffer environmental variation in Saccharomyces cerevisiae. We find more than 300 gene products that, when absent, increase morphological variation. Overrepresented among these capacitors are gene products that control chromosome organization and DNA integrity, RNA elongation, protein modification, cell cycle, and response to stimuli such as stress. Capacitors have a high number of synthetic-lethal interactions but knockouts of these genes do not tend to cause severe decreases in growth rate. Each capacitor can be classified based on whether or not it is encoded by a gene with a paralog in the genome. Capacitors with a duplicate are highly connected in the protein–protein interaction network and show considerable divergence in expression from their paralogs. In contrast, capacitors encoded by singleton genes are part of highly interconnected protein clusters whose other members also tend to affect phenotypic variability or fitness. These results suggest that buffering and release of variation is a widespread phenomenon that is caused by incomplete functional redundancy at multiple levels in the genetic architecture. PMID:18986213

Biological interpretation of genome-wide association studies using predicted gene functions.

PubMed

Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

2015-01-19

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

Frailty and sarcopenia as the basis for the phenotypic manifestation of chronic diseases in older adults.

PubMed

Angulo, Javier; El Assar, Mariam; Rodríguez-Mañas, Leocadio

2016-08-01

Frailty is a functional status that precedes disability and is characterized by decreased functional reserve and increased vulnerability. In addition to disability, the frailty phenotype predicts falls, institutionalization, hospitalization and mortality. Frailty is the consequence of the interaction between the aging process and some chronic diseases and conditions that compromise functional systems and finally produce sarcopenia. Many of the clinical manifestations of frailty are explained by sarcopenia which is closely related to poor physical performance. Reduced regenerative capacity, malperfusion, oxidative stress, mitochondrial dysfunction and inflammation compose the sarcopenic skeletal muscle alterations associated to the frailty phenotype. Inflammation appears as a common determinant for chronic diseases, sarcopenia and frailty. The strategies to prevent the frailty phenotype include an adequate amount of physical activity and exercise as well as pharmacological interventions such as myostatin inhibitors and specific androgen receptor modulators. Cell response to stress pathways such as Nrf2, sirtuins and klotho could be considered as future therapeutic interventions for the management of frailty phenotype and aging-related chronic diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Systematic Association of Genes to Phenotypes by Genome and Literature Mining

PubMed Central

Jensen, Lars J; Perez-Iratxeta, Carolina; Kaczanowski, Szymon; Hooper, Sean D; Andrade, Miguel A

2005-01-01

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene–phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases. PMID:15799710

Dimensional Structure of the Autism Phenotype: Relations between Early Development and Current Presentation

ERIC Educational Resources Information Center

Kamp-Becker, Inge; Ghahreman, Mardjan; Smidt, Judith; Remschmidt, Helmut

2009-01-01

The dimensional structure of higher functioning autism phenotype was investigated by factor analysis. The goal of this study was to identify the degree to which early symptoms of autism (measured using the ADI-R) could be predictive of the current symptoms of autism as identified using the ADOS, the adaptive behavior scales, IQ scores and theory…

Mapping structural landmarks, ligand binding sites and missense mutations to the collagen IV heterotrimers predicts major functional domains, novel interactions and variation in phenotypes in inherited diseases affecting basement membranes

PubMed Central

Des Parkin, J.; San Antonio, James D.; Pedchenko, Vadim; Hudson, Billy; Jensen, Shane T.; Savige, Judy

2016-01-01

Collagen IV is the major protein found in basement membranes. It comprises 3 heterotrimers (α1α1α2, α3α4α5, and α5α5α6) that form distinct networks, and are responsible for membrane strength and integrity. We constructed linear maps of the collagen IV heterotrimers (‘interactomes’) that indicated major structural landmarks, known and predicted ligand-binding sites, and missense mutations, in order to identify functional and disease-associated domains, potential interactions between ligands, and genotype-phenotype relationships. The maps documented more than 30 known ligand-binding sites as well as motifs for integrins, heparin, von Willebrand factor (VWF), decorin and bone morphogenetic protein (BMP). They predicted functional domains for angiogenesis and haemostasis, and disease domains for autoimmunity, tumor growth and inhibition, infection and glycation. Cooperative ligand interactions were indicated by binding site proximity, for example, between integrins, matrix metalloproteinases and heparin. The maps indicated that mutations affecting major ligand-binding sites, for example for Von Hippel Lindau (VHL) protein in the α1 chain or integrins in the α5 chain, resulted in distinctive phenotypes (Hereditary Angiopathy, Nephropathy, Aneurysms and muscle Cramps (HANAC) syndrome, and early onset Alport syndrome respectively). These maps further our understanding of basement membrane biology and disease, and suggest novel membrane interactions, functions, and therapeutic targets. PMID:21280145

Phenotypic plasticity and specialization in clonal versus non-clonal plants: A data synthesis

NASA Astrophysics Data System (ADS)

Fazlioglu, Fatih; Bonser, Stephen P.

2016-11-01

Reproductive strategies can be associated with ecological specialization and generalization. Clonal plants produce lineages adapted to the maternal habitat that can lead to specialization. However, clonal plants frequently display high phenotypic plasticity (e.g. clonal foraging for resources), factors linked to ecological generalization. Alternately, sexual reproduction can be associated with generalization via increasing genetic variation or specialization through rapid adaptive evolution. Moreover, specializing to high or low quality habitats can determine how phenotypic plasticity is expressed in plants. The specialization hypothesis predicts that specialization to good environments results in high performance trait plasticity and specialization to bad environments results in low performance trait plasticity. The interplay between reproductive strategies, phenotypic plasticity, and ecological specialization is important for understanding how plants adapt to variable environments. However, we currently have a poor understanding of these relationships. In this study, we addressed following questions: 1) Is there a relationship between phenotypic plasticity, specialization, and reproductive strategies in plants? 2) Do good habitat specialists express greater performance trait plasticity than bad habitat specialists? We searched the literature for studies examining plasticity for performance traits and functional traits in clonal and non-clonal plant species from different habitat types. We found that non-clonal (obligate sexual) plants expressed greater performance trait plasticity and functional trait plasticity than clonal plants. That is, non-clonal plants exhibited a specialist strategy where they perform well only in a limited range of habitats. Clonal plants expressed less performance loss across habitats and a more generalist strategy. In addition, specialization to good habitats did not result in greater performance trait plasticity. This result was contrary to the predictions of the specialization hypothesis. Overall, reproductive strategies are associated with ecological specialization or generalization through phenotypic plasticity. While specialization is common in plant populations, the evolution of specialization does not control the nature of phenotypic plasticity as predicted under the specialization hypothesis.

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

PubMed

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.

Biological interpretation of genome-wide association studies using predicted gene functions

PubMed Central

Pers, Tune H.; Karjalainen, Juha M.; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R.; Yang, Jian; Lui, Julian C.; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K.; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S.N.; Hirschhorn, Joel N.; Franke, Lude

2015-01-01

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. PMID:25597830

VarMod: modelling the functional effects of non-synonymous variants.

PubMed

Pappalardo, Morena; Wass, Mark N

2014-07-01

Unravelling the genotype-phenotype relationship in humans remains a challenging task in genomics studies. Recent advances in sequencing technologies mean there are now thousands of sequenced human genomes, revealing millions of single nucleotide variants (SNVs). For non-synonymous SNVs present in proteins the difficulties of the problem lie in first identifying those nsSNVs that result in a functional change in the protein among the many non-functional variants and in turn linking this functional change to phenotype. Here we present VarMod (Variant Modeller) a method that utilises both protein sequence and structural features to predict nsSNVs that alter protein function. VarMod develops recent observations that functional nsSNVs are enriched at protein-protein interfaces and protein-ligand binding sites and uses these characteristics to make predictions. In benchmarking on a set of nearly 3000 nsSNVs VarMod performance is comparable to an existing state of the art method. The VarMod web server provides extensive resources to investigate the sequence and structural features associated with the predictions including visualisation of protein models and complexes via an interactive JSmol molecular viewer. VarMod is available for use at http://www.wasslab.org/varmod. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparative genomics of 28 Salmonella enterica isolates: evidence for CRISPR-mediated adaptive sublineage evolution.

PubMed

Fricke, W Florian; Mammel, Mark K; McDermott, Patrick F; Tartera, Carmen; White, David G; Leclerc, J Eugene; Ravel, Jacques; Cebula, Thomas A

2011-07-01

Despite extensive surveillance, food-borne Salmonella enterica infections continue to be a significant burden on public health systems worldwide. As the S. enterica species comprises sublineages that differ greatly in antigenic representation, virulence, and antimicrobial resistance phenotypes, a better understanding of the species' evolution is critical for the prediction and prevention of future outbreaks. The roles that virulence and resistance phenotype acquisition, exchange, and loss play in the evolution of S. enterica sublineages, which to a certain extent are represented by serotypes, remains mostly uncharacterized. Here, we compare 17 newly sequenced and phenotypically characterized nontyphoidal S. enterica strains to 11 previously sequenced S. enterica genomes to carry out the most comprehensive comparative analysis of this species so far. These phenotypic and genotypic data comparisons in the phylogenetic species context suggest that the evolution of known S. enterica sublineages is mediated mostly by two mechanisms, (i) the loss of coding sequences with known metabolic functions, which leads to functional reduction, and (ii) the acquisition of horizontally transferred phage and plasmid DNA, which provides virulence and resistance functions and leads to increasing specialization. Matches between S. enterica clustered regularly interspaced short palindromic repeats (CRISPR), part of a defense mechanism against invading plasmid and phage DNA, and plasmid and prophage regions suggest that CRISPR-mediated immunity could control short-term phenotype changes and mediate long-term sublineage evolution. CRISPR analysis could therefore be critical in assessing the evolutionary potential of S. enterica sublineages and aid in the prediction and prevention of future S. enterica outbreaks.

Comparative Genomics of 28 Salmonella enterica Isolates: Evidence for CRISPR-Mediated Adaptive Sublineage Evolution ▿†

PubMed Central

Fricke, W. Florian; Mammel, Mark K.; McDermott, Patrick F.; Tartera, Carmen; White, David G.; LeClerc, J. Eugene; Ravel, Jacques; Cebula, Thomas A.

2011-01-01

Despite extensive surveillance, food-borne Salmonella enterica infections continue to be a significant burden on public health systems worldwide. As the S. enterica species comprises sublineages that differ greatly in antigenic representation, virulence, and antimicrobial resistance phenotypes, a better understanding of the species' evolution is critical for the prediction and prevention of future outbreaks. The roles that virulence and resistance phenotype acquisition, exchange, and loss play in the evolution of S. enterica sublineages, which to a certain extent are represented by serotypes, remains mostly uncharacterized. Here, we compare 17 newly sequenced and phenotypically characterized nontyphoidal S. enterica strains to 11 previously sequenced S. enterica genomes to carry out the most comprehensive comparative analysis of this species so far. These phenotypic and genotypic data comparisons in the phylogenetic species context suggest that the evolution of known S. enterica sublineages is mediated mostly by two mechanisms, (i) the loss of coding sequences with known metabolic functions, which leads to functional reduction, and (ii) the acquisition of horizontally transferred phage and plasmid DNA, which provides virulence and resistance functions and leads to increasing specialization. Matches between S. enterica clustered regularly interspaced short palindromic repeats (CRISPR), part of a defense mechanism against invading plasmid and phage DNA, and plasmid and prophage regions suggest that CRISPR-mediated immunity could control short-term phenotype changes and mediate long-term sublineage evolution. CRISPR analysis could therefore be critical in assessing the evolutionary potential of S. enterica sublineages and aid in the prediction and prevention of future S. enterica outbreaks. PMID:21602358

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

PubMed

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.

Metabolic Host Responses to Malarial Infection during the Intraerythrocytic Developmental Cycle

DTIC Science & Technology

2016-08-08

by reproducing the experimentally determined 1) stage-specific production of biomass components and their precursors in the parasite and 2) metabolite...uptake, allow for the prediction of cellular growth ( biomass accumulation) and other phenotypic functions related to metabolism [9]. For example...our group to capture stage-specific growth phenotypes and biomass metabolite production [15]. Among these metabolic descriptions, only the network

Ecological transition predictably associated with gene degeneration.

PubMed

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.

Causal Genetic Variation Underlying Metabolome Differences.

PubMed

Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

2017-08-01

An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

Correlation between Relatives given Complete Genotypes: from Identity by Descent to Identity by Function

PubMed Central

Sverdlov, Serge; Thompson, Elizabeth A.

2013-01-01

In classical quantitative genetics, the correlation between the phenotypes of individuals with unknown genotypes and a known pedigree relationship is expressed in terms of probabilities of IBD states. In existing approaches to the inverse problem where genotypes are observed but pedigree relationships are not, dependence between phenotypes is either modeled as Bayesian uncertainty or mapped to an IBD model via inferred relatedness parameters. Neither approach yields a relationship between genotypic similarity and phenotypic similarity with a probabilistic interpretation corresponding to a generative model. We introduce a generative model for diploid allele effect based on the classic infinite allele mutation process. This approach motivates the concept of IBF (Identity by Function). The phenotypic covariance between two individuals given their diploid genotypes is expressed in terms of functional identity states. The IBF parameters define a genetic architecture for a trait without reference to specific alleles or population. Given full genome sequences, we treat a gene-scale functional region, rather than a SNP, as a QTL, modeling patterns of dominance for multiple alleles. Applications demonstrated by simulation include phenotype and effect prediction and association, and estimation of heritability and classical variance components. A simulation case study of the Missing Heritability problem illustrates a decomposition of heritability under the IBF framework into Explained and Unexplained components. PMID:23851163

Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

Which ante mortem clinical features predict progressive supranuclear palsy pathology?

PubMed

Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

2017-07-01

Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Brain evolution and development: adaptation, allometry and constraint

PubMed Central

Barton, Robert A.

2016-01-01

Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns. PMID:27629025

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.

PubMed

van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem

2015-10-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.

Improving Microbial Genome Annotations in an Integrated Database Context

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, T; Jones, I M; Mohrenweiser, H W

2003-11-03

Over 520 different amino acid substitution variants have been previously identified in the systematic screening of 91 human DNA repair genes for sequence variation. Two algorithms were employed to predict the impact of these amino acid substitutions on protein activity. Sorting Intolerant From Tolerant (SIFT) classified 226 of 508 variants (44%) as ''Intolerant''. Polymorphism Phenotyping (PolyPhen) classed 165 of 489 amino acid substitutions (34%) as ''Probably or Possibly Damaging''. Another 9-15% of the variants were classed as ''Potentially Intolerant or Damaging''. The results from the two algorithms are highly associated, with concordance in predicted impact observed for {approx}62% of themore » variants. Twenty one to thirty one percent of the variant proteins are predicted to exhibit reduced activity by both algorithms. These variants occur at slightly lower individual allele frequency than do the variants classified as ''Tolerant'' or ''Benign''. Both algorithms correctly predicted the impact of 26 functionally characterized amino acid substitutions in the APE1 protein on biochemical activity, with one exception. It is concluded that a substantial fraction of the missense variants observed in the general human population are functionally relevant. These variants are expected to be the molecular genetic and biochemical basis for the associations of reduced DNA repair capacity phenotypes with elevated cancer risk.« less

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

PubMed

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.

Introduction to Focus Issue: Genetic Interactions

NASA Astrophysics Data System (ADS)

Segrè, Daniel; Marx, Christopher J.

2010-06-01

The perturbation of a gene in an organism's genome often causes changes in the organism's observable properties or phenotypes. It is not obvious a priori whether the simultaneous perturbation of two genes produces a phenotypic change that is easily predictable from the changes caused by individual perturbations. In fact, this is often not the case: the nonlinearity and interdependence between genetic variants in determining phenotypes, also known as epistasis, is a prevalent phenomenon in biological systems. This focus issue presents recent developments in the study of epistasis and genetic interactions, emphasizing the broad implications of this phenomenon in evolutionary biology, functional genomics, and human diseases.

GLADIATOR: a global approach for elucidating disease modules.

PubMed

Silberberg, Yael; Kupiec, Martin; Sharan, Roded

2017-05-26

Understanding the genetic basis of disease is an important challenge in biology and medicine. The observation that disease-related proteins often interact with one another has motivated numerous network-based approaches for deciphering disease mechanisms. In particular, protein-protein interaction networks were successfully used to illuminate disease modules, i.e., interacting proteins working in concert to drive a disease. The identification of these modules can further our understanding of disease mechanisms. We devised a global method for the prediction of multiple disease modules simultaneously named GLADIATOR (GLobal Approach for DIsease AssociaTed mOdule Reconstruction). GLADIATOR relies on a gold-standard disease phenotypic similarity to obtain a pan-disease view of the underlying modules. To traverse the search space of potential disease modules, we applied a simulated annealing algorithm aimed at maximizing the correlation between module similarity and the gold-standard phenotypic similarity. Importantly, this optimization is employed over hundreds of diseases simultaneously. GLADIATOR's predicted modules highly agree with current knowledge about disease-related proteins. Furthermore, the modules exhibit high coherence with respect to functional annotations and are highly enriched with known curated pathways, outperforming previous methods. Examination of the predicted proteins shared by similar diseases demonstrates the diverse role of these proteins in mediating related processes across similar diseases. Last, we provide a detailed analysis of the suggested molecular mechanism predicted by GLADIATOR for hyperinsulinism, suggesting novel proteins involved in its pathology. GLADIATOR predicts disease modules by integrating knowledge of disease-related proteins and phenotypes across multiple diseases. The predicted modules are functionally coherent and are more in line with current biological knowledge compared to modules obtained using previous disease-centric methods. The source code for GLADIATOR can be downloaded from http://www.cs.tau.ac.il/~roded/GLADIATOR.zip .

Protein function prediction--the power of multiplicity.

PubMed

Rentzsch, Robert; Orengo, Christine A

2009-04-01

Advances in experimental and computational methods have quietly ushered in a new era in protein function annotation. This 'age of multiplicity' is marked by the notion that only the use of multiple tools, multiple evidence and considering the multiple aspects of function can give us the broad picture that 21st century biology will need to link and alter micro- and macroscopic phenotypes. It might also help us to undo past mistakes by removing errors from our databases and prevent us from producing more. On the downside, multiplicity is often confusing. We therefore systematically review methods and resources for automated protein function prediction, looking at individual (biochemical) and contextual (network) functions, respectively.

Monogenic diabetes syndromes: Locus‐specific databases for Alström, Wolfram, and Thiamine‐responsive megaloblastic anemia

PubMed Central

Astuti, Dewi; Sabir, Ataf; Fulton, Piers; Zatyka, Malgorzata; Williams, Denise; Hardy, Carol; Milan, Gabriella; Favaretto, Francesca; Yu‐Wai‐Man, Patrick; Rohayem, Julia; López de Heredia, Miguel; Hershey, Tamara; Tranebjaerg, Lisbeth; Chen, Jian‐Hua; Chaussenot, Annabel; Nunes, Virginia; Marshall, Bess; McAfferty, Susan; Tillmann, Vallo; Maffei, Pietro; Paquis‐Flucklinger, Veronique; Geberhiwot, Tarekign; Mlynarski, Wojciech; Parkinson, Kay; Picard, Virginie; Bueno, Gema Esteban; Dias, Renuka; Arnold, Amy; Richens, Caitlin; Paisey, Richard; Urano, Fumihiko; Semple, Robert; Sinnott, Richard

2017-01-01

Abstract We developed a variant database for diabetes syndrome genes, using the Leiden Open Variation Database platform, containing observed phenotypes matched to the genetic variations. We populated it with 628 published disease‐associated variants (December 2016) for: WFS1 (n = 309), CISD2 (n = 3), ALMS1 (n = 268), and SLC19A2 (n = 48) for Wolfram type 1, Wolfram type 2, Alström, and Thiamine‐responsive megaloblastic anemia syndromes, respectively; and included 23 previously unpublished novel germline variants in WFS1 and 17 variants in ALMS1. We then investigated genotype–phenotype relations for the WFS1 gene. The presence of biallelic loss‐of‐function variants predicted Wolfram syndrome defined by insulin‐dependent diabetes and optic atrophy, with a sensitivity of 79% (95% CI 75%–83%) and specificity of 92% (83%–97%). The presence of minor loss‐of‐function variants in WFS1 predicted isolated diabetes, isolated deafness, or isolated congenital cataracts without development of the full syndrome (sensitivity 100% [93%–100%]; specificity 78% [73%–82%]). The ability to provide a prognostic prediction based on genotype will lead to improvements in patient care and counseling. The development of the database as a repository for monogenic diabetes gene variants will allow prognostic predictions for other diabetes syndromes as next‐generation sequencing expands the repertoire of genotypes and phenotypes. The database is publicly available online at https://lovd.euro-wabb.org. PMID:28432734

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach.

PubMed

Nagasundaram, N; Priya Doss, C George

2011-01-01

Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

Wine Expertise Predicts Taste Phenotype

PubMed Central

Hayes, John E; Pickering, Gary J

2011-01-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance – with appropriate caveats about populations tested, outcomes measured and psychophysical methods used – an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli. PMID:22888174

Wine Expertise Predicts Taste Phenotype.

PubMed

Hayes, John E; Pickering, Gary J

2012-03-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

COMBREX-DB: an experiment centered database of protein function: knowledge, predictions and knowledge gaps.

PubMed

Chang, Yi-Chien; Hu, Zhenjun; Rachlin, John; Anton, Brian P; Kasif, Simon; Roberts, Richard J; Steffen, Martin

2016-01-04

The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼ 3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Semi-supervised learning for genomic prediction of novel traits with small reference populations: an application to residual feed intake in dairy cattle.

PubMed

Yao, Chen; Zhu, Xiaojin; Weigel, Kent A

2016-11-07

Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a semi-supervised learning strategy known as the self-training model, and applied this method to genomic prediction of residual feed intake (RFI) in dairy cattle. We describe a self-training model that is wrapped around a support vector machine (SVM) algorithm, which enables it to use data from animals with and without measured phenotypes. Initially, a SVM model was trained using data from 792 animals with measured RFI phenotypes. Then, the resulting SVM was used to generate self-trained phenotypes for 3000 animals for which RFI measurements were not available. Finally, the SVM model was re-trained using data from up to 3792 animals, including those with measured and self-trained RFI phenotypes. Incorporation of additional animals with self-trained phenotypes enhanced the accuracy of genomic predictions compared to that of predictions that were derived from the subset of animals with measured phenotypes. The optimal ratio of animals with self-trained phenotypes to animals with measured phenotypes (2.5, 2.0, and 1.8) and the maximum increase achieved in prediction accuracy measured as the correlation between predicted and actual RFI phenotypes (5.9, 4.1, and 2.4%) decreased as the size of the initial training set (300, 400, and 500 animals with measured phenotypes) increased. The optimal number of animals with self-trained phenotypes may be smaller when prediction accuracy is measured as the mean squared error rather than the correlation between predicted and actual RFI phenotypes. Our results demonstrate that semi-supervised learning models that incorporate self-trained phenotypes can achieve genomic prediction accuracies that are comparable to those obtained with models using larger training sets that include only animals with measured phenotypes. Semi-supervised learning can be helpful for genomic prediction of novel traits, such as RFI, for which the size of reference population is limited, in particular, when the animals to be predicted and the animals in the reference population originate from the same herd-environment.

Mitochondrial “power” drives tamoxifen resistance: NQO1 and GCLC are new therapeutic targets in breast cancer

PubMed Central

Fiorillo, Marco; Sotgia, Federica; Sisci, Diego; Cappello, Anna Rita; Lisanti, Michael P.

2017-01-01

Here, we identified two new molecular targets, which are functionally sufficient to metabolically confer the tamoxifen-resistance phenotype in human breast cancer cells. Briefly, ~20 proteins were first selected as potential candidates, based on unbiased proteomics analysis, using tamoxifen-resistant cell lines. Then, the cDNAs of the most promising candidates were systematically transduced into MCF-7 cells. Remarkably, NQO1 and GCLC were both functionally sufficient to autonomously confer a tamoxifen-resistant metabolic phenotype, characterized by i) increased mitochondrial biogenesis, ii) increased ATP production and iii) reduced glutathione levels. Thus, we speculate that pharmacological inhibition of NQO1 and GCLC may be new therapeutic strategies for overcoming tamoxifen-resistance in breast cancer patients. In direct support of this notion, we demonstrate that treatment with a known NQO1 inhibitor (dicoumarol) is indeed sufficient to revert the tamoxifen-resistance phenotype. As such, these findings could have important translational significance for the prevention of tumor recurrence in ER(+) breast cancers, which is due to an endocrine resistance phenotype. Importantly, we also show here that NQO1 has significant prognostic value as a biomarker for the prediction of tumor recurrence. More specifically, higher levels of NQO1 mRNA strongly predict patient relapse in high-risk ER(+) breast cancer patients receiving endocrine therapy (mostly tamoxifen; H.R. > 2.15; p = 0.007). PMID:28411284

Prevalence of the Fibromyalgia Phenotype in Spine Pain Patients Presenting to a Tertiary Care Pain Clinic and the Potential Treatment Implications

PubMed Central

Brummett, Chad M.; Goesling, Jenna; Tsodikov, Alex; Meraj, Taha S.; Wasserman, Ronald A.; Clauw, Daniel J.; Hassett, Afton L.

2014-01-01

Objective Injections for spinal pain have high failure rates, emphasizing the importance of patient selection. It is possible that detecting the presence of a fibromyalgia-like phenotype could aid in prediction, because in these individuals a peripheral injection would not address pain due to alterations in central neurotransmission. We hypothesized that spine pain patients meeting survey criteria for fibromyalgia would be phenotypically distinct from those who do not meet criteria. Methods 548 patients with a primary spine pain diagnosis were studied. All patients completed validated self-report questionnaires, including the Brief Pain Inventory, PainDETECT, Hospital Anxiety and Depression Scale, measures of physical function, and the American College of Rheumatology survey criteria for fibromyalgia. Results 42% met survey criteria for fibromyalgia (FM+). When compared with criteria negative patients, FM+ patients were more likely to be younger, unemployed, receiving compensation, have greater pain intensity, pain interference and neuropathic pain descriptors, as well as higher levels of depression and anxiety, and lower level of physical function (p < 0.0001 for each comparison). Gender, neuropathic pain, pain interference, physical function, and anxiety were independently predictive of fibromyalgia status in a multivariate analysis (p < 0.01, all variables). ROC analysis showed the strength of association of 0.81 as measured by the cross-validated C-statistic. Conclusion Using the survey criteria for fibromyalgia, we demonstrated profound phenotypic differences in a spine pain population. Although centralized pain cannot be confirmed with a survey alone, the pathophysiology of fibromyalgia may help explain a portion of the variability of responses to spine interventions. PMID:24022710

Plasma oxytocin concentrations and OXTR polymorphisms predict social impairments in children with and without autism spectrum disorder.

PubMed

Parker, Karen J; Garner, Joseph P; Libove, Robin A; Hyde, Shellie A; Hornbeak, Kirsten B; Carson, Dean S; Liao, Chun-Ping; Phillips, Jennifer M; Hallmayer, Joachim F; Hardan, Antonio Y

2014-08-19

The neuropeptide oxytocin (OXT) and its receptor (OXTR) regulate social functioning in animals and humans. Initial clinical research suggests that dysregulated plasma OXT concentrations and/or OXTR SNPs may be biomarkers of social impairments in autism spectrum disorder (ASD). We do not know, however, whether OXT dysregulation is unique to ASD or whether OXT biology influences social functioning more generally, thus contributing to, but not causing, ASD phenotypes. To distinguish between these possibilities, we tested in a child ASD cohort, which included unaffected siblings and unrelated neurotypical controls (ages 3-12 y; n = 193), whether plasma OXT concentrations and OXTR SNPs (i) interact to produce ASD phenotypes, (ii) exert differential phenotypic effects in ASD vs. non-ASD children, or (iii) have similar phenotypic effects independent of disease status. In the largest cohort tested to date, we found no evidence to support the OXT deficit hypothesis of ASD. Rather, OXT concentrations strongly and positively predicted theory of mind and social communication performance in all groups. Furthermore, OXT concentrations showed significant heritability between ASD-discordant siblings (h(2) = 85.5%); a heritability estimate on par with that of height in humans. Finally, carriers of the "G" allele of rs53576 showed impaired affect recognition performance and carriers of the "A" allele of rs2254298 exhibited greater global social impairments in all groups. These findings indicate that OXT biology is not uniquely associated with ASD, but instead exerts independent, additive, and highly heritable influences on individual differences in human social functioning, including the severe social impairments which characterize ASD.

Plasma oxytocin concentrations and OXTR polymorphisms predict social impairments in children with and without autism spectrum disorder

PubMed Central

Parker, Karen J.; Garner, Joseph P.; Libove, Robin A.; Hyde, Shellie A.; Hornbeak, Kirsten B.; Carson, Dean S.; Liao, Chun-Ping; Phillips, Jennifer M.; Hallmayer, Joachim F.; Hardan, Antonio Y.

2014-01-01

The neuropeptide oxytocin (OXT) and its receptor (OXTR) regulate social functioning in animals and humans. Initial clinical research suggests that dysregulated plasma OXT concentrations and/or OXTR SNPs may be biomarkers of social impairments in autism spectrum disorder (ASD). We do not know, however, whether OXT dysregulation is unique to ASD or whether OXT biology influences social functioning more generally, thus contributing to, but not causing, ASD phenotypes. To distinguish between these possibilities, we tested in a child ASD cohort, which included unaffected siblings and unrelated neurotypical controls (ages 3–12 y; n = 193), whether plasma OXT concentrations and OXTR SNPs (i) interact to produce ASD phenotypes, (ii) exert differential phenotypic effects in ASD vs. non-ASD children, or (iii) have similar phenotypic effects independent of disease status. In the largest cohort tested to date, we found no evidence to support the OXT deficit hypothesis of ASD. Rather, OXT concentrations strongly and positively predicted theory of mind and social communication performance in all groups. Furthermore, OXT concentrations showed significant heritability between ASD-discordant siblings (h2 = 85.5%); a heritability estimate on par with that of height in humans. Finally, carriers of the “G” allele of rs53576 showed impaired affect recognition performance and carriers of the “A” allele of rs2254298 exhibited greater global social impairments in all groups. These findings indicate that OXT biology is not uniquely associated with ASD, but instead exerts independent, additive, and highly heritable influences on individual differences in human social functioning, including the severe social impairments which characterize ASD. PMID:25092315

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

PubMed

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.

Unique and shared functions of nuclear lamina LEM domain proteins in Drosophila.

PubMed

Barton, Lacy J; Wilmington, Shameika R; Martin, Melinda J; Skopec, Hannah M; Lovander, Kaylee E; Pinto, Belinda S; Geyer, Pamela K

2014-06-01

The nuclear lamina is an extensive protein network that contributes to nuclear structure and function. LEM domain (LAP2, emerin, MAN1 domain, LEM-D) proteins are components of the nuclear lamina, identified by a shared ∼45-amino-acid motif that binds Barrier-to-autointegration factor (BAF), a chromatin-interacting protein. Drosophila melanogaster has three nuclear lamina LEM-D proteins, named Otefin (Ote), Bocksbeutel (Bocks), and dMAN1. Although these LEM-D proteins are globally expressed, loss of either Ote or dMAN1 causes tissue-specific defects in adult flies that differ from each other. The reason for such distinct tissue-restricted defects is unknown. Here, we generated null alleles of bocks, finding that loss of Bocks causes no overt adult phenotypes. Next, we defined phenotypes associated with lem-d double mutants. Although the absence of individual LEM-D proteins does not affect viability, loss of any two proteins causes lethality. Mutant phenotypes displayed by lem-d double mutants differ from baf mutants, suggesting that BAF function is retained in animals with a single nuclear lamina LEM-D protein. Interestingly, lem-d double mutants displayed distinct developmental and cellular mutant phenotypes, suggesting that Drosophila LEM-D proteins have developmental functions that are differentially shared with other LEM-D family members. This conclusion is supported by studies showing that ectopically produced LEM-D proteins have distinct capacities to rescue the tissue-specific phenotypes found in single lem-d mutants. Our findings predict that cell-specific mutant phenotypes caused by loss of LEM-D proteins reflect both the constellation of LEM-D proteins within the nuclear lamina and the capacity of functional compensation of the remaining LEM-D proteins. Copyright © 2014 by the Genetics Society of America.

Unique and Shared Functions of Nuclear Lamina LEM Domain Proteins in Drosophila

PubMed Central

Barton, Lacy J.; Wilmington, Shameika R.; Martin, Melinda J.; Skopec, Hannah M.; Lovander, Kaylee E.; Pinto, Belinda S.; Geyer, Pamela K.

2014-01-01

The nuclear lamina is an extensive protein network that contributes to nuclear structure and function. LEM domain (LAP2, emerin, MAN1 domain, LEM-D) proteins are components of the nuclear lamina, identified by a shared ∼45-amino-acid motif that binds Barrier-to-autointegration factor (BAF), a chromatin-interacting protein. Drosophila melanogaster has three nuclear lamina LEM-D proteins, named Otefin (Ote), Bocksbeutel (Bocks), and dMAN1. Although these LEM-D proteins are globally expressed, loss of either Ote or dMAN1 causes tissue-specific defects in adult flies that differ from each other. The reason for such distinct tissue-restricted defects is unknown. Here, we generated null alleles of bocks, finding that loss of Bocks causes no overt adult phenotypes. Next, we defined phenotypes associated with lem-d double mutants. Although the absence of individual LEM-D proteins does not affect viability, loss of any two proteins causes lethality. Mutant phenotypes displayed by lem-d double mutants differ from baf mutants, suggesting that BAF function is retained in animals with a single nuclear lamina LEM-D protein. Interestingly, lem-d double mutants displayed distinct developmental and cellular mutant phenotypes, suggesting that Drosophila LEM-D proteins have developmental functions that are differentially shared with other LEM-D family members. This conclusion is supported by studies showing that ectopically produced LEM-D proteins have distinct capacities to rescue the tissue-specific phenotypes found in single lem-d mutants. Our findings predict that cell-specific mutant phenotypes caused by loss of LEM-D proteins reflect both the constellation of LEM-D proteins within the nuclear lamina and the capacity of functional compensation of the remaining LEM-D proteins. PMID:24700158

Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.

PubMed

Gao, Shan; Chen, Weiyang; Zeng, Yingxin; Jing, Haiming; Zhang, Nan; Flavel, Matthew; Jois, Markandeya; Han, Jing-Dong J; Xian, Bo; Li, Guojun

2018-04-18

Traditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction. As these benefits allow large scale studies to be initiated with relative ease, the problem of how to efficiently capture, organize and analyze the resulting large volumes of data must be addressed. We have developed a new method for quantitative screening of chemicals using C. elegans. 33 features were identified for each chemical treatment. The compounds with different toxicities were shown to alter the phenotypes of C. elegans in distinct and detectable patterns. We found that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals. Our results demonstrate the power of phenotypic profiling in C. elegans under different chemical environments.

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

PubMed

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.

Folate network genetic variation, plasma homocysteine, and global genomic methylation content: a genetic association study

PubMed Central

2011-01-01

Background Sequence variants in genes functioning in folate-mediated one-carbon metabolism are hypothesized to lead to changes in levels of homocysteine and DNA methylation, which, in turn, are associated with risk of cardiovascular disease. Methods 330 SNPs in 52 genes were studied in relation to plasma homocysteine and global genomic DNA methylation. SNPs were selected based on functional effects and gene coverage, and assays were completed on the Illumina Goldengate platform. Age-, smoking-, and nutrient-adjusted genotype--phenotype associations were estimated in regression models. Results Using a nominal P ≤ 0.005 threshold for statistical significance, 20 SNPs were associated with plasma homocysteine, 8 with Alu methylation, and 1 with LINE-1 methylation. Using a more stringent false discovery rate threshold, SNPs in FTCD, SLC19A1, and SLC19A3 genes remained associated with plasma homocysteine. Gene by vitamin B-6 interactions were identified for both Alu and LINE-1 methylation, and epistatic interactions with the MTHFR rs1801133 SNP were identified for the plasma homocysteine phenotype. Pleiotropy involving the MTHFD1L and SARDH genes for both plasma homocysteine and Alu methylation phenotypes was identified. Conclusions No single gene was associated with all three phenotypes, and the set of the most statistically significant SNPs predictive of homocysteine or Alu or LINE-1 methylation was unique to each phenotype. Genetic variation in folate-mediated one-carbon metabolism, other than the well-known effects of the MTHFR c.665C>T (known as c.677 C>T, rs1801133, p.Ala222Val), is predictive of cardiovascular disease biomarkers. PMID:22103680

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

PubMed Central

van Zanten, Martijn

2015-01-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492

Context-sensitive network-based disease genetics prediction and its implications in drug discovery

PubMed Central

Chen, Yang; Xu, Rong

2017-01-01

Abstract Motivation: Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery. Results: We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach (p

Association of sweat chloride concentration at time of diagnosis and CFTR genotype with mortality and cystic fibrosis phenotype.

PubMed

McKone, Edward F; Velentgas, Priscilla; Swenson, Anna J; Goss, Christopher H

2015-09-01

The extent to which sweat chloride concentration predicts survival and clinical phenotype independently of CFTR genotype in cystic fibrosis is not well understood. We analyzed the US Cystic Fibrosis Foundation Patient Registry data using Cox regression to examine the relationship between sweat chloride concentration (<60, 60-<80, ≥80mmol/L), CFTR genotype (high and lower risk for lung function decline), and survival and mixed linear regression to examine the relationship between sweat chloride, CFTR genotype, and measures of lung function and growth. When included in the same model, CFTR genotype, but not sweat chloride, was independently associated with survival and with lung function, height, and BMI. Among patients with unclassified CFTR genotype, sweat chloride was an independent predictor of survival (<60 HR 0.53 [0.37, 0.77], 60-<80 0.51 [0.42, 0.63]). Sweat chloride concentration may be a useful predictor of mortality and clinical phenotype when CFTR genotype functional class is unclassified. Copyright © 2015 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

A Strong Loss-of-Function Mutation in RAN1 Results in Constitutive Activation of the Ethylene Response Pathway as Well as a Rosette-Lethal Phenotype

PubMed Central

Woeste, Keith E.; Kieber, Joseph J.

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. PMID:10715329

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

NASA Technical Reports Server (NTRS)

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.

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.

PubMed

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.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

PubMed Central

NagaSundaram, N; Priya Doss, C George

2011-01-01

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype. PMID:22190868

PRKC-ζ Expression Promotes the Aggressive Phenotype of Human Prostate Cancer Cells and Is a Novel Target for Therapeutic Intervention

PubMed Central

Yao, Sheng; Bee, Alix; Brewer, Daniel; Dodson, Andrew; Beesley, Carol; Ke, Youqiang; Ambroisine, Laurence; Fisher, Gabrielle; Møller, Heinrich; Dickinson, Tim; Gerard, Patricia; Lian, Lu-Yu; Risk, Janet; Lane, Brian; Smith, Paul; Reuter, Victor; Berney, Daniel; Gosden, Christine; Scardino, Peter; Cuzick, Jack; Djamgoz, Mustafa B.A.; Cooper, Colin; Foster, Christopher S.

2010-01-01

We show protein kinase C–zeta (PKC-ζ) to be a novel predictive biomarker for survival from prostate cancer (P < 0.001). We also confirm that transcription of the PRKC-ζ gene is crucial to the malignant phenotype of human prostate cancer. Following siRNA silencing of PRKC-ζ in PC3-M prostate cancer cells, stable transfectant cell line si-PRKC-ζ-PC3-MT1-6 is phenotypically nonmalignant in vitro and in vivo. Genome-wide expression analysis identified 373 genes to be differentially expressed in the knockdown cells and 4 key gene networks to be significantly perturbed during phenotype modulation. Functional interconnection between some of the modulated genes is revealed, although these may be within different regulatory pathways, emphasizing the complexity of their mutual interdependence. Genes with altered expression following PRKC-ζ knockdown include HSPB1, RAD51, and ID1 that we have previously described to be critical in prostatic malignancy. Because expression of PRKC-ζ is functionally involved in promoting the malignant phenotype, we propose PKC-ζ as a novel and biologically relevant target for therapeutic intervention in prostate cancer. PMID:21779455

FIG4 regulates lysosome membrane homeostasis independent of phosphatase function.

PubMed

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.

FIG4 regulates lysosome membrane homeostasis independent of phosphatase function

PubMed Central

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

2016-01-01

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. PMID:26662798

TRPC6 G757D Loss-of-Function Mutation Associates with FSGS

PubMed Central

Riehle, Marc; Büscher, Anja K.; Gohlke, Björn-Oliver; Kaßmann, Mario; Kolatsi-Joannou, Maria; Bräsen, Jan H.; Nagel, Mato; Becker, Jan U.; Winyard, Paul; Hoyer, Peter F.; Preissner, Robert; Krautwurst, Dietmar; Gollasch, Maik

2016-01-01

FSGS is a CKD with heavy proteinuria that eventually progresses to ESRD. Hereditary forms of FSGS have been linked to mutations in the transient receptor potential cation channel, subfamily C, member 6 (TRPC6) gene encoding a nonselective cation channel. Most of these TRPC6 mutations cause a gain-of-function phenotype, leading to calcium–triggered podocyte cell death, but the underlying molecular mechanisms are unclear. We studied the molecular effect of disease-related mutations using tridimensional in silico modeling of tetrameric TRPC6. Our results indicated that G757 is localized in a domain forming a TRPC6-TRPC6 interface and predicted that the amino acid exchange G757D causes local steric hindrance and disruption of the channel complex. Notably, functional characterization of model interface domain mutants suggested a loss-of-function phenotype. We then characterized 19 human FSGS–related TRPC6 mutations, the majority of which caused gain-of-function mutations. However, five mutations (N125S, L395A, G757D, L780P, and R895L) caused a loss-of-function phenotype. Coexpression of wild-type TRPC6 and TRPC6 G757D, mimicking heterozygosity observed in patients, revealed a dominant negative effect of TRPC6 G757D. Our comprehensive analysis of human disease–causing TRPC6 mutations reveals loss of TRPC6 function as an additional concept of hereditary FSGS and provides molecular insights into the mechanism responsible for the loss-of-function phenotype of TRPC6 G757D in humans. PMID:26892346

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

PubMed

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.

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

PubMed

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-type residue, whereas the minimal p.Ser112X function was explained by missense changes permitting FVII secretion and function. Conclusions The extent of functional readthrough might explain differences in the bleeding phenotype of patients homozygous for F7 nonsense mutations, and prevent null conditions even for the most readthrough-unfavorable mutations. © 2016 International Society on Thrombosis and Haemostasis.

Prenatal stress effects in a wild, long-lived primate: predictive adaptive responses in an unpredictable environment.

PubMed

Berghänel, Andreas; Heistermann, Michael; Schülke, Oliver; Ostner, Julia

2016-09-28

Prenatal maternal stress affects offspring phenotype in numerous species including humans, but it is debated whether these effects are evolutionarily adaptive. Relating stress to adverse conditions, current explanations invoke either short-term developmental constraints on offspring phenotype resulting in decelerated growth to avoid starvation, or long-term predictive adaptive responses (PARs) resulting in accelerated growth and reproduction in response to reduced life expectancies. Two PAR subtypes were proposed, acting either on predicted internal somatic states or predicted external environmental conditions, but because both affect phenotypes similarly, they are largely indistinguishable. Only external (not internal) PARs rely on high environmental stability particularly in long-lived species. We report on a crucial test case in a wild long-lived mammal, the Assamese macaque (Macaca assamensis), which evolved and lives in an unpredictable environment where external PARs are probably not advantageous. We quantified food availability, growth, motor skills, maternal caretaking style and maternal physiological stress from faecal glucocorticoid measures. Prenatal maternal stress was negatively correlated to prenatal food availability and led to accelerated offspring growth accompanied by decelerated motor skill acquisition and reduced immune function. These results support the 'internal PAR' theory, which stresses the role of stable adverse internal somatic states rather than stable external environments. © 2016 The Author(s).

CT Metrics of Airway Disease and Emphysema in Severe COPD

PubMed Central

Kim, Woo Jin; Silverman, Edwin K.; Hoffman, Eric; Criner, Gerard J.; Mosenifar, Zab; Sciurba, Frank C.; Make, Barry J.; Carey, Vincent; Estépar, Raúl San José; Diaz, Alejandro; Reilly, John J.; Martinez, Fernando J.; Washko, George R.

2009-01-01

Background: CT scan measures of emphysema and airway disease have been correlated with lung function in cohorts of subjects with a range of COPD severity. The contribution of CT scan-assessed airway disease to objective measures of lung function and respiratory symptoms such as dyspnea in severe emphysema is less clear. Methods: Using data from 338 subjects in the National Emphysema Treatment Trial (NETT) Genetics Ancillary Study, densitometric measures of emphysema using a threshold of −950 Hounsfield units (%LAA-950) and airway wall phenotypes of the wall thickness (WT) and the square root of wall area (SRWA) of a 10-mm luminal perimeter airway were calculated for each subject. Linear regression analysis was performed for outcome variables FEV1 and percent predicted value of FEV1 with CT scan measures of emphysema and airway disease. Results: In univariate analysis, there were significant negative correlations between %LAA-950 and both the WT (r = −0.28, p = 0.0001) and SRWA (r = −0.19, p = 0.0008). Airway wall thickness was weakly but significantly correlated with postbronchodilator FEV1% predicted (R = −0.12, p = 0.02). Multivariate analysis showed significant associations between either WT or SRWA (β = −5.2, p = 0.009; β = −2.6, p = 0.008, respectively) and %LAA-950 (β = −10.6, p = 0.03) with the postbronchodilator FEV1% predicted. Male subjects exhibited significantly thicker airway wall phenotypes (p = 0.007 for WT and p = 0.0006 for SRWA). Conclusions: Airway disease and emphysema detected by CT scanning are inversely related in patients with severe COPD. Airway wall phenotypes were influenced by gender and associated with lung function in subjects with severe emphysema. PMID:19411295

Predicting rates of interspecific interaction from phylogenetic trees.

PubMed

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.

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

PubMed

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.

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

PubMed Central

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

Systemic Corticosteroid Responses in Children with Severe Asthma: Phenotypic and Endotypic Features.

PubMed

Fitzpatrick, Anne M; Stephenson, Susan T; Brown, Milton R; Nguyen, Khristopher; Douglas, Shaneka; Brown, Lou Ann S

Severe asthma in children is a heterogeneous disorder associated with variable responses to corticosteroid treatment. Criterion standards for corticosteroid responsiveness assessment in children are lacking. This study sought to characterize systemic corticosteroid responses in children with severe asthma after treatment with intramuscular triamcinolone and to identify phenotypic and molecular predictors of an intramuscular triamcinolone response. Asthma-related quality of life, exhaled nitric oxide, blood eosinophils, lung function, and inflammatory cytokine and chemokine mRNA gene expression in peripheral blood mononuclear cells were assessed in 56 children with severe asthma at baseline and 14 days after intramuscular triamcinolone injection. The Asthma Control Questionnaire was used to classify children with severe asthma into corticosteroid response groups. Three groups of children with severe asthma were identified: controlled severe asthma, children who achieved control after triamcinolone, and children who did not achieve control. At baseline, these groups were phenotypically similar. After triamcinolone, discordance between symptoms, lung function, exhaled nitric oxide, and blood eosinophils was noted. Clinical phenotypic predictors were of limited utility in predicting the triamcinolone response, whereas systemic mRNA expression of inflammatory cytokines and chemokines related to IL-2, IL-10, and TNF signaling pathways, namely, AIMP1, CCR2, IL10RB, and IL5, strongly differentiated children who failed to achieve control with triamcinolone administration. Systemic corticosteroid responsiveness in children with severe asthma is heterogeneous. Alternative prediction models that include molecular endotypic as well as clinical phenotypic features are needed to identify which children derive the most clinical benefit from systemic corticosteroid step-up therapy given the potential side effects. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Design of synthetic bacterial communities for predictable plant phenotypes

PubMed Central

Herrera Paredes, Sur; Gao, Tianxiang; Law, Theresa F.; Finkel, Omri M.; Mucyn, Tatiana; Teixeira, Paulo José Pereira Lima; Salas González, Isaí; Feltcher, Meghan E.; Powers, Matthew J.; Shank, Elizabeth A.; Jones, Corbin D.; Jojic, Vladimir; Dangl, Jeffery L.; Castrillo, Gabriel

2018-01-01

Specific members of complex microbiota can influence host phenotypes, depending on both the abiotic environment and the presence of other microorganisms. Therefore, it is challenging to define bacterial combinations that have predictable host phenotypic outputs. We demonstrate that plant–bacterium binary-association assays inform the design of small synthetic communities with predictable phenotypes in the host. Specifically, we constructed synthetic communities that modified phosphate accumulation in the shoot and induced phosphate starvation–responsive genes in a predictable fashion. We found that bacterial colonization of the plant is not a predictor of the plant phenotypes we analyzed. Finally, we demonstrated that characterizing a subset of all possible bacterial synthetic communities is sufficient to predict the outcome of untested bacterial consortia. Our results demonstrate that it is possible to infer causal relationships between microbiota membership and host phenotypes and to use these inferences to rationally design novel communities. PMID:29462153

Field-based phenomics for plant genetics research

USDA-ARS?s Scientific Manuscript database

Perhaps the greatest challenge for crop research in the 21st century is how to predict crop performance as a function of genetic architecture and climate change. Advances in “next generation” DNA sequencing have greatly reduced genotyping costs. Methods for characterization of plant traits (phenotyp...

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing.

PubMed

Ghadie, Mohamed Ali; Lambourne, Luke; Vidal, Marc; Xia, Yu

2017-08-01

Alternative splicing is known to remodel protein-protein interaction networks ("interactomes"), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing

PubMed Central

Lambourne, Luke; Vidal, Marc

2017-01-01

Alternative splicing is known to remodel protein-protein interaction networks (“interactomes”), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing. PMID:28846689

Phenotypic Evolution of UNC80 Loss of Function

PubMed Central

Valkanas, Elise; Schaffer, Katherine; Dunham, Christopher; Maduro, Valerie; du Souich, Christèle; Rupps, Rosemarie; Adams, David R.; Baradaran-Heravi, Alireza; Flynn, Elise; Malicdan, May C.; Gahl, William A.; Toro, Camilo; Boerkoel, Cornelius F.

2017-01-01

Failure to thrive arises as a complication of a heterogeneous group of disorders. We describe two female siblings with spastic paraplegia and global developmental delay but also, atypically for the HSPs, poor weight gain classified as failure to thrive. After extensive clinical and biochemical investigations failed to identify the etiology, we used exome sequencing to identify biallelic UNC80 mutations (NM_032504.1:c.[3983-3_3994delinsA];[2431C>T]. The paternally inherited NM_032504.1:c.3983-3_3994delinsA is predicted to encode p.Ser1328Argfs*19 and the maternally inherited NM_032504.1:c.2431C>T is predicted to encode p.Arg811*. No UNC80 mRNA was detectable in patient cultured skin fibroblasts, suggesting UNC80 loss of function by nonsense mediated mRNA decay. Further supporting the UNC80 mutations as causative of these siblings disorder, biallelic mutations in UNC80 have recently been described among individuals with an overlapping phenotype. This report expands the disease spectrum associated with UNC80 mutations. PMID:27513830

Identification and characterization of a locus which regulates multiple functions in Pseudomonas tolaasii, the cause of brown blotch disease of Agaricus bisporus.

PubMed Central

Grewal, S I; Han, B; Johnstone, K

1995-01-01

Pseudomonas tolaasii, the causal agent of brown blotch disease of Agaricus bisporus, spontaneously gives rise to morphologically distinct stable sectors, referred to as the phenotypic variant form, at the margins of the wild-type colonies. The phenotypic variant form is nonpathogenic and differs from the wild type in a range of biochemical and physiological characteristics. A genomic cosmid clone (pSISG29) from a wild-type P. tolaasii library was shown to be capable of restoring a range of characteristics of the phenotypic variant to those of the wild-type form, when present in trans. Subcloning and saturation mutagenesis analysis with Tn5lacZ localized a 3.0-kb region from pSISG29, designated the pheN locus, required for complementation of the phenotypic variant to the wild-type form. Marker exchange of the Tn5lacZ-mutagenized copy of the pheN locus into the wild-type strain demonstrated that a functional copy of the pheN gene is required to maintain the wild-type pathogenic phenotype and that loss of the pheN gene or its function results in conversion of the wild-type form to the phenotypic variant form. The pheN locus contained a 2,727-bp open reading frame encoding an 83-kDa protein. The predicted amino acid sequence of the PheN protein showed homology to the sensor and regulator domains of the conserved family of two component bacterial sensor regulator proteins. Southern hybridization analysis of pheN genes from the wild type and the phenotypic variant form revealed that DNA rearrangement occurs within the pheN locus during phenotypic variation. Analysis of pheN expression with a pheN::lacZ fusion demonstrated that expression is regulated by environmental factors. These results are related to a model for control for phenotypic variation in P. tolaasii. PMID:7642492

Association of GSK-3β genetic variation with GSK-3β expression, prefrontal cortical thickness, prefrontal physiology, and schizophrenia.

PubMed

Blasi, Giuseppe; Napolitano, Francesco; Ursini, Gianluca; Di Giorgio, Annabella; Caforio, Grazia; Taurisano, Paolo; Fazio, Leonardo; Gelao, Barbara; Attrotto, Maria Teresa; Colagiorgio, Lucia; Todarello, Giovanna; Piva, Francesco; Papazacharias, Apostolos; Masellis, Rita; Mancini, Marina; Porcelli, Annamaria; Romano, Raffaella; Rampino, Antonio; Quarto, Tiziana; Giulietti, Matteo; Lipska, Barbara K; Kleinman, Joel E; Popolizio, Teresa; Weinberger, Daniel R; Usiello, Alessandro; Bertolino, Alessandro

2013-08-01

OBJECTIVE Glycogen synthase kinase 3β (GSK-3β) is an enzyme implicated in neurodevelopmental processes with a broad range of substrates mediating several canonical signaling pathways in the brain. The authors investigated the association of variation in the GSK-3β gene with a series of progressively more complex phenotypes of relevance to schizophrenia, a neurodevelopmental disorder with strong genetic risk. METHOD Based on computer predictions, the authors investigated in humans the association of GSK-3β functional variation with 1) GSK-3β mRNA expression from postmortem prefrontal cortex, 2) GSK-3β and β-catenin protein expression from peripheral blood mononuclear cells (PBMCs), 3) prefrontal imaging phenotypes, and 4) diagnosis of schizophrenia. RESULTS Consistent with predictions, the TT genotype of a single-nucleotide polymorphism in GSK-3β (rs12630592) was associated with reduced GSK-3β mRNA from postmortem prefrontal cortex. Furthermore, this genotype was associated with GSK-3β protein expression and kinase activity, as well as with downstream effects on β-catenin expression in PBMCs. Finally, the TT genotype was associated with attenuated functional MRI prefrontal activity, reduced prefrontal cortical thickness, and diagnosis of schizophrenia. CONCLUSIONS These results suggest that GSK-3β variation is implicated in multiple phenotypes relevant to schizophrenia.

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

Measuring the effect of inter-study variability on estimating prediction error.

PubMed

Ma, Shuyi; Sung, Jaeyun; Magis, Andrew T; Wang, Yuliang; Geman, Donald; Price, Nathan D

2014-01-01

The biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite ostensibly promising performance in predicting disease phenotypes. One widely cited reason is lack of classification consistency, largely due to failure to maintain performance from study to study. This failure is widely attributed to variability in data collected for the same phenotype among disparate studies, due to technical factors unrelated to phenotypes (e.g., laboratory settings resulting in "batch-effects") and non-phenotype-associated biological variation in the underlying populations. These sources of variability persist in new data collection technologies. Here we quantify the impact of these combined "study-effects" on a disease signature's predictive performance by comparing two types of validation methods: ordinary randomized cross-validation (RCV), which extracts random subsets of samples for testing, and inter-study validation (ISV), which excludes an entire study for testing. Whereas RCV hardwires an assumption of training and testing on identically distributed data, this key property is lost in ISV, yielding systematic decreases in performance estimates relative to RCV. Measuring the RCV-ISV difference as a function of number of studies quantifies influence of study-effects on performance. As a case study, we gathered publicly available gene expression data from 1,470 microarray samples of 6 lung phenotypes from 26 independent experimental studies and 769 RNA-seq samples of 2 lung phenotypes from 4 independent studies. We find that the RCV-ISV performance discrepancy is greater in phenotypes with few studies, and that the ISV performance converges toward RCV performance as data from additional studies are incorporated into classification. We show that by examining how fast ISV performance approaches RCV as the number of studies is increased, one can estimate when "sufficient" diversity has been achieved for learning a molecular signature likely to translate without significant loss of accuracy to new clinical settings.

New Discriminant Method for Identifying the Aggressive Disease Phenotype of Non-alcoholic Fatty Liver Disease.

PubMed

Kawamura, Yusuke; Ikeda, Kenji; Arase, Yasuji; Fujiyama, Shunichiro; Hosaka, Tetsuya; Kobayashi, Masahiro; Saitoh, Satoshi; Sezaki, Hitomi; Akuta, Norio; Suzuki, Fumitaka; Suzuki, Yoshiyuki; Kumada, Hiromitsu

2017-01-01

Objective To detect the aggressive phenotype (AP) of non-alcoholic fatty liver disease (NAFLD) based on the initial laboratory data and clinical characteristics. Methods We enrolled 144 patients with histologically proven NAFLD. For the first analysis, 24 NAFLD patients underwent repeat biopsy to establish a discriminant formula for predicting the AP of NAFLD (D-APN). The AP was defined by NAFLD that had been maintained or progressed to a fibrotic stage beyond stage 2. In the second analysis, we analyzed the distribution of the AP in each stage of disease and the incidence of the PNPLA3 rs738409 GG genotype in AP in 120 other patients. Results After the analysis, the following function was found to discriminate the disease phenotype: z=0.150×body mass index (kg/m 2 )+0.085×age (years)+1.112×ln (AST) (IU/L)+0.127×ln (m-AST)-12.96. A positive result indicates the AP of NAFLD. The discriminant functions had a positive predictive value of 94% and a negative predictive value of 71%. The distribution of the AP and the incidence of the PNPLA3 GG genotype in the AP in each stage of the disease among the 120 patients were as follows: non-alcoholic fatty liver, 30%/33%; non-alcoholic steatohepatitis (NASH) stage 1, 53%/26%; stage 2, 71%/70%; stage 3, 92%/57%; and stage 4, 93%/64%; there was a significant increase in the incidence of the AP as the disease progressed (p<0.001). Conclusion The new discriminant formula was useful for predicting disease progression potential in NAFLD patients and the incidence of the PNPLA3 GG genotype was elevated according to the distribution of AP.

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. 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 Phenotypes from Genetic Crosses: A Mathematical Concept to Help Struggling Biology Students

ERIC Educational Resources Information Center

Baurhoo, Neerusha; Darwish, Shireef

2012-01-01

Predicting phenotypic outcomes from genetic crosses is often very difficult for biology students, especially those with learning disabilities. With our mathematical concept, struggling students in inclusive biology classrooms are now better equipped to solve genetic problems and predict phenotypes, because of improved understanding of dominance…

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

PubMed Central

Liu, Jiangang; Jolly, Robert A.; Smith, Aaron T.; Searfoss, George H.; Goldstein, Keith M.; Uversky, Vladimir N.; Dunker, Keith; Li, Shuyu; Thomas, Craig E.; Wei, Tao

2011-01-01

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. PMID:21935387

Functional modules, mutational load and human genetic disease.

PubMed

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.

Functional modules, mutational load and human genetic disease

PubMed Central

Zaghloul, Norann A.; Katsanis, Nicholas

2013-01-01

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. PMID:20226561

SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments.

PubMed

Hall, Barry G

2014-01-01

SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.

Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks

DOE PAGES

Zhao, Suwen; Sakai, Ayano; Zhang, Xinshuai; ...

2014-06-30

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins inmore » 12 families in the PRS that represent ~85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.« less

CYP2D6 polymorphisms as predictors of outcome in breast cancer patients treated with tamoxifen: expanded polymorphism coverage improves risk stratification.

PubMed

Schroth, Werner; Hamann, Ute; Fasching, Peter A; Dauser, Silke; Winter, Stefan; Eichelbaum, Michel; Schwab, Matthias; Brauch, Hiltrud

2010-09-01

This study aimed to validate matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)/Taqman copy number assay (CNA) CYP2D6 genotyping by AmpliChip CYP450 Test for the prediction of tamoxifen metabolizer phenotypes in breast cancer, and to investigate the influence of CYP2D6 variant coverage on genotype-phenotype relationships and tamoxifen outcome. Hormone receptor-positive postmenopausal breast cancer patients (n = 492) treated with adjuvant tamoxifen, previously analyzed by MALDI-TOF MS/CNA, were reanalyzed by AmpliChip CYP450 Test and validated by independent methods. Cox proportional hazard ratios (HR) were calculated for recurrence of poor (PM) relative to extensive metabolizer (EM) phenotypes with increasing numbers of CYP2D6 variants. Kaplan-Meier distributions were calculated for different phenotype classifications. Concordance was 99.2% to 99.5% for CNA and 99.8% to 100% per CYP2D6 allele (*3, *4, *5, *9, *10, and *41). The prevalence of predicted phenotypes was 1.2% for ultrarapid metabolizer (UM), 37.2% for EM without variant, 43.5% for heterozygous EM, 9.7% for intermediate metabolizer (IM), and 8.3% for PM. Approximately, one third of patients were misclassified based on a *4 analysis only, but inclusion of all reduced-function alleles increased the PM-associated HR from 1.33 (P = 0.58) to 2.87 (P = 0.006). Kaplan-Meier analyses showed highest and lowest clinical benefit for UM and PM with respect to both the AmpliChip-based and a redefined phenotype assignment. The latter revealed significant allele-dose-dependent associations (P = 0.011) and largest effect size (HR(PM_EM) = 2.77; 95% confidence interval, 1.31-5.89). MALDI-TOF MS/CNA is suitable for accurate CYP2D6 genotyping. For tamoxifen pharmacogenetics, broad CYP2D6 allele coverage is recommended to reduce phenotype misclassification. Classification based on refined EM and reduced-function metabolizers is advisable. AACR.

Context-sensitive network-based disease genetics prediction and its implications in drug discovery.

PubMed

Chen, Yang; Xu, Rong

2017-04-01

Disease phenotype networks play an important role in computational approaches to identifying new disease-gene associations. Current disease phenotype networks often model disease relationships based on pairwise similarities, therefore ignore the specific context on how two diseases are connected. In this study, we propose a new strategy to model disease associations using context-sensitive networks (CSNs). We developed a CSN-based phenome-driven approach for disease genetics prediction, and investigated the translational potential of the predicted genes in drug discovery. We constructed CSNs by directly connecting diseases with associated phenotypes. Here, we constructed two CSNs using different data sources; the two networks contain 26 790 and 13 822 nodes respectively. We integrated the CSNs with a genetic functional relationship network and predicted disease genes using a network-based ranking algorithm. For comparison, we built Similarity-Based disease Networks (SBN) using the same disease phenotype data. In a de novo cross validation for 3324 diseases, the CSN-based approach significantly increased the average rank from top 12.6 to top 8.8% for all tested genes comparing with the SBN-based approach ( p

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis.

PubMed

Kooke, Rik; Kruijer, Willem; Bours, Ralph; Becker, Frank; Kuhn, André; van de Geest, Henri; Buntjer, Jaap; Doeswijk, Timo; Guerra, José; Bouwmeester, Harro; Vreugdenhil, Dick; Keurentjes, Joost J B

2016-04-01

Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified. © 2016 American Society of Plant Biologists. All Rights Reserved.

Type and Level of RMRP Functional Impairment Predicts Phenotype in the Cartilage Hair Hypoplasia–Anauxetic Dysplasia Spectrum

PubMed Central

Thiel, Christian T. ; Mortier, Geert ; Kaitila, Ilkka ; Reis, André ; Rauch, Anita 

2007-01-01

Mutations in the RMRP gene lead to a wide spectrum of autosomal recessive skeletal dysplasias, ranging from the milder phenotypes metaphyseal dysplasia without hypotrichosis and cartilage hair hypoplasia (CHH) to the severe anauxetic dysplasia (AD). This clinical spectrum includes different degrees of short stature, hair hypoplasia, defective erythrogenesis, and immunodeficiency. The RMRP gene encodes the untranslated RNA component of the mitochondrial RNA–processing ribonuclease, RNase MRP. We recently demonstrated that mutations may affect both messenger RNA (mRNA) and ribosomal RNA (rRNA) cleavage and thus cell-cycle regulation and protein synthesis. To investigate the genotype-phenotype correlation, we analyzed the position and the functional effect of 13 mutations in patients with variable features of the CHH-AD spectrum. Those at the end of the spectrum include a novel patient with anauxetic dysplasia who was compound heterozygous for the null mutation g.254_263delCTCAGCGCGG and the mutation g.195C→T, which was previously described in patients with milder phenotypes. Mapping of nucleotide conservation to the two-dimensional structure of the RMRP gene revealed that disease-causing mutations either affect evolutionarily conserved nucleotides or are likely to alter secondary structure through mispairing in stem regions. In vitro testing of RNase MRP multiprotein-specific mRNA and rRNA cleavage of different mutations revealed a strong correlation between the decrease in rRNA cleavage in ribosomal assembly and the degree of bone dysplasia, whereas reduced mRNA cleavage, and thus cell-cycle impairment, predicts the presence of hair hypoplasia, immunodeficiency, and hematological abnormalities and thus increased cancer risk. PMID:17701897

Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta

PubMed Central

Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves

2017-01-01

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI. PMID:28659819

Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta.

PubMed

Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves

2017-01-01

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene ( MMP20 ) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.

Prediction of BRCA1 and BRCA2 mutation status using post-irradiation assays of lymphoblastoid cell lines is compromised by inter-cell-line phenotypic variability.

PubMed

Lovelock, Paul K; Wong, Ee Ming; Sprung, Carl N; Marsh, Anna; Hobson, Karen; French, Juliet D; Southey, Melissa; Sculley, Tom; Pandeya, Nirmala; Brown, Melissa A; Chenevix-Trench, Georgia; Spurdle, Amanda B; McKay, Michael J

2007-09-01

Assays to determine the pathogenicity of unclassified sequence variants in disease-associated genes include the analysis of lymphoblastoid cell lines (LCLs). We assessed the ability of several assays of LCLs to distinguish carriers of germline BRCA1 and BRCA2 gene mutations from mutation-negative controls to determine their utility for use in a diagnostic setting. Post-ionising radiation cell viability and micronucleus formation, and telomere length were assayed in LCLs carrying BRCA1 or BRCA2 mutations, and in unaffected mutation-negative controls. Post-irradiation cell viability and micronucleus induction assays of LCLs from individuals carrying pathogenic BRCA1 mutations, unclassified BRCA1 sequence variants or wildtype BRCA1 sequence showed significant phenotypic heterogeneity within each group. Responses were not consistent with predicted functional consequences of known pathogenic or normal sequences. Telomere length was also highly heterogeneous within groups of LCLs carrying pathogenic BRCA1 or BRCA2 mutations, and normal BRCA1 sequences, and was not predictive of mutation status. Given the significant degree of phenotypic heterogeneity of LCLs after gamma-irradiation, and the lack of association with BRCA1 or BRCA2 mutation status, we conclude that the assays evaluated in this study should not be used as a means of differentiating pathogenic and non-pathogenic sequence variants for clinical application. We suggest that a range of normal controls must be included in any functional assays of LCLs to ensure that any observed differences between samples reflect the genotype under investigation rather than generic inter-individual variation.

GESPA: classifying nsSNPs to predict disease association.

PubMed

Khurana, Jay K; Reeder, Jay E; Shrimpton, Antony E; Thakar, Juilee

2015-07-25

Non-synonymous single nucleotide polymorphisms (nsSNPs) are the most common DNA sequence variation associated with disease in humans. Thus determining the clinical significance of each nsSNP is of great importance. Potential detrimental nsSNPs may be identified by genetic association studies or by functional analysis in the laboratory, both of which are expensive and time consuming. Existing computational methods lack accuracy and features to facilitate nsSNP classification for clinical use. We developed the GESPA (GEnomic Single nucleotide Polymorphism Analyzer) program to predict the pathogenicity and disease phenotype of nsSNPs. GESPA is a user-friendly software package for classifying disease association of nsSNPs. It allows flexibility in acceptable input formats and predicts the pathogenicity of a given nsSNP by assessing the conservation of amino acids in orthologs and paralogs and supplementing this information with data from medical literature. The development and testing of GESPA was performed using the humsavar, ClinVar and humvar datasets. Additionally, GESPA also predicts the disease phenotype associated with a nsSNP with high accuracy, a feature unavailable in existing software. GESPA's overall accuracy exceeds existing computational methods for predicting nsSNP pathogenicity. The usability of GESPA is enhanced by fast SQL-based cloud storage and retrieval of data. GESPA is a novel bioinformatics tool to determine the pathogenicity and phenotypes of nsSNPs. We anticipate that GESPA will become a useful clinical framework for predicting the disease association of nsSNPs. The program, executable jar file, source code, GPL 3.0 license, user guide, and test data with instructions are available at http://sourceforge.net/projects/gespa.

Functional wiring of the yeast kinome revealed by global analysis of genetic network motifs

PubMed Central

Sharifpoor, Sara; van Dyk, Dewald; Costanzo, Michael; Baryshnikova, Anastasia; Friesen, Helena; Douglas, Alison C.; Youn, Ji-Young; VanderSluis, Benjamin; Myers, Chad L.; Papp, Balázs; Boone, Charles; Andrews, Brenda J.

2012-01-01

A combinatorial genetic perturbation strategy was applied to interrogate the yeast kinome on a genome-wide scale. We assessed the global effects of gene overexpression or gene deletion to map an integrated genetic interaction network of synthetic dosage lethal (SDL) and loss-of-function genetic interactions (GIs) for 92 kinases, producing a meta-network of 8700 GIs enriched for pathways known to be regulated by cognate kinases. Kinases most sensitive to dosage perturbations had constitutive cell cycle or cell polarity functions under standard growth conditions. Condition-specific screens confirmed that the spectrum of kinase dosage interactions can be expanded substantially in activating conditions. An integrated network composed of systematic SDL, negative and positive loss-of-function GIs, and literature-curated kinase–substrate interactions revealed kinase-dependent regulatory motifs predictive of novel gene-specific phenotypes. Our study provides a valuable resource to unravel novel functional relationships and pathways regulated by kinases and outlines a general strategy for deciphering mutant phenotypes from large-scale GI networks. PMID:22282571

Accuracy of different bioinformatics methods in detecting antibiotic resistance and virulence factors from Staphylococcus aureus whole genome sequences.

PubMed

Mason, Amy; Foster, Dona; Bradley, Phelim; Golubchik, Tanya; Doumith, Michel; Gordon, N Claire; Pichon, Bruno; Iqbal, Zamin; Staves, Peter; Crook, Derrick; Walker, A Sarah; Kearns, Angela; Peto, Tim

2018-06-20

Background : In principle, whole genome sequencing (WGS) can predict phenotypic resistance directly from genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. Methods : We compared three WGS-based bioinformatics methods (Genefinder (read-based), Mykrobe (de Bruijn graph-based) and Typewriter (BLAST-based)) for predicting presence/absence of 83 different resistance determinants and virulence genes, and overall antimicrobial susceptibility, in 1379 Staphylococcus aureus isolates previously characterised by standard laboratory methods (disc diffusion, broth and/or agar dilution and PCR). Results : 99.5% (113830/114457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fliess-Kappa=0.98, p<0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b ). Genotypic antimicrobial susceptibility prediction matched laboratory phenotype in 98.3% (14224/14464) cases (2720 (18.8%) resistant, 11504 (79.5%) susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 (0.7%) phenotypically-susceptible but all bioinformatic methods reported resistance; 89 (0.6%) phenotypically-resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 (0.4%) cases, 16 phenotypically-resistant, 38 phenotypically-susceptible). However, in 36/54 (67%), the consensus genotype matched the laboratory phenotype. Conclusions : In this study, the choice between these three specific bioinformatic methods to identify resistance-determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations and therefore consensus methods provide some assurance. Copyright © 2018 American Society for Microbiology.

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

A novel test of the phenotype-linked fertility hypothesis reveals independent components of fertility.

PubMed Central

Pizzari, Tommaso; Jensen, Per; Cornwallis, Charles K.

2004-01-01

The phenotype-linked fertility hypothesis predicts that male sexual ornaments signal fertilizing efficiency and that the coevolution of male ornaments and female preference for such ornaments is driven by female pursuit of fertility benefits. In addition, directional testicular asymmetry frequently observed in birds has been suggested to reflect fertilizing efficiency and to covary with ornament expression. However, the idea of a phenotypic relationship between male ornaments and fertilizing efficiency is often tested in populations where environmental effects mask the underlying genetic associations between ornaments and fertilizing efficiency implied by this idea. Here, we adopt a novel design, which increases genetic diversity through the crossing of two divergent populations while controlling for environmental effects, to test: (i) the phenotypic relationship between male ornaments and both, gonadal (testicular mass) and gametic (sperm quality) components of fertilizing efficiency; and (ii) the extent to which these components are phenotypically integrated in the fowl, Gallus gallus. We show that consistent with theory, the testosterone-dependent expression of a male ornament, the comb, predicted testicular mass. However, despite their functional inter-dependence, testicular mass and sperm quality were not phenotypically integrated. Consistent with this result, males of one parental population invested more in testicular and comb mass, whereas males of the other parental population had higher sperm quality. We found no evidence that directional testicular asymmetry covaried with ornament expression. These results shed new light on the evolutionary relationship between male fertilizing efficiency and ornaments. Although testosterone-dependent ornaments may covary with testicular mass and thus reflect sperm production rate, the lack of phenotypic integration between gonadal and gametic traits reveals that the expression of an ornament is unlikely to reflect the overall fertilizing efficiency of a male. PMID:15002771

A phenotype of early infancy predicts reactivity of the amygdala in male adults.

PubMed

Schwartz, C E; Kunwar, P S; Greve, D N; Kagan, J; Snidman, N C; Bloch, R B

2012-10-01

One of the central questions that has occupied those disciplines concerned with human development is the nature of continuities and discontinuities from birth to maturity. The amygdala has a central role in the processing of novelty and emotion in the brain. Although there is considerable variability among individuals in the reactivity of the amygdala to novel and emotional stimuli, the origin of these individual differences is not well understood. Four-month old infants called high reactive (HR) demonstrate a distinctive pattern of vigorous motor activity and crying to specific unfamiliar visual, auditory and olfactory stimuli in the laboratory. Low-reactive infants show the complementary pattern. Here, we demonstrate that the HR infant phenotype predicts greater amygdalar reactivity to novel faces almost two decades later in adults. A prediction of individual differences in brain function at maturity can be made on the basis of a single behavioral assessment made in the laboratory at 4 months of age. This is the earliest known human behavioral phenotype that predicts individual differences in patterns of neural activity at maturity. These temperamental differences rooted in infancy may be relevant to understanding individual differences in vulnerability and resilience to clinical psychiatric disorder. Males who were HR infants showed particularly high levels of reactivity to novel faces in the amygdala that distinguished them as adults from all other sex/temperament subgroups, suggesting that their amygdala is particularly prone to engagement by unfamiliar faces. These findings underline the importance of taking gender into account when studying the developmental neurobiology of human temperament and anxiety disorders. The genetic study of behavioral and biologic intermediate phenotypes (or 'endophenotypes') indexing anxiety-proneness offers an important alternative to examining phenotypes based on clinically defined disorder. As the HR phenotype is characterized by specific patterns of reactivity to elemental visual, olfactory and auditory stimuli, well before complex social behaviors such as shyness or fearful interaction with strangers can be observed, it may be closer to underlying neurobiological mechanisms than behavioral profiles observed later in life. This possibility, together with the fact that environmental factors have less time to impact the 4-month phenotype, suggests that this temperamental profile may be a fruitful target for high-risk genetic studies.

Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen

PubMed Central

Adissu, Hibret A.; Estabel, Jeanne; Sunter, David; Tuck, Elizabeth; Hooks, Yvette; Carragher, Damian M.; Clarke, Kay; Karp, Natasha A.; Project, Sanger Mouse Genetics; Newbigging, Susan; Jones, Nora; Morikawa, Lily; White, Jacqueline K.; McKerlie, Colin

2014-01-01

The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice. PMID:24652767

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

PubMed

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.

De novo PHIP-predicted deleterious variants are associated with developmental delay, intellectual disability, obesity, and dysmorphic features.

PubMed

Webster, Emily; Cho, Megan T; Alexander, Nora; Desai, Sonal; Naidu, Sakkubai; Bekheirnia, Mir Reza; Lewis, Andrea; Retterer, Kyle; Juusola, Jane; Chung, Wendy K

2016-11-01

Using whole-exome sequencing, we have identified novel de novo heterozygous pleckstrin homology domain-interacting protein ( PHIP ) variants that are predicted to be deleterious, including a frameshift deletion, in two unrelated patients with common clinical features of developmental delay, intellectual disability, anxiety, hypotonia, poor balance, obesity, and dysmorphic features. A nonsense mutation in PHIP has previously been associated with similar clinical features. Patients with microdeletions of 6q14.1, including PHIP , have a similar phenotype of developmental delay, intellectual disability, hypotonia, and obesity, suggesting that the phenotype of our patients is a result of loss-of-function mutations. PHIP produces multiple protein products, such as PHIP1 (also known as DCAF14), PHIP, and NDRP. PHIP1 is one of the multiple substrate receptors of the proteolytic CUL4-DDB1 ubiquitin ligase complex. CUL4B deficiency has been associated with intellectual disability, central obesity, muscle wasting, and dysmorphic features. The overlapping phenotype associated with CUL4B deficiency suggests that PHIP mutations cause disease through disruption of the ubiquitin ligase pathway.

RHO Mutations (p.W126L and p.A346P) in Two Japanese Families with Autosomal Dominant Retinitis Pigmentosa

PubMed Central

Akahori, Masakazu; Itabashi, Takeshi; Nishino, Jo; Yoshitake, Kazutoshi; Ikeo, Kazuho; Tsuneoka, Hiroshi

2014-01-01

Purpose. To investigate genetic and clinical features of patients with rhodopsin (RHO) mutations in two Japanese families with autosomal dominant retinitis pigmentosa (adRP). Methods. Whole-exome sequence analysis was performed in ten adRP families. Identified RHO mutations for the cosegregation analysis were confirmed by Sanger sequencing. Ophthalmic examinations were performed to evaluate the RP phenotypes. The impact of the RHO mutation on the rhodopsin conformation was examined by molecular modeling analysis. Results. In two adRP families, we identified two RHO mutations (c.377G>T (p.W126L) and c.1036G>C (p.A346P)), one of which was novel. Complete cosegregation was confirmed for each mutation exhibiting the RP phenotype in both families. Molecular modeling predicted that the novel mutation (p.W126L) might impair rhodopsin function by affecting its conformational transition in the light-adapted form. Clinical phenotypes showed that patients with p.W126L exhibited sector RP, whereas patients with p.A346P exhibited classic RP. Conclusions. Our findings demonstrated that the novel mutation (p.W126L) may be associated with the phenotype of sector RP. Identification of RHO mutations is a very useful tool for predicting disease severity and providing precise genetic counseling. PMID:25485142

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

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

PubMed

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.

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

Functional studies of novel CYP21A2 mutations detected in Norwegian patients with congenital adrenal hyperplasia

PubMed Central

Brønstad, Ingeborg; Breivik, Lars; Methlie, Paal; Wolff, Anette S B; Bratland, Eirik; Nermoen, Ingrid; Løvås, Kristian; Husebye, Eystein S

2014-01-01

In about 95% of cases, congenital adrenal hyperplasia (CAH) is caused by mutations in CYP21A2 gene encoding steroid 21-hydroxylase (21OH). Recently, we have reported four novel CYP21A2 variants in the Norwegian population of patients with CAH, of which p.L388R and p.E140K were associated with salt wasting (SW), p.P45L with simple virilising (SV) and p.V211M+p.V281L with SV to non-classical (NC) phenotypes. We aimed to characterise the novel variants functionally utilising a newly designed in vitro assay of 21OH enzyme activity and structural simulations and compare the results with clinical phenotypes. CYP21A2 mutations and variants were expressed in vitro. Enzyme activity was assayed by assessing the conversion of 17-hydroxyprogesterone to 11-deoxycortisol by liquid chromatography tandem mass spectroscopy. PyMOL 1.3 was used for structural simulations, and PolyPhen2 and PROVEAN for predicting the severity of the mutants. The CYP21A2 mutants, p.L388R and p.E140K, exhibited 1.1 and 11.3% of wt 21OH enzyme activity, respectively, in vitro. We could not detect any functional deficiency of the p.P45L variant in vitro; although prediction tools suggest p.P45L to be pathogenic. p.V211M displayed enzyme activity equivalent to the wt in vitro, which was supported by in silico analyses. We found good correlations between phenotype and the in vitro enzyme activities of the SW mutants, but not for the SV p.P45L variant. p.V211M might have a synergistic effect together with p.V281L, explaining a phenotype between SV and NC CAH. PMID:24671123

Novel strategies to enforce an epithelial phenotype in mesenchymal cells

PubMed Central

Dragoi, Ana-Maria; Swiss, Rachel; Gao, Beile; Agaisse, Hervé

2014-01-01

E-cadherin downregulation in cancer cells is associated with epithelial-to-mesenchymal transition (EMT) and metastatic prowess, but the underlying mechanisms are incompletely characterized. In this study, we probed E-cadherin expression at the plasma membrane as a functional assay to identify genes involved in E-cadherin downregulation. The assay was based on the E-cadherin-dependent invasion properties of the intracellular pathogen Listeria monocytogenes. On the basis of a functional readout, automated microscopy and computer-assisted image analysis were used to screen siRNAs targeting 7,000 human genes. The validity of the screen was supported by its definion of several known regulators of E-cadherin expression, including ZEB1, HDAC1 and MMP14. We identified three new regulators (FLASH, CASP7 and PCGF1), the silencing of which was sufficient to restore high levels of E-cadherin transcription. Additionally, we identified two new regulators (FBXL5 and CAV2), the silencing of which was sufficient to increase E-cadherin expression at a post-transcriptional level. FLASH silencing regulated the expression of E-cadherin and other ZEB1-dependent genes, through post-transcriptional regulation of ZEB1, but it also regulated the expression of numerous ZEB1-independent genes with functions predicted to contribute to a restoration of the epithelial phenotype. Finally, we also report the identification of siRNA duplexes that potently restored the epithelial phenotype by mimicking the activity of known and putative microRNAs. Our findings suggest new ways to enforce epithelial phenotypes as a general strategy to treat cancer by blocking invasive and metastatic phenotypes associated with EMT. PMID:24845104

Urokinase Receptor Counteracts Vascular Smooth Muscle Cell Functional Changes Induced by Surface Topography

PubMed Central

Kiyan, Yulia; Kurselis, Kestutis; Kiyan, Roman; Haller, Hermann; Chichkov, Boris N.; Dumler, Inna

2013-01-01

Current treatments for human coronary artery disease necessitate the development of the next generations of vascular bioimplants. Recent reports provide evidence that controlling cell orientation and morphology through topographical patterning might be beneficial for bioimplants and tissue engineering scaffolds. However, a concise understanding of cellular events underlying cell-biomaterial interaction remains missing. In this study, applying methods of laser material processing, we aimed to obtain useful markers to guide in the choice of better vascular biomaterials. Our data show that topographically treated human primary vascular smooth muscle cells (VSMC) have a distinct differentiation profile. In particular, cultivation of VSMC on the microgrooved biocompatible polymer E-shell induces VSMC modulation from synthetic to contractile phenotype and directs formation and maintaining of cell-cell communication and adhesion structures. We show that the urokinase receptor (uPAR) interferes with VSMC behavior on microstructured surfaces and serves as a critical regulator of VSMC functional fate. Our findings suggest that microtopography of the E-shell polymer could be important in determining VSMC phenotype and cytoskeleton organization. They further suggest uPAR as a useful target in the development of predictive models for clinical VSMC phenotyping on functional advanced biomaterials. PMID:23843899

Discovering cancer vulnerabilities using high-throughput micro-RNA screening.

PubMed

Nikolic, Iva; Elsworth, Benjamin; Dodson, Eoin; Wu, Sunny Z; Gould, Cathryn M; Mestdagh, Pieter; Marshall, Glenn M; Horvath, Lisa G; Simpson, Kaylene J; Swarbrick, Alexander

2017-12-15

Micro-RNAs (miRNAs) are potent regulators of gene expression and cellular phenotype. Each miRNA has the potential to target hundreds of transcripts within the cell thus controlling fundamental cellular processes such as survival and proliferation. Here, we exploit this important feature of miRNA networks to discover vulnerabilities in cancer phenotype, and map miRNA-target relationships across different cancer types. More specifically, we report the results of a functional genomics screen of 1280 miRNA mimics and inhibitors in eight cancer cell lines, and its presentation in a sophisticated interactive data portal. This resource represents the most comprehensive survey of miRNA function in oncology, incorporating breast cancer, prostate cancer and neuroblastoma. A user-friendly web portal couples this experimental data with multiple tools for miRNA target prediction, pathway enrichment analysis and visualization. In addition, the database integrates publicly available gene expression and perturbation data enabling tailored and context-specific analysis of miRNA function in a particular disease. As a proof-of-principle, we use the database and its innovative features to uncover novel determinants of the neuroblastoma malignant phenotype. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of functional importance of binding sites in the Drosophila gap gene network model.

PubMed

Kozlov, Konstantin; Gursky, Vitaly V; Kulakovskiy, Ivan V; Dymova, Arina; Samsonova, Maria

2015-01-01

The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

PubMed Central

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Beyond BMI: Conceptual Issues Related to Overweight and Obese Patients

PubMed Central

Müller, Manfred James; Braun, Wiebke; Enderle, Janna; Bosy-Westphal, Anja

2016-01-01

BMI is widely used as a measure of weight status and disease risks; it defines overweight and obesity based on statistical criteria. BMI is a score; neither is it biologically sound nor does it reflect a suitable phenotype worthwhile to study. Because of its limited value, BMI cannot provide profound insight into obesity biology and its co-morbidity. Alternative assessments of weight status include detailed phenotyping by body composition analysis (BCA). However, predicting disease risks, fat mass, and fat-free mass as assessed by validated techniques (i.e., densitometry, dual energy X ray absorptiometry, and bioelectrical impedance analysis) does not exceed the value of BMI. Going beyond BMI and descriptive BCA, the concept of functional body composition (FBC) integrates body components into regulatory systems. FBC refers to the masses of body components, organs, and tissues as well as to their inter-relationships within the context of endocrine, metabolic and immune functions. FBC can be used to define specific phenotypes of obesity, e.g. the sarcopenic-obese patient. Well-characterized obesity phenotypes are a precondition for targeted research (e.g., on the genomics of obesity) and patient-centered care (e.g., adequate treatment of individual obese phenotypes such as the sarcopenic-obese patient). FBC contributes to a future definition of overweight and obesity based on physiological criteria rather than on body weight alone. PMID:27286962

Genetic dissection of ethanol tolerance in the budding yeast Saccharomyces cerevisiae.

PubMed

Hu, X H; Wang, M H; Tan, T; Li, J R; Yang, H; Leach, L; Zhang, R M; Luo, Z W

2007-03-01

Uncovering genetic control of variation in ethanol tolerance in natural populations of yeast Saccharomyces cerevisiae is essential for understanding the evolution of fermentation, the dominant lifestyle of the species, and for improving efficiency of selection for strains with high ethanol tolerance, a character of great economic value for the brewing and biofuel industries. To date, as many as 251 genes have been predicted to be involved in influencing this character. Candidacy of these genes was determined from a tested phenotypic effect following gene knockout, from an induced change in gene function under an ethanol stress condition, or by mutagenesis. This article represents the first genomics approach for dissecting genetic variation in ethanol tolerance between two yeast strains with a highly divergent trait phenotype. We developed a simple but reliable experimental protocol for scoring the phenotype and a set of STR/SNP markers evenly covering the whole genome. We created a mapping population comprising 319 segregants from crossing the parental strains. On the basis of the data sets, we find that the tolerance trait has a high heritability and that additive genetic variance dominates genetic variation of the trait. Segregation at five QTL detected has explained approximately 50% of phenotypic variation; in particular, the major QTL mapped on yeast chromosome 9 has accounted for a quarter of the phenotypic variation. We integrated the QTL analysis with the predicted candidacy of ethanol resistance genes and found that only a few of these candidates fall in the QTL regions.

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

PubMed

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 (P = 0.011). The PP algorithm performed significantly better (P < 0.001) than traditional machine learning algorithms for both short- and long-term asthma control prediction. Asthma control and bronchodilator response were the features most predictive of short-term asthma control, regardless of type of controller medication or phenotype. Bronchodilator response and serum eosinophils were the most predictive features of asthma control, regardless of type of controller medication or phenotype. Advanced statistical machine learning approaches can be powerful tools for discovery of phenotypes based on treatment response and can aid in asthma control prediction in complex medical conditions such as asthma.

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

PubMed Central

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

Ehlers-Danlos syndrome with lethal cardiac valvular dystrophy in males carrying a novel splice mutation in FLNA.

PubMed

Ritelli, Marco; Morlino, Silvia; Giacopuzzi, Edoardo; Carini, Giulia; Cinquina, Valeria; Chiarelli, Nicola; Majore, Silvia; Colombi, Marina; Castori, Marco

2017-01-01

Filamin A is an X-linked, ubiquitous actin-binding protein whose mutations are associated to multiple disorders with limited genotype-phenotype correlations. While gain-of-function mutations cause various bone dysplasias, loss-of-function variants are the most common cause of periventricular nodular heterotopias with variable soft connective tissue involvement, as well as X-linked cardiac valvular dystrophy (XCVD). The term "Ehlers-Danlos syndrome (EDS) with periventricular heterotopias" has been used in females with neurological, cardiovascular, integument and joint manifestations, but this nosology is still a matter of debate. We report the clinical and molecular update of an Italian family with an X-linked recessive soft connective tissue disorder and which was described, in 1975, as the first example of EDS type V of the Berlin nosology. The cutaneous phenotype of the index patient was close to classical EDS and all males died for a lethal cardiac valvular dystrophy. Whole exome sequencing identified the novel c.1829-1G>C splice variation in FLNA in two affected cousins. The nucleotide change was predicted to abolish the canonical splice acceptor site of exon 13 and to activate a cryptic acceptor site 15 bp downstream, leading to in frame deletion of five amino acid residues (p.Phe611_Gly615del). The predicted in frame deletion clusters with all the mutations previously identified in XCVD and falls within the N-terminus rod 1 domain of filamin A. Our findings expand the male-specific phenotype of FLNA mutations that now includes classical-like EDS with lethal cardiac valvular dystrophy, and offer further insights for the genotype-phenotype correlations within this spectrum. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A probabilistic model to predict clinical phenotypic traits from genome sequencing.

PubMed

Chen, Yun-Ching; Douville, Christopher; Wang, Cheng; Niknafs, Noushin; Yeo, Grace; Beleva-Guthrie, Violeta; Carter, Hannah; Stenson, Peter D; Cooper, David N; Li, Biao; Mooney, Sean; Karchin, Rachel

2014-09-01

Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina's Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Genetic contributions to variation in general cognitive function: a meta-analysis of genome-wide association studies in the CHARGE consortium (N=53 949)

PubMed Central

Davies, G; Armstrong, N; Bis, J C; Bressler, J; Chouraki, V; Giddaluru, S; Hofer, E; Ibrahim-Verbaas, C A; Kirin, M; Lahti, J; van der Lee, S J; Le Hellard, S; Liu, T; Marioni, R E; Oldmeadow, C; Postmus, I; Smith, A V; Smith, J A; Thalamuthu, A; Thomson, R; Vitart, V; Wang, J; Yu, L; Zgaga, L; Zhao, W; Boxall, R; Harris, S E; Hill, W D; Liewald, D C; Luciano, M; Adams, H; Ames, D; Amin, N; Amouyel, P; Assareh, A A; Au, R; Becker, J T; Beiser, A; Berr, C; Bertram, L; Boerwinkle, E; Buckley, B M; Campbell, H; Corley, J; De Jager, P L; Dufouil, C; Eriksson, J G; Espeseth, T; Faul, J D; Ford, I; Scotland, Generation; Gottesman, R F; Griswold, M E; Gudnason, V; Harris, T B; Heiss, G; Hofman, A; Holliday, E G; Huffman, J; Kardia, S L R; Kochan, N; Knopman, D S; Kwok, J B; Lambert, J-C; Lee, T; Li, G; Li, S-C; Loitfelder, M; Lopez, O L; Lundervold, A J; Lundqvist, A; Mather, K A; Mirza, S S; Nyberg, L; Oostra, B A; Palotie, A; Papenberg, G; Pattie, A; Petrovic, K; Polasek, O; Psaty, B M; Redmond, P; Reppermund, S; Rotter, J I; Schmidt, H; Schuur, M; Schofield, P W; Scott, R J; Steen, V M; Stott, D J; van Swieten, J C; Taylor, K D; Trollor, J; Trompet, S; Uitterlinden, A G; Weinstein, G; Widen, E; Windham, B G; Jukema, J W; Wright, A F; Wright, M J; Yang, Q; Amieva, H; Attia, J R; Bennett, D A; Brodaty, H; de Craen, A J M; Hayward, C; Ikram, M A; Lindenberger, U; Nilsson, L-G; Porteous, D J; Räikkönen, K; Reinvang, I; Rudan, I; Sachdev, P S; Schmidt, R; Schofield, P R; Srikanth, V; Starr, J M; Turner, S T; Weir, D R; Wilson, J F; van Duijn, C; Launer, L; Fitzpatrick, A L; Seshadri, S; Mosley, T H; Deary, I J

2015-01-01

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N=53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P=3.93 × 10−9, MIR2113; rs17522122, P=2.55 × 10−8, AKAP6; rs10119, P=5.67 × 10−9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1 × 10−6). These genes have previously been associated with neuropsychiatric phenotypes. Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N=6617) and the Health and Retirement Study (N=5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e.=5%) and 28% (s.e.=7%), respectively. Using polygenic prediction analysis, ~1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N=5487; P=1.5 × 10−17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer's disease: TOMM40, APOE, ABCG1 and MEF2C. PMID:25644384

Mutations in the Arabidopsis Peroxisomal ABC Transporter COMATOSE Allow Differentiation between Multiple Functions In Planta: Insights from an Allelic Series

PubMed Central

Dietrich, Daniela; Schmuths, Heike; Lousa, Carine De Marcos; Baldwin, Jocelyn M.; Baldwin, Stephen A.; Baker, Alison; Holdsworth, Michael J.

2009-01-01

COMATOSE (CTS), the Arabidopsis homologue of human Adrenoleukodystrophy protein (ALDP), is required for import of substrates for peroxisomal β-oxidation. A new allelic series and a homology model based on the bacterial ABC transporter, Sav1866, provide novel insights into structure-function relations of ABC subfamily D proteins. In contrast to ALDP, where the majority of mutations result in protein absence from the peroxisomal membrane, all CTS mutants produced stable protein. Mutation of conserved residues in the Walker A and B motifs in CTS nucleotide-binding domain (NBD) 1 resulted in a null phenotype but had little effect in NBD2, indicating that the NBDs are functionally distinct in vivo. Two alleles containing mutations in NBD1 outside the Walker motifs (E617K and C631Y) exhibited resistance to auxin precursors 2,4-dichlorophenoxybutyric acid (2,4-DB) and indole butyric acid (IBA) but were wild type in all other tests. The homology model predicted that the transmission interfaces are domain-swapped in CTS, and the differential effects of mutations in the conserved “EAA motif” of coupling helix 2 supported this prediction, consistent with distinct roles for each NBD. Our findings demonstrate that CTS functions can be separated by mutagenesis and the structural model provides a framework for interpretation of phenotypic data. PMID:19019987

A comprehensive study of small non-frameshift insertions/deletions in proteins and prediction of their phenotypic effects by a machine learning method (KD4i)

PubMed Central

2014-01-01

Background Small insertion and deletion polymorphisms (Indels) are the second most common mutations in the human genome, after Single Nucleotide Polymorphisms (SNPs). Recent studies have shown that they have significant influence on genetic variation by altering human traits and can cause multiple human diseases. In particular, many Indels that occur in protein coding regions are known to impact the structure or function of the protein. A major challenge is to predict the effects of these Indels and to distinguish between deleterious and neutral variants. When an Indel occurs within a coding region, it can be either frameshifting (FS) or non-frameshifting (NFS). FS-Indels either modify the complete C-terminal region of the protein or result in premature termination of translation. NFS-Indels insert/delete multiples of three nucleotides leading to the insertion/deletion of one or more amino acids. Results In order to study the relationships between NFS-Indels and Mendelian diseases, we characterized NFS-Indels according to numerous structural, functional and evolutionary parameters. We then used these parameters to identify specific characteristics of disease-causing and neutral NFS-Indels. Finally, we developed a new machine learning approach, KD4i, that can be used to predict the phenotypic effects of NFS-Indels. Conclusions We demonstrate in a large-scale evaluation that the accuracy of KD4i is comparable to existing state-of-the-art methods. However, a major advantage of our approach is that we also provide the reasons for the predictions, in the form of a set of rules. The rules are interpretable by non-expert humans and they thus represent new knowledge about the relationships between the genotype and phenotypes of NFS-Indels and the causative molecular perturbations that result in the disease. PMID:24742296

A Framework for Integrating Multiple Biological Networks to Predict MicroRNA-Disease Associations.

PubMed

Peng, Wei; Lan, Wei; Yu, Zeng; Wang, Jianxin; Pan, Yi

2017-03-01

MicroRNAs have close relationship with human diseases. Therefore, identifying disease related MicroRNAs plays an important role in disease diagnosis, prognosis and therapy. However, designing an effective computational method which can make good use of various biological resources and correctly predict the associations between MicroRNA and disease is still a big challenge. Previous researchers have pointed out that there are complex relationships among microRNAs, diseases and environment factors. There are inter-relationships between microRNAs, diseases or environment factors based on their functional similarity or phenotype similarity or chemical structure similarity and so on. There are also intra-relationships between microRNAs and diseases, microRNAs and environment factors, diseases and environment factors. Moreover, functionally similar microRNAs tend to associate with common diseases and common environment factors. The diseases with similar phenotypes are likely caused by common microRNAs and common environment factors. In this work, we propose a framework namely ThrRWMDE which can integrate these complex relationships to predict microRNA-disease associations. In this framework, microRNA similarity network (MFN), disease similarity network (DSN) and environmental factor similarity network (ESN) are constructed according to certain biological properties. Then, an unbalanced three random walking algorithm is implemented on the three networks so as to obtain information from neighbors in corresponding networks. This algorithm not only can flexibly infer information from different levels of neighbors with respect to the topological and structural differences of the three networks, but also in the course of working the functional information will be transferred from one network to another according to the associations between the nodes in different networks. The results of experiment show that our method achieves better prediction performance than other state-of-the-art methods.

Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Akgöl, Batuhan; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2017-02-01

Early generation genomic selection is superior to conventional phenotypic selection in line breeding and can be strongly improved by including additional information from preliminary yield trials. The selection of lines that enter resource-demanding multi-environment trials is a crucial decision in every line breeding program as a large amount of resources are allocated for thoroughly testing these potential varietal candidates. We compared conventional phenotypic selection with various genomic selection approaches across multiple years as well as the merit of integrating phenotypic information from preliminary yield trials into the genomic selection framework. The prediction accuracy using only phenotypic data was rather low (r = 0.21) for grain yield but could be improved by modeling genetic relationships in unreplicated preliminary yield trials (r = 0.33). Genomic selection models were nevertheless found to be superior to conventional phenotypic selection for predicting grain yield performance of lines across years (r = 0.39). We subsequently simplified the problem of predicting untested lines in untested years to predicting tested lines in untested years by combining breeding values from preliminary yield trials and predictions from genomic selection models by a heritability index. This genomic assisted selection led to a 20% increase in prediction accuracy, which could be further enhanced by an appropriate marker selection for both grain yield (r = 0.48) and protein content (r = 0.63). The easy to implement and robust genomic assisted selection gave thus a higher prediction accuracy than either conventional phenotypic or genomic selection alone. The proposed method took the complex inheritance of both low and high heritable traits into account and appears capable to support breeders in their selection decisions to develop enhanced varieties more efficiently.

Risk factors of treatment failure and 30-day mortality in patients with bacteremia due to MRSA with reduced vancomycin susceptibility.

PubMed

Yang, Chien-Chang; Sy, Cheng-Len; Huang, Yhu-Chering; Shie, Shian-Sen; Shu, Jwu-Ching; Hsieh, Pang-Hsin; Hsiao, Ching-Hsi; Chen, Chih-Jung

2018-05-18

Bacteremia caused by MRSA with reduced vancomycin susceptibility (MRSA-RVS) frequently resulted in treatment failure and mortality. The relation of bacterial factors and unfavorable outcomes remains controversial. We retrospectively reviewed clinical data of patients with bacteremia caused by MRSA with vancomycin MIC = 2 mg/L from 2009 to 2012. The significance of bacterial genotypes, agr function and heterogeneous vancomycin-intermediate S. aureus (hIVSA) phenotype in predicting outcomes were determined after clinical covariates adjustment with multivariate analysis. A total of 147 patients with mean age of 63.5 (±18.1) years were included. Seventy-nine (53.7%) patients failed treatment. Forty-seven (31.9%) patients died within 30 days of onset of MRSA bacteremia. The Charlson index, Pitt bacteremia score and definitive antibiotic regimen were independent factors significantly associated with either treatment failure or mortality. The hVISA phenotype was a potential risk factor predicting treatment failure (adjusted odds ratio 2.420, 95% confidence interval 0.946-6.191, P = 0.0652). No bacterial factors were significantly associated with 30-day mortality. In conclusion, the comorbidities, disease severity and antibiotic regimen remained the most relevant factors predicting treatment failure and 30-day mortality in patients with MRSA-RVS bacteremia. hIVSA phenotype was the only bacterial factor potentially associated with unfavorable outcome in this cohort.

Global Genetic Variations Predict Brain Response to Faces

PubMed Central

Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

2014-01-01

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

Allelic hierarchy of CDH23 mutations causing non-syndromic deafness DFNB12 or Usher syndrome USH1D in compound heterozygotes.

PubMed

Schultz, Julie M; Bhatti, Rashid; Madeo, Anne C; Turriff, Amy; Muskett, Julie A; Zalewski, Christopher K; King, Kelly A; Ahmed, Zubair M; Riazuddin, Saima; Ahmad, Nazir; Hussain, Zawar; Qasim, Muhammad; Kahn, Shaheen N; Meltzer, Meira R; Liu, Xue Z; Munisamy, Murali; Ghosh, Manju; Rehm, Heidi L; Tsilou, Ekaterini T; Griffith, Andrew J; Zein, Wadih M; Brewer, Carmen C; Riazuddin, Sheikh; Friedman, Thomas B

2011-11-01

Recessive mutant alleles of MYO7A, USH1C, CDH23, and PCDH15 cause non-syndromic deafness or type 1 Usher syndrome (USH1) characterised by deafness, vestibular areflexia, and vision loss due to retinitis pigmentosa. For CDH23, encoding cadherin 23, non-syndromic DFNB12 deafness is associated primarily with missense mutations hypothesised to have residual function. In contrast, homozygous nonsense, frame shift, splice site, and some missense mutations of CDH23, all of which are presumably functional null alleles, cause USH1D. The phenotype of a CDH23 compound heterozygote for a DFNB12 allele in trans configuration to an USH1D allele is not known and cannot be predicted from current understanding of cadherin 23 function in the retina and vestibular labyrinth. To address this issue, this study sought CDH23 compound heterozygotes by sequencing this gene in USH1 probands, and families segregating USH1D or DFNB12. Five non-syndromic deaf individuals were identified with normal retinal and vestibular phenotypes that segregate compound heterozygous mutations of CDH23, where one mutation is a known or predicted USH1 allele. One DFNB12 allele in trans configuration to an USH1D allele of CDH23 preserves vision and balance in deaf individuals, indicating that the DFNB12 allele is phenotypically dominant to an USH1D allele. This finding has implications for genetic counselling and the development of therapies for retinitis pigmentosa in Usher syndrome. ACCESSION NUMBERS: The cDNA and protein Genbank accession numbers for CDH23 and cadherin 23 used in this paper are AY010111.2 and AAG27034.2, respectively.

The fibromyalgia survey score correlates with preoperative pain phenotypes but does not predict pain outcomes after shoulder arthroscopy

PubMed Central

Cheng, Jennifer; Kahn, Richard L.; YaDeau, Jacques T.; Tsodikov, Alexander; Goytizolo, Enrique A.; Guheen, Carrie R.; Haskins, Stephen C.; Oxendine, Joseph A.; Allen, Answorth A.; Gulotta, Lawrence V.; Dines, David M.; Brummett, Chad M.

2015-01-01

Objectives Fibromyalgia characteristics can be evaluated using a simple, self-reported measure, which correlates with postoperative opioid consumption following lower-extremity joint arthroplasty. The purpose of this study was to determine if preoperative pain history and/or the fibromyalgia survey score can predict postoperative outcomes following shoulder arthroscopy, which may cause moderate-to-severe pain. Methods In this prospective study, 100 shoulder arthroscopy patients completed preoperative validated self-report measures to assess baseline quality of recovery score, physical functioning, depression/anxiety, and neuropathic pain. Fibromyalgia characteristics were evaluated using a validated measure of widespread pain and comorbid symptoms on a 0–31 scale. Outcomes were assessed on postoperative days 2 (opioid consumption [primary], pain, physical functioning, quality of recovery score) and 14 (opioid consumption, pain). Results Fibromyalgia survey scores ranged from 0–13. The cohort was divided into tertiles for univariate analyses. Preoperative depression/anxiety (p<0.001) and neuropathic pain (p=0.008) were higher, and physical functioning was lower (p<0.001), in higher fibromyalgia survey score groups. The fibromyalgia survey score was not associated with postoperative pain or opioid consumption; however, it was independently associated with poorer quality of recovery scores (p=0.001). The only independent predictor of postoperative opioid use was preoperative opioid use (p=0.038). Discussion Fibromyalgia survey scores were lower than those in a previous study of joint arthroplasty. Although they distinguished a negative preoperative pain phenotype, fibromyalgia scores were not independently associated with postoperative opioid consumption. Further research is needed to elucidate the impact of a fibromyalgia-like phenotype on postoperative analgesic outcomes. PMID:26626295

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp.case.edu/public/data/DMN Contact: rxx@case.edu PMID:26072493

Female guppies agree to differ: phenotypic and genetic variation in mate-choice behavior and the consequences for sexual selection.

PubMed

Brooks, R; Endler, J A

2001-08-01

Variation among females in mate choice may influence evolution by sexual selection. The genetic basis of this variation is of interest because the elaboration of mating preferences requires additive genetic variation in these traits. Here we measure the repeatability and heritability of two components of female choosiness (responsiveness and discrimination) and of female preference functions for the multiple ornaments borne by male guppies (Poecilia reticulata). We show that there is significant repeatable variation in both components of choosiness and in some preference functions but not in others. There appear to be several male ornaments that females find uniformly attractive and others for which females differ in preference. One consequence is that there is no universally attractive male phenotype. Only responsiveness shows significant additive genetic variation. Variation in responsiveness appears to mask variation in discrimination and some preference functions and may be the most biologically relevant source of phenotypic and genetic variation in mate-choice behavior. To test the potential evolutionary importance of the phenotypic variation in mate choice that we report, we estimated the opportunity for and the intensity of sexual selection under models of mate choice that excluded and that incorporated individual female variation. We then compared these estimates with estimates based on measured mating success. Incorporating individual variation in mate choice generally did not predict the outcome of sexual selection any better than models that ignored such variation.

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources.

PubMed

Kahanda, Indika; Funk, Christopher; Verspoor, Karin; Ben-Hur, Asa

2015-01-01

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.

Environmental and genetic modulation of the phenotypic expression of antibiotic resistance

PubMed Central

Andersson, Dan I

2017-01-01

Abstract Antibiotic resistance can be acquired by mutation or horizontal transfer of a resistance gene, and generally an acquired mechanism results in a predictable increase in phenotypic resistance. However, recent findings suggest that the environment and/or the genetic context can modify the phenotypic expression of specific resistance genes/mutations. An important implication from these findings is that a given genotype does not always result in the expected phenotype. This dissociation of genotype and phenotype has important consequences for clinical bacteriology and for our ability to predict resistance phenotypes from genetics and DNA sequences. A related problem concerns the degree to which the genes/mutations currently identified in vitro can fully explain the in vivo resistance phenotype, or whether there is a significant additional amount of presently unknown mutations/genes (genetic ‘dark matter’) that could contribute to resistance in clinical isolates. Finally, a very important question is whether/how we can identify the genetic features that contribute to making a successful pathogen, and predict why some resistant clones are very successful and spread globally? In this review, we describe different environmental and genetic factors that influence phenotypic expression of antibiotic resistance genes/mutations and how this information is needed to understand why particular resistant clones spread worldwide and to what extent we can use DNA sequences to predict evolutionary success. PMID:28333270

An Evolution-Based Screen for Genetic Differentiation between Anopheles Sister Taxa Enriches for Detection of Functional Immune Factors

PubMed Central

Takashima, Eizo; Williams, Marni; Eiglmeier, Karin; Pain, Adrien; Guelbeogo, Wamdaogo M.; Gneme, Awa; Brito-Fravallo, Emma; Holm, Inge; Lavazec, Catherine; Sagnon, N’Fale; Baxter, Richard H.; Riehle, Michelle M.; Vernick, Kenneth D.

2015-01-01

Nucleotide variation patterns across species are shaped by the processes of natural selection, including exposure to environmental pathogens. We examined patterns of genetic variation in two sister species, Anopheles gambiae and Anopheles coluzzii, both efficient natural vectors of human malaria in West Africa. We used the differentiation signature displayed by a known coordinate selective sweep of immune genes APL1 and TEP1 in A. coluzzii to design a population genetic screen trained on the sweep, classified a panel of 26 potential immune genes for concordance with the signature, and functionally tested their immune phenotypes. The screen results were strongly predictive for genes with protective immune phenotypes: genes meeting the screen criteria were significantly more likely to display a functional phenotype against malaria infection than genes not meeting the criteria (p = 0.0005). Thus, an evolution-based screen can efficiently prioritize candidate genes for labor-intensive downstream functional testing, and safely allow the elimination of genes not meeting the screen criteria. The suite of immune genes with characteristics similar to the APL1-TEP1 selective sweep appears to be more widespread in the A. coluzzii genome than previously recognized. The immune gene differentiation may be a consequence of adaptation of A. coluzzii to new pathogens encountered in its niche expansion during the separation from A. gambiae, although the role, if any of natural selection by Plasmodium is unknown. Application of the screen allowed identification of new functional immune factors, and assignment of new functions to known factors. We describe biochemical binding interactions between immune proteins that underlie functional activity for malaria infection, which highlights the interplay between pathogen specificity and the structure of immune complexes. We also find that most malaria-protective immune factors display phenotypes for either human or rodent malaria, with broad specificity a rarity. PMID:26633695

Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

PubMed

Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

PubMed Central

Magesh, R.; George Priya Doss, C.

2012-01-01

A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria. PMID:22606059

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

PubMed

Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

2016-01-01

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

Update on oral-facial-digital syndromes (OFDS).

PubMed

Franco, Brunella; Thauvin-Robinet, Christel

2016-01-01

Oral-facial-digital syndromes (OFDS) represent a heterogeneous group of rare developmental disorders affecting the mouth, the face and the digits. Additional signs may involve brain, kidneys and other organs thus better defining the different clinical subtypes. With the exception of OFD types I and VIII, which are X-linked, the majority of OFDS is transmitted as an autosomal recessive syndrome. A number of genes have already found to be mutated in OFDS and most of the encoded proteins are predicted or proven to be involved in primary cilia/basal body function. Preliminary data indicate a physical interaction among some of those proteins and future studies will clarify whether all OFDS proteins are part of a network functionally connected to cilia. Mutations in some of the genes can also lead to other types of ciliopathies with partially overlapping phenotypes, such as Joubert syndrome (JS) and Meckel syndrome (MKS), supporting the concept that cilia-related diseases might be a continuous spectrum of the same phenotype with different degrees of severity. To date, seven of the described OFDS still await a molecular definition and two unclassified forms need further clinical and molecular validation. Next-generation sequencing (NGS) approaches are expected to shed light on how many OFDS geneticists should consider while evaluating oral-facial-digital cases. Functional studies will establish whether the non-ciliary functions of the transcripts mutated in OFDS might contribute to any of the phenotypic abnormalities observed in OFDS.

Predictive oncology: multidisciplinary, multi-scale in-silico modeling linking phenotype, morphology and growth

PubMed Central

Sanga, Sandeep; Frieboes, Hermann B.; Zheng, Xiaoming; Gatenby, Robert; Bearer, Elaine L.; Cristini, Vittorio

2007-01-01

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically review advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we propose and discuss a multi-scale, i.e., from the molecular to the gross tumor scale, mathematical and computational “first-principle” approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We demonstrate that this methodology, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as phenotype-diagnostic tool and thus to predict collective and individual tumor cell invasion of surrounding host. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior. PMID:17629503

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.

PubMed

Okaty, Benjamin W; Freret, Morgan E; Rood, Benjamin D; Brust, Rachael D; Hennessy, Morgan L; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N; Dymecki, Susan M

2015-11-18

Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-seq to deconstruct the mouse 5HT system at multiple levels of granularity-from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal principles underlying system organization, 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers sertonergic subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-Scale Molecular Deconstruction of the Serotonin Neuron System

PubMed Central

Okaty, Benjamin W.; Freret, Morgan E.; Rood, Benjamin D.; Brust, Rachael D.; Hennessy, Morgan L.; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N.; Dymecki, Susan M.

2016-01-01

Summary Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-Seq to deconstruct the mouse 5HT system at multiple levels of granularity—from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal: principles underlying system organization, novel 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers new subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. PMID:26549332

Evolving phenotypic networks in silico.

PubMed

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.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2016-01-01

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Sex Allocation and Reproductive Success in the Andromonoecious Perennial Solanum carolinense (Solanaceae). II. Paternity and Functional Gender.

PubMed

Elle, Elizabeth; Meagher, Thomas R

2000-12-01

According to Bateman's principle, male fitness in entomophilous plant species should be limited by mating opportunity, which is influenced by the size or number of flowers. We determined male-specific fitness consequences of floral phenotype in andromonoecious Solanum carolinense, examined the relationship between male and female reproductive success within plants, and evaluated the distribution of functional gender among plants. A maximum likelihood-based paternity analysis, based on multilocus allozyme phenotypes of parents and offspring from four experimental plots, was used to determine male reproductive success and its relationship to floral phenotype. Male success was enhanced by an increase in the proportion of male flowers produced but not by an increase in total flower number, even though all flowers contain male parts. Larger flower size increased male success in only one plot. Male and female reproductive success were negatively correlated, and plants varied in functional gender from completely female to completely male. This gender specialization may occur because hermaphroditic and male flowers differ in their ability to contribute to male and female success. Although sex allocation theory predicts a positive relationship between the size or number of plant parts and reproductive success, this study indicates that aspects of floral morphology that affect gender specialization should also be considered.

Developmental effects of androgens in the human brain.

PubMed

Nguyen, T-V

2018-02-01

Neuroendocrine theories of brain development posit that androgens play a crucial role in sex-specific cortical growth, although little is known about the differential effects of testosterone and dehydroepiandrosterone (DHEA) on cortico-limbic development and cognition during adolescence. In this context, the National Institutes of Health Study of Normal Brain Development, a longitudinal study of typically developing children and adolescents aged 4-24 years (n=433), offers a unique opportunity to examine the developmental effects of androgens on cortico-limbic maturation and cognition. Using data from this sample, our group found that higher testosterone levels were associated with left-sided decreases in cortical thickness (CTh) in post-pubertal boys, particularly in the prefrontal cortex, compared to right-sided increases in CTh in somatosensory areas in pre-pubertal girls. Prefrontal-amygdala and prefrontal-hippocampal structural covariance (considered to reflect structural connectivity) also varied according to testosterone levels, with the testosterone-related brain phenotype predicting higher aggression levels and lower executive function, particularly in boys. By contrast, DHEA was associated with a pre-pubertal increase in CTh of several regions involved in cognitive control in both boys and girls. Covariance within several cortico-amygdalar structural networks also varied as a function of DHEA levels, with the DHEA-related brain phenotype predicting improvements in visual attention in both boys and girls. DHEA-related cortico-hippocampal structural covariance, on the other hand, predicted higher scores on a test of working memory. Interestingly, there were significant interactions between testosterone and DHEA, such that DHEA tended to mitigate the anti-proliferative effects of testosterone on brain structure. In sum, testosterone-related effects on the developing brain may lead to detrimental effects on cortical functions (ie, higher aggression and lower executive function), whereas DHEA-related effects may optimise cortical functions (ie, better attention and working memory), perhaps by decreasing the influence of amygdalar and hippocampal afferents on cortical functions. © 2017 British Society for Neuroendocrinology.

Multilevel biological characterization of exomic variants at the protein level significantly improves the identification of their deleterious effects.

PubMed

Raimondi, Daniele; Gazzo, Andrea M; Rooman, Marianne; Lenaerts, Tom; Vranken, Wim F

2016-06-15

There are now many predictors capable of identifying the likely phenotypic effects of single nucleotide variants (SNVs) or short in-frame Insertions or Deletions (INDELs) on the increasing amount of genome sequence data. Most of these predictors focus on SNVs and use a combination of features related to sequence conservation, biophysical, and/or structural properties to link the observed variant to either neutral or disease phenotype. Despite notable successes, the mapping between genetic variants and their phenotypic effects is riddled with levels of complexity that are not yet fully understood and that are often not taken into account in the predictions, despite their promise of significantly improving the prediction of deleterious mutants. We present DEOGEN, a novel variant effect predictor that can handle both missense SNVs and in-frame INDELs. By integrating information from different biological scales and mimicking the complex mixture of effects that lead from the variant to the phenotype, we obtain significant improvements in the variant-effect prediction results. Next to the typical variant-oriented features based on the evolutionary conservation of the mutated positions, we added a collection of protein-oriented features that are based on functional aspects of the gene affected. We cross-validated DEOGEN on 36 825 polymorphisms, 20 821 deleterious SNVs, and 1038 INDELs from SwissProt. The multilevel contextualization of each (variant, protein) pair in DEOGEN provides a 10% improvement of MCC with respect to current state-of-the-art tools. The software and the data presented here is publicly available at http://ibsquare.be/deogen : wvranken@vub.ac.be Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genome wide selection in Citrus breeding.

PubMed

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

A quantitative study of shape descriptors from glioblastoma multiforme phenotypes for predicting survival outcome

PubMed Central

Desrosiers, Christian; Hassan, Lama; Tanougast, Camel

2016-01-01

Objective: Predicting the survival outcome of patients with glioblastoma multiforme (GBM) is of key importance to clinicians for selecting the optimal course of treatment. The goal of this study was to evaluate the usefulness of geometric shape features, extracted from MR images, as a potential non-invasive way to characterize GBM tumours and predict the overall survival times of patients with GBM. Methods: The data of 40 patients with GBM were obtained from the Cancer Genome Atlas and Cancer Imaging Archive. The T1 weighted post-contrast and fluid-attenuated inversion-recovery volumes of patients were co-registered and segmented into delineate regions corresponding to three GBM phenotypes: necrosis, active tumour and oedema/invasion. A set of two-dimensional shape features were then extracted slicewise from each phenotype region and combined over slices to describe the three-dimensional shape of these phenotypes. Thereafter, a Kruskal–Wallis test was employed to identify shape features with significantly different distributions across phenotypes. Moreover, a Kaplan–Meier analysis was performed to find features strongly associated with GBM survival. Finally, a multivariate analysis based on the random forest model was used for predicting the survival group of patients with GBM. Results: Our analysis using the Kruskal–Wallis test showed that all but one shape feature had statistically significant differences across phenotypes, with p-value < 0.05, following Holm–Bonferroni correction, justifying the analysis of GBM tumour shapes on a per-phenotype basis. Furthermore, the survival analysis based on the Kaplan–Meier estimator identified three features derived from necrotic regions (i.e. Eccentricity, Extent and Solidity) that were significantly correlated with overall survival (corrected p-value < 0.05; hazard ratios between 1.68 and 1.87). In the multivariate analysis, features from necrotic regions gave the highest accuracy in predicting the survival group of patients, with a mean area under the receiver-operating characteristic curve (AUC) of 63.85%. Combining the features of all three phenotypes increased the mean AUC to 66.99%, suggesting that shape features from different phenotypes can be used in a synergic manner to predict GBM survival. Conclusion: Results show that shape features, in particular those extracted from necrotic regions, can be used effectively to characterize GBM tumours and predict the overall survival of patients with GBM. Advances in knowledge: Simple volumetric features have been largely used to characterize the different phenotypes of a GBM tumour (i.e. active tumour, oedema and necrosis). This study extends previous work by considering a wide range of shape features, extracted in different phenotypes, for the prediction of survival in patients with GBM. PMID:27781499

Multiparametric MRI characterization and prediction in autism spectrum disorder using graph theory and machine learning.

PubMed

Zhou, Yongxia; Yu, Fang; Duong, Timothy

2014-01-01

This study employed graph theory and machine learning analysis of multiparametric MRI data to improve characterization and prediction in autism spectrum disorders (ASD). Data from 127 children with ASD (13.5±6.0 years) and 153 age- and gender-matched typically developing children (14.5±5.7 years) were selected from the multi-center Functional Connectome Project. Regional gray matter volume and cortical thickness increased, whereas white matter volume decreased in ASD compared to controls. Small-world network analysis of quantitative MRI data demonstrated decreased global efficiency based on gray matter cortical thickness but not with functional connectivity MRI (fcMRI) or volumetry. An integrative model of 22 quantitative imaging features was used for classification and prediction of phenotypic features that included the autism diagnostic observation schedule, the revised autism diagnostic interview, and intelligence quotient scores. Among the 22 imaging features, four (caudate volume, caudate-cortical functional connectivity and inferior frontal gyrus functional connectivity) were found to be highly informative, markedly improving classification and prediction accuracy when compared with the single imaging features. This approach could potentially serve as a biomarker in prognosis, diagnosis, and monitoring disease progression.

Behavioural phenotypes predict disease susceptibility and infectiousness

PubMed Central

Araujo, Alessandra; Kirschman, Lucas

2016-01-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. PMID:27555652

Behavioural phenotypes predict disease susceptibility and infectiousness.

PubMed

Araujo, Alessandra; Kirschman, Lucas; Warne, Robin W

2016-08-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. © 2016 The Author(s).

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

PubMed

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.

Architecture and functional ecology of the human gastrocnemius muscle-tendon unit.

PubMed

Butler, Erin E; Dominy, Nathaniel J

2016-04-01

The gastrocnemius muscle-tendon unit (MTU) is central to human locomotion. Structural variation in the human gastrocnemius MTU is predicted to affect the efficiency of locomotion, a concept most often explored in the context of performance activities. For example, stiffness of the Achilles tendon varies among individuals with different histories of competitive running. Such a finding highlights the functional variation of individuals and raises the possibility of similar variation between populations, perhaps in response to specific ecological or environmental demands. Researchers often assume minimal variation in human populations, or that industrialized populations represent the human species as well as any other. Yet rainforest hunter-gatherers, which often express the human pygmy phenotype, contradict such assumptions. Indeed, the human pygmy phenotype is a potential model system for exploring the range of ecomorphological variation in the architecture of human hindlimb muscles, a concept we review here. © 2015 Anatomical Society.

Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.

PubMed

Emdin, Connor A; Khera, Amit V; Chaffin, Mark; Klarin, Derek; Natarajan, Pradeep; Aragam, Krishna; Haas, Mary; Bick, Alexander; Zekavat, Seyedeh M; Nomura, Akihiro; Ardissino, Diego; Wilson, James G; Schunkert, Heribert; McPherson, Ruth; Watkins, Hugh; Elosua, Roberto; Bown, Matthew J; Samani, Nilesh J; Baber, Usman; Erdmann, Jeanette; Gupta, Namrata; Danesh, John; Chasman, Daniel; Ridker, Paul; Denny, Joshua; Bastarache, Lisa; Lichtman, Judith H; D'Onofrio, Gail; Mattera, Jennifer; Spertus, John A; Sheu, Wayne H-H; Taylor, Kent D; Psaty, Bruce M; Rich, Stephen S; Post, Wendy; Rotter, Jerome I; Chen, Yii-Der Ida; Krumholz, Harlan; Saleheen, Danish; Gabriel, Stacey; Kathiresan, Sekar

2018-04-24

Less than 3% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In >400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency < 5%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B, pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease.

Prediction accuracy of direct and indirect approaches, and their relationships with prediction ability of calibration models.

PubMed

Belay, T K; Dagnachew, B S; Boison, S A; Ådnøy, T

2018-03-28

Milk infrared spectra are routinely used for phenotyping traits of interest through links developed between the traits and spectra. Predicted individual traits are then used in genetic analyses for estimated breeding value (EBV) or for phenotypic predictions using a single-trait mixed model; this approach is referred to as indirect prediction (IP). An alternative approach [direct prediction (DP)] is a direct genetic analysis of (a reduced dimension of) the spectra using a multitrait model to predict multivariate EBV of the spectral components and, ultimately, also to predict the univariate EBV or phenotype for the traits of interest. We simulated 3 traits under different genetic (low: 0.10 to high: 0.90) and residual (zero to high: ±0.90) correlation scenarios between the 3 traits and assumed the first trait is a linear combination of the other 2 traits. The aim was to compare the IP and DP approaches for predictions of EBV and phenotypes under the different correlation scenarios. We also evaluated relationships between performances of the 2 approaches and the accuracy of calibration equations. Moreover, the effect of using different regression coefficients estimated from simulated phenotypes (β p ), true breeding values (β g ), and residuals (β r ) on performance of the 2 approaches were evaluated. The simulated data contained 2,100 parents (100 sires and 2,000 cows) and 8,000 offspring (4 offspring per cow). Of the 8,000 observations, 2,000 were randomly selected and used to develop links between the first and the other 2 traits using partial least square (PLS) regression analysis. The different PLS regression coefficients, such as β p , β g , and β r , were used in subsequent predictions following the IP and DP approaches. We used BLUP analyses for the remaining 6,000 observations using the true (co)variance components that had been used for the simulation. Accuracy of prediction (of EBV and phenotype) was calculated as a correlation between predicted and true values from the simulations. The results showed that accuracies of EBV prediction were higher in the DP than in the IP approach. The reverse was true for accuracy of phenotypic prediction when using β p but not when using β g and β r , where accuracy of phenotypic prediction in the DP was slightly higher than in the IP approach. Within the DP approach, accuracies of EBV when using β g were higher than when using β p only at the low genetic correlation scenario. However, we found no differences in EBV prediction accuracy between the β p and β g in the IP approach. Accuracy of the calibration models increased with an increase in genetic and residual correlations between the traits. Performance of both approaches increased with an increase in accuracy of the calibration models. In conclusion, the DP approach is a good strategy for EBV prediction but not for phenotypic prediction, where the classical PLS regression-based equations or the IP approach provided better results. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Temporal variation in phenotypic gender and expected functional gender within and among individuals in an annual plant.

PubMed

Austen, Emily J; Weis, Arthur E

2014-07-01

Adaptive explanations for variation in sex allocation centre on variation in resource status and variation in the mating environment. The latter can occur when dichogamy causes siring opportunity to vary across the flowering season. In this study, it is hypothesized that the widespread tendency towards declining fruit-set from first to last flowers on plants can similarly lead to a varying mating environment by causing a temporal shift in the quality (not quantity) of siring opportunities. A numerical model was developed to examine the effects of declining fruit-set on the expected male versus female reproductive success (functional gender) of first and last flowers on plants, and of early- and late-flowering plants. Within- and among-plant temporal variation in pollen production, ovule production and fruit-set in 70 Brassica rapa plants was then characterized to determine if trends in male and female investment mirror expected trends in functional gender. Under a wide range of model conditions, functional femaleness decreased sharply in the last flowers on plants, and increased from early- to late-flowering plants in the population. In B. rapa, pollen production decreased more rapidly than ovule production from first to last flowers, leading to a within-plant increase in phenotypic femaleness. Among plants, ovule production decreased from early- to late-flowering plants, causing a temporal decrease in phenotypic femaleness. The numerical model confirmed that declining fruit-set can drive temporal variation in functional gender, especially among plants. The discrepancy between observed trends in phenotypic gender in B. rapa and expected functional gender predicted by the numerical model does not rule out the possibility that male reproductive success decreases with later flowering onset. If so, plants may experience selection for early flowering through male fitness. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Assessment of the Clinical Relevance of BRCA2 Missense Variants by Functional and Computational Approaches.

PubMed

Guidugli, Lucia; Shimelis, Hermela; Masica, David L; Pankratz, Vernon S; Lipton, Gary B; Singh, Namit; Hu, Chunling; Monteiro, Alvaro N A; Lindor, Noralane M; Goldgar, David E; Karchin, Rachel; Iversen, Edwin S; Couch, Fergus J

2018-01-17

Many variants of uncertain significance (VUS) have been identified in BRCA2 through clinical genetic testing. VUS pose a significant clinical challenge because the contribution of these variants to cancer risk has not been determined. We conducted a comprehensive assessment of VUS in the BRCA2 C-terminal DNA binding domain (DBD) by using a validated functional assay of BRCA2 homologous recombination (HR) DNA-repair activity and defined a classifier of variant pathogenicity. Among 139 variants evaluated, 54 had ≥99% probability of pathogenicity, and 73 had ≥95% probability of neutrality. Functional assay results were compared with predictions of variant pathogenicity from the Align-GVGD protein-sequence-based prediction algorithm, which has been used for variant classification. Relative to the HR assay, Align-GVGD significantly (p < 0.05) over-predicted pathogenic variants. We subsequently combined functional and Align-GVGD prediction results in a Bayesian hierarchical model (VarCall) to estimate the overall probability of pathogenicity for each VUS. In addition, to predict the effects of all other BRCA2 DBD variants and to prioritize variants for functional studies, we used the endoPhenotype-Optimized Sequence Ensemble (ePOSE) algorithm to train classifiers for BRCA2 variants by using data from the HR functional assay. Together, the results show that systematic functional assays in combination with in silico predictors of pathogenicity provide robust tools for clinical annotation of BRCA2 VUS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2018-06-09

Endothelial dysfunction is an early hallmark of multiple disease states that also display sex differences with respect to age of onset, frequency, and severity. Results of in vivo studies of basal and stimulated microvascular barrier function revealed sex differences difficult to ascribe to specific cells or environmental factors. The present study evaluated endothelial cells (EC) isolated from macro- and/or microvessels of reproductively mature rats under the controlled conditions of low-passage culture to test the assumption that EC phenotype would be sex-independent. The primary finding was that EC, regardless of where they are derived, retain a sex-bias in low-passage culture, independent of varying levels of reproductive hormones. Implications of the work include the fallacy of expecting a universal set of mechanisms derived from study of EC from one sex and/or one vascular origin to apply uniformly to all EC under unstimulated conditions no less in the disease state. Vascular endothelial cells (EC) are heterogeneous with respect to phenotype reflecting at least organ of origin, location within the vascular network, and physical forces. Sex, as an independent influence on EC functions in health or etiology, susceptibility, and progression of dysfunction in numerous disease states, has been largely ignored. The current study focussed on EC isolated from aorta (macrovascular) and skeletal muscle vessels (microvascular) of age-matched male and female rats under identical conditions of short term (passage 4) culture. We tested the hypothesis that genomic sex would not influence endothelial growth, wound healing, morphology, lactate production, or messenger RNA and protein expression of key proteins (sex hormone receptors for androgen (AR) and oestrogen (ERα and ERβ); PECAM-1 and VE-CAD mediating barrier function; α v β 3 and N-Cadherin influencing matrix interactions; ICAM-1 and VCAM-1 mediating EC/white cell adhesion). The hypothesis was rejected as EC origin (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 < Vessel Origin < 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.

Differential translation efficiency of orthologous genes is involved in phenotypic divergence of yeast species.

PubMed

Man, Orna; Pilpel, Yitzhak

2007-03-01

A major challenge in comparative genomics is to understand how phenotypic differences between species are encoded in their genomes. Phenotypic divergence may result from differential transcription of orthologous genes, yet less is known about the involvement of differential translation regulation in species phenotypic divergence. In order to assess translation effects on divergence, we analyzed approximately 2,800 orthologous genes in nine yeast genomes. For each gene in each species, we predicted translation efficiency, using a measure of the adaptation of its codons to the organism's tRNA pool. Mining this data set, we found hundreds of genes and gene modules with correlated patterns of translational efficiency across the species. One signal encompassed entire modules that are either needed for oxidative respiration or fermentation and are efficiently translated in aerobic or anaerobic species, respectively. In addition, the efficiency of translation of the mRNA splicing machinery strongly correlates with the number of introns in the various genomes. Altogether, we found extensive selection on synonymous codon usage that modulates translation according to gene function and organism phenotype. We conclude that, like factors such as transcription regulation, translation efficiency affects and is affected by the process of species divergence.

The emotion system promotes diversity and evolvability

PubMed Central

Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J.; Aksnes, Dag L.; Mangel, Marc; Jørgensen, Christian

2014-01-01

Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels. PMID:25100697

The emotion system promotes diversity and evolvability.

PubMed

Giske, Jarl; Eliassen, Sigrunn; Fiksen, Øyvind; Jakobsen, Per J; Aksnes, Dag L; Mangel, Marc; Jørgensen, Christian

2014-09-22

Studies on the relationship between the optimal phenotype and its environment have had limited focus on genotype-to-phenotype pathways and their evolutionary consequences. Here, we study how multi-layered trait architecture and its associated constraints prescribe diversity. Using an idealized model of the emotion system in fish, we find that trait architecture yields genetic and phenotypic diversity even in absence of frequency-dependent selection or environmental variation. That is, for a given environment, phenotype frequency distributions are predictable while gene pools are not. The conservation of phenotypic traits among these genetically different populations is due to the multi-layered trait architecture, in which one adaptation at a higher architectural level can be achieved by several different adaptations at a lower level. Our results emphasize the role of convergent evolution and the organismal level of selection. While trait architecture makes individuals more constrained than what has been assumed in optimization theory, the resulting populations are genetically more diverse and adaptable. The emotion system in animals may thus have evolved by natural selection because it simultaneously enhances three important functions, the behavioural robustness of individuals, the evolvability of gene pools and the rate of evolutionary innovation at several architectural levels.

The stable traits of melanoma genetics: an alternate approach to target discovery

PubMed Central

2012-01-01

Background The weight that gene copy number plays in transcription remains controversial; although in specific cases gene expression correlates with copy number, the relationship cannot be inferred at the global level. We hypothesized that genes steadily expressed by 15 melanoma cell lines (CMs) and their parental tissues (TMs) should be critical for oncogenesis and their expression most frequently influenced by their respective copy number. Results Functional interpretation of 3,030 transcripts concordantly expressed (Pearson's correlation coefficient p-value < 0.05) by CMs and TMs confirmed an enrichment of functions crucial to oncogenesis. Among them, 968 were expressed according to the transcriptional efficiency predicted by copy number analysis (Pearson's correlation coefficient p-value < 0.05). We named these genes, "genomic delegates" as they represent at the transcriptional level the genetic footprint of individual cancers. We then tested whether the genes could categorize 112 melanoma metastases. Two divergent phenotypes were observed: one with prevalent expression of cancer testis antigens, enhanced cyclin activity, WNT signaling, and a Th17 immune phenotype (Class A). This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer. The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy. An intermediate third class (C) was further identified. The three phenotypes were confirmed by unsupervised principal component analysis. Conclusions This study suggests that clinically relevant phenotypes of melanoma can be retraced to stable oncogenic properties of cancer cells linked to their genetic back bone, and offers a roadmap for uncovering novel targets for tailored anti-cancer therapy. PMID:22537248

Phenotypes from ancient DNA: approaches, insights and prospects.

PubMed

Fortes, Gloria G; Speller, Camilla F; Hofreiter, Michael; King, Turi E

2013-08-01

The great majority of phenotypic characteristics are complex traits, complicating the identification of the genes underlying their expression. However, both methodological and theoretical progress in genome-wide association studies have resulted in a much better understanding of the underlying genetics of many phenotypic traits, including externally visible characteristics (EVCs) such as eye and hair color. Consequently, it has become possible to predict EVCs from human samples lacking phenotypic information. Predicting EVCs from genetic evidence is clearly appealing for forensic applications involving the personal identification of human remains. Now, a recent paper has reported the genetic determination of eye and hair color in samples up to 800 years old. The ability to predict EVCs from ancient human remains opens up promising perspectives for ancient DNA research, as this could allow studies to directly address archaeological and evolutionary questions related to the temporal and geographical origins of the genetic variants underlying phenotypes. © 2013 WILEY Periodicals, Inc.

Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity

PubMed Central

Saleheen, Danish; Natarajan, Pradeep; Armean, Irina M.; Zhao, Wei; Rasheed, Asif; Khetarpal, Sumeet; Won, Hong-Hee; Karczewski, Konrad J.; O’Donnell-Luria, Anne H.; Samocha, Kaitlin E.; Weisburd, Benjamin; Gupta, Namrata; Zaidi, Mozzam; Samuel, Maria; Imran, Atif; Abbas, Shahid; Majeed, Faisal; Ishaq, Madiha; Akhtar, Saba; Trindade, Kevin; Mucksavage, Megan; Qamar, Nadeem; Zaman, Khan Shah; Yaqoob, Zia; Saghir, Tahir; Rizvi, Syed Nadeem Hasan; Memon, Anis; Mallick, Nadeem Hayyat; Ishaq, Mohammad; Rasheed, Syed Zahed; Memon, Fazal-ur-Rehman; Mahmood, Khalid; Ahmed, Naveeduddin; Do, Ron; Krauss, Ronald M.; MacArthur, Daniel G.; Gabriel, Stacey; Lander, Eric S.; Daly, Mark J.; Frossard, Philippe; Danesh, John; Rader, Daniel J.; Kathiresan, Sekar

2017-01-01

A major goal of biomedicine is to understand the function of every gene in the human genome.1 Loss-of-function (LoF) mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such ‘human knockouts’ can provide insight into gene function. Consanguineous unions are more likely to result in offspring who carry LoF mutations in a homozygous state. In Pakistan, consanguinity rates are notably high.2 Here, we sequenced the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS) designed to understand the determinants of cardiometabolic diseases in South Asians.3 We identified individuals carrying predicted LoF (pLoF) mutations in the homozygous state, and performed phenotypic analysis involving >200 biochemical and disease traits. We enumerated 49,138 rare (<1 % minor allele frequency) pLoF mutations. These pLoF mutations are predicted to knock out 1,317 genes in at least one participant. Homozygosity for pLoF mutations at PLAG27 was associated with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; at TREH, with lower concentrations of apoB-containing lipoprotein subfractions; at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations; and at SLC9A3R1, with mediators of calcium and phosphate signaling. Finally, APOC3 is a gene which retards clearance of plasma triglyceride-rich lipoproteins and where heterozygous deficiency confers protection against coronary heart disease.4,5 In Pakistan, we now observe APOC3 homozygous pLoF carriers; we recalled these knockout humans and challenged with an oral fat load. Compared with wild-type family members, APOC3 knockouts displayed marked blunting of the usual post-prandial rise in plasma triglycerides. Overall, these observations provide a roadmap for a ‘human knockout project’, a systematic effort to understand the phenotypic consequences of complete disruption of genes in humans. PMID:28406212

Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda.

PubMed

Prasher, Bhavana; Negi, Sapna; Aggarwal, Shilpi; Mandal, Amit K; Sethi, Tav P; Deshmukh, Shailaja R; Purohit, Sudha G; Sengupta, Shantanu; Khanna, Sangeeta; Mohammad, Farhan; Garg, Gaurav; Brahmachari, Samir K; Mukerji, Mitali

2008-09-09

Ayurveda is an ancient system of personalized medicine documented and practiced in India since 1500 B.C. According to this system an individual's basic constitution to a large extent determines predisposition and prognosis to diseases as well as therapy and life-style regime. Ayurveda describes seven broad constitution types (Prakritis) each with a varying degree of predisposition to different diseases. Amongst these, three most contrasting types, Vata, Pitta, Kapha, are the most vulnerable to diseases. In the realm of modern predictive medicine, efforts are being directed towards capturing disease phenotypes with greater precision for successful identification of markers for prospective disease conditions. In this study, we explore whether the different constitution types as described in Ayurveda has molecular correlates. Normal individuals of the three most contrasting constitutional types were identified following phenotyping criteria described in Ayurveda in Indian population of Indo-European origin. The peripheral blood samples of these individuals were analysed for genome wide expression levels, biochemical and hematological parameters. Gene Ontology (GO) and pathway based analysis was carried out on differentially expressed genes to explore if there were significant enrichments of functional categories among Prakriti types. Individuals from the three most contrasting constitutional types exhibit striking differences with respect to biochemical and hematological parameters and at genome wide expression levels. Biochemical profiles like liver function tests, lipid profiles, and hematological parameters like haemoglobin exhibited differences between Prakriti types. Functional categories of genes showing differential expression among Prakriti types were significantly enriched in core biological processes like transport, regulation of cyclin dependent protein kinase activity, immune response and regulation of blood coagulation. A significant enrichment of housekeeping, disease related and hub genes were observed in these extreme constitution types. Ayurveda based method of phenotypic classification of extreme constitutional types allows us to uncover genes that may contribute to system level differences in normal individuals which could lead to differential disease predisposition. This is a first attempt towards unraveling the clinical phenotyping principle of a traditional system of medicine in terms of modern biology. An integration of Ayurveda with genomics holds potential and promise for future predictive medicine.

Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda

PubMed Central

Prasher, Bhavana; Negi, Sapna; Aggarwal, Shilpi; Mandal, Amit K; Sethi, Tav P; Deshmukh, Shailaja R; Purohit, Sudha G; Sengupta, Shantanu; Khanna, Sangeeta; Mohammad, Farhan; Garg, Gaurav; Brahmachari, Samir K; Mukerji, Mitali

2008-01-01

Background Ayurveda is an ancient system of personalized medicine documented and practiced in India since 1500 B.C. According to this system an individual's basic constitution to a large extent determines predisposition and prognosis to diseases as well as therapy and life-style regime. Ayurveda describes seven broad constitution types (Prakritis) each with a varying degree of predisposition to different diseases. Amongst these, three most contrasting types, Vata, Pitta, Kapha, are the most vulnerable to diseases. In the realm of modern predictive medicine, efforts are being directed towards capturing disease phenotypes with greater precision for successful identification of markers for prospective disease conditions. In this study, we explore whether the different constitution types as described in Ayurveda has molecular correlates. Methods Normal individuals of the three most contrasting constitutional types were identified following phenotyping criteria described in Ayurveda in Indian population of Indo-European origin. The peripheral blood samples of these individuals were analysed for genome wide expression levels, biochemical and hematological parameters. Gene Ontology (GO) and pathway based analysis was carried out on differentially expressed genes to explore if there were significant enrichments of functional categories among Prakriti types. Results Individuals from the three most contrasting constitutional types exhibit striking differences with respect to biochemical and hematological parameters and at genome wide expression levels. Biochemical profiles like liver function tests, lipid profiles, and hematological parameters like haemoglobin exhibited differences between Prakriti types. Functional categories of genes showing differential expression among Prakriti types were significantly enriched in core biological processes like transport, regulation of cyclin dependent protein kinase activity, immune response and regulation of blood coagulation. A significant enrichment of housekeeping, disease related and hub genes were observed in these extreme constitution types. Conclusion Ayurveda based method of phenotypic classification of extreme constitutional types allows us to uncover genes that may contribute to system level differences in normal individuals which could lead to differential disease predisposition. This is a first attempt towards unraveling the clinical phenotyping principle of a traditional system of medicine in terms of modern biology. An integration of Ayurveda with genomics holds potential and promise for future predictive medicine. PMID:18782426

Upper gastrointestinal tract phenotype of Crohn's disease is associated with early surgery and further hospitalization.

PubMed

Chow, Dorothy K L; Sung, Joseph J Y; Wu, Justin C Y; Tsoi, Kelvin K F; Leong, Rupert W L; Chan, Francis K L

2009-04-01

According to the Montreal Classification, upper gastrointestinal tract phenotype L4 is uncommon in Caucasian patients with Crohn's disease (CD) but carries excess risk of recurrence. We studied the clinical course of CD in Chinese patients presenting with the L4 phenotype and factors predicting its occurrence upon longitudinal follow-up. This prospective cohort study included 132 Chinese CD patients (median age at diagnosis, 30.0 years, range: 14.0-77.0 years) who were followed for 770 person-years. Demographic data including disease behavior and location, details of surgery, and hospitalization were collected. The Kaplan-Meier method was used to estimate the probabilities of further hospitalization and major surgery followed by Cox proportional hazards regression to determine if clinical variables independently predicted the endpoints. The L4 phenotype was found in 30 (22.7%) patients at presentation. There were significantly more stricturing (46.7% versus 18.6%) and penetrating (30.0% versus 3.9%) phenotypes in the L4 group than in the non-L4 group (P < 0.0001). The 3-year cumulative probability of further hospitalization was 86.9% (95% confidence interval [CI]: 73.8%-100.0%) in the L4 group as compared with 49.3% (95% CI: 39.3%-59.3%) in the non-L4 group (log-rank test, P < 0.0001). The L4 phenotype independently predicted further hospitalization (adjusted hazards ratio [HR]: 2.1; 95% CI: 1.3-3.5). The cumulative probability of major surgery was significantly higher in the L4 than in the non-L4 group (P < 0.0001). Eighteen (17.6%) patients developed the L4 phenotype on follow-up and the stricturing phenotype predicted its occurrence (adjusted HR: 5.5; 95% CI: 2.2-14.0). Chinese CD patients more often had the L4 phenotype, which predicted the need of subsequent hospitalization.

Prediction of whole-genome risk for selection and management of hyperketonemia in Holstein dairy cattle.

PubMed

Weigel, K A; Pralle, R S; Adams, H; Cho, K; Do, C; White, H M

2017-06-01

Hyperketonemia (HYK), a common early postpartum health disorder characterized by elevated blood concentrations of β-hydroxybutyrate (BHB), affects millions of dairy cows worldwide and leads to significant economic losses and animal welfare concerns. In this study, blood concentrations of BHB were assessed for 1,453 Holstein cows using electronic handheld meters at four time points between 5 and 18 days postpartum. Incidence rates of subclinical (1.2 ≤ maximum BHB ≤ 2.9 mmol/L) and clinical ketosis (maximum BHB ≥ 3.0 mmol/L) were 24.0 and 2.4%, respectively. Variance components, estimated breeding values, and predicted HYK phenotypes were computed on the original, square-root, and binary scales. Heritability estimates for HYK ranged from 0.058 to 0.072 in pedigree-based analyses, as compared to estimates that ranged from 0.071 to 0.093 when pedigrees were augmented with 60,671 single nucleotide polymorphism genotypes of 959 cows and 801 male ancestors. On average, predicted HYK phenotypes from the genome-enhanced analysis ranged from 0.55 mmol/L for first-parity cows in the best contemporary group to 1.40 mmol/L for fourth-parity cows in the worst contemporary group. Genome-enhanced predictions of HYK phenotypes were more closely associated with actual phenotypes than pedigree-based predictions in five-fold cross-validation, and transforming phenotypes to reduce skewness and kurtosis also improved predictive ability. This study demonstrates the feasibility of using repeated cowside measurement of blood BHB concentration in early lactation to construct a reference population that can be used to estimate HYK breeding values for genomic selection programmes and predict HYK phenotypes for genome-guided management decisions. © 2017 Blackwell Verlag GmbH.

Relations of mitochondrial genetic variants to measures of vascular function.

PubMed

Fetterman, Jessica L; Liu, Chunyu; Mitchell, Gary F; Vasan, Ramachandran S; Benjamin, Emelia J; Vita, Joseph A; Hamburg, Naomi M; Levy, Daniel

2018-05-01

Mitochondrial genetic variation with resultant alterations in oxidative phosphorylation may influence vascular function and contribute to cardiovascular disease susceptibility. We assessed relations of peptide-encoding variants in the mitochondrial genome with measures of vascular function in Framingham Heart Study participants. Of 258 variants assessed, 40 were predicted to have functional consequences by bioinformatics programs. A maternal pattern of heritability was estimated to contribute to the variability of aortic stiffness. A putative association with a microvascular function measure was identified that requires replication. The methods we have developed can be applied to assess the relations of mitochondrial genetic variation to other phenotypes. Copyright © 2017 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

Present Day Biology seen in the Looking Glass of Physics of Complexity

NASA Astrophysics Data System (ADS)

Schuster, P.

Darwin's theory of variation and selection in its simplest form is directly applicable to RNA evolution in vitro as well as to virus evolution, and it allows for quantitative predictions. Understanding evolution at the molecular level is ultimately related to the central paradigm of structural biology: sequence⇒ structure ⇒ function. We elaborate on the state of the art in modeling and understanding evolution of RNA driven by reproduction and mutation. The focus will be laid on the landscape concept—originally introduced by Sewall Wright—and its application to problems in biology. The relation between genotypes and phenotypes is the result of two consecutive mappings from a space of genotypes called sequence space onto a space of phenotypes or structures, and fitness is the result of a mapping from phenotype space into non-negative real numbers. Realistic landscapes as derived from folding of RNA sequences into structures are characterized by two properties: (i) they are rugged in the sense that sequences lying nearby in sequence space may have very different fitness values and (ii) they are characterized by an appreciable degree of neutrality implying that a certain fraction of genotypes and/or phenotypes cannot be distinguished in the selection process. Evolutionary dynamics on realistic landscapes will be studied as a function of the mutation rate, and the role of neutrality in the selection process will be discussed.

HSJ1-related hereditary neuropathies: novel mutations and extended clinical spectrum.

PubMed

Gess, Burkhard; Auer-Grumbach, Michaela; Schirmacher, Anja; Strom, Tim; Zitzelsberger, Manuela; Rudnik-Schöneborn, Sabine; Röhr, Dominik; Halfter, Hartmut; Young, Peter; Senderek, Jan

2014-11-04

To determine the nature and frequency of HSJ1 mutations in patients with hereditary motor and hereditary motor and sensory neuropathies. Patients were screened for mutations by genome-wide or targeted linkage and homozygosity studies, whole-exome sequencing, and Sanger sequencing. RNA and protein studies of skin fibroblasts were used for functional characterization. We describe 2 additional mutations in the HSJ1 gene in a cohort of 90 patients with autosomal recessive distal hereditary motor neuropathy (dHMN) and Charcot-Marie-Tooth disease type 2 (CMT2). One family with a dHMN phenotype showed the homozygous splice-site mutation c.229+1G>A, which leads to retention of intron 4 in the HSJ1 messenger RNA with a premature stop codon and loss of protein expression. Another family, presenting with a CMT2 phenotype, carried the homozygous missense mutation c.14A>G (p.Tyr5Cys). This mutation was classified as likely disease-related by several automatic algorithms for prediction of possible impact of an amino acid substitution on the structure and function of proteins. Both mutations cosegregated with autosomal recessive inheritance of the disease and were absent from the general population. Taken together, in our cohort of 90 probands, we confirm that HSJ1 mutations are a rare but detectable cause of autosomal recessive dHMN and CMT2. We provide clinical and functional information on an HSJ1 splice-site mutation and report the detailed phenotype of 2 patients with CMT2, broadening the phenotypic spectrum of HSJ1-related neuropathies. © 2014 American Academy of Neurology.

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

PubMed

Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

2017-10-12

The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

Cortisol in mother's milk across lactation reflects maternal life history and predicts infant temperament.

PubMed

Hinde, Katie; Skibiel, Amy L; Foster, Alison B; Del Rosso, Laura; Mendoza, Sally P; Capitanio, John P

2015-01-01

The maternal environment exerts important influences on offspring mass/growth, metabolism, reproduction, neurobiology, immune function, and behavior among birds, insects, reptiles, fish, and mammals. For mammals, mother's milk is an important physiological pathway for nutrient transfer and glucocorticoid signaling that potentially influences offspring growth and behavioral phenotype. Glucocorticoids in mother's milk have been associated with offspring behavioral phenotype in several mammals, but studies have been handicapped by not simultaneously evaluating milk energy density and yield. This is problematic as milk glucocorticoids and nutrients likely have simultaneous effects on offspring phenotype. We investigated mother's milk and infant temperament and growth in a cohort of rhesus macaque ( Macaca mulatta ) mother-infant dyads at the California National Primate Research Center ( N = 108). Glucocorticoids in mother's milk, independent of available milk energy, predicted a more Nervous, less Confident temperament in both sons and daughters. We additionally found sex differences in the windows of sensitivity and the magnitude of sensitivity to maternal-origin glucocorticoids. Lower parity mothers produced milk with higher cortisol concentrations. Lastly, higher cortisol concentrations in milk were associated with greater infant weight gain across time. Taken together, these results suggest that mothers with fewer somatic resources, even in captivity, may be "programming" through cortisol signaling, behaviorally cautious offspring that prioritize growth. Glucocorticoids ingested through milk may importantly contribute to the assimilation of available milk energy, development of temperament, and orchestrate, in part, the allocation of maternal milk energy between growth and behavioral phenotype.

Limited plasticity in the phenotypic variance-covariance matrix for male advertisement calls in the black field cricket, Teleogryllus commodus

PubMed Central

Pitchers, W. R.; Brooks, R.; Jennions, M. D.; Tregenza, T.; Dworkin, I.; Hunt, J.

2013-01-01

Phenotypic integration and plasticity are central to our understanding of how complex phenotypic traits evolve. Evolutionary change in complex quantitative traits can be predicted using the multivariate breeders’ equation, but such predictions are only accurate if the matrices involved are stable over evolutionary time. Recent work, however, suggests that these matrices are temporally plastic, spatially variable and themselves evolvable. The data available on phenotypic variance-covariance matrix (P) stability is sparse, and largely focused on morphological traits. Here we compared P for the structure of the complex sexual advertisement call of six divergent allopatric populations of the Australian black field cricket, Teleogryllus commodus. We measured a subset of calls from wild-caught crickets from each of the populations and then a second subset after rearing crickets under common-garden conditions for three generations. In a second experiment, crickets from each population were reared in the laboratory on high- and low-nutrient diets and their calls recorded. In both experiments, we estimated P for call traits and used multiple methods to compare them statistically (Flury hierarchy, geometric subspace comparisons and random skewers). Despite considerable variation in means and variances of individual call traits, the structure of P was largely conserved among populations, across generations and between our rearing diets. Our finding that P remains largely stable, among populations and between environmental conditions, suggests that selection has preserved the structure of call traits in order that they can function as an integrated unit. PMID:23530814

Cortisol in mother’s milk across lactation reflects maternal life history and predicts infant temperament

PubMed Central

Skibiel, Amy L.; Foster, Alison B.; Del Rosso, Laura; Mendoza, Sally P.; Capitanio, John P.

2015-01-01

The maternal environment exerts important influences on offspring mass/growth, metabolism, reproduction, neurobiology, immune function, and behavior among birds, insects, reptiles, fish, and mammals. For mammals, mother’s milk is an important physiological pathway for nutrient transfer and glucocorticoid signaling that potentially influences offspring growth and behavioral phenotype. Glucocorticoids in mother’s milk have been associated with offspring behavioral phenotype in several mammals, but studies have been handicapped by not simultaneously evaluating milk energy density and yield. This is problematic as milk glucocorticoids and nutrients likely have simultaneous effects on offspring phenotype. We investigated mother’s milk and infant temperament and growth in a cohort of rhesus macaque (Macaca mulatta) mother–infant dyads at the California National Primate Research Center (N = 108). Glucocorticoids in mother’s milk, independent of available milk energy, predicted a more Nervous, less Confident temperament in both sons and daughters. We additionally found sex differences in the windows of sensitivity and the magnitude of sensitivity to maternal-origin glucocorticoids. Lower parity mothers produced milk with higher cortisol concentrations. Lastly, higher cortisol concentrations in milk were associated with greater infant weight gain across time. Taken together, these results suggest that mothers with fewer somatic resources, even in captivity, may be “programming” through cortisol signaling, behaviorally cautious offspring that prioritize growth. Glucocorticoids ingested through milk may importantly contribute to the assimilation of available milk energy, development of temperament, and orchestrate, in part, the allocation of maternal milk energy between growth and behavioral phenotype. PMID:25713475

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits*

PubMed Central

Sharma, Amitabh; Gulbahce, Natali; Pevzner, Samuel J.; Menche, Jörg; Ladenvall, Claes; Folkersen, Lasse; Eriksson, Per; Orho-Melander, Marju; Barabási, Albert-László

2013-01-01

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10−5 and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes. PMID:23882023

Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage-derived cytokines.

PubMed

Brasier, Allan R; Victor, Sundar; Boetticher, Gary; Ju, Hyunsu; Lee, Chang; Bleecker, Eugene R; Castro, Mario; Busse, William W; Calhoun, William J

2008-01-01

Asthma is a heterogeneous clinical disorder. Methods for objective identification of disease subtypes will focus on clinical interventions and help identify causative pathways. Few studies have explored phenotypes at a molecular level. We sought to discriminate asthma phenotypes on the basis of cytokine profiles in bronchoalveolar lavage (BAL) samples from patients with mild-moderate and severe asthma. Twenty-five cytokines were measured in BAL samples of 84 patients (41 severe, 43 mild-moderate) using bead-based multiplex immunoassays. The normalized data were subjected to statistical and informatics analysis. Four groups of asthmatic profiles could be identified on the basis of unsupervised analysis (hierarchical clustering) that were independent of treatment. One group, enriched in patients with severe asthma, showed differences in BAL cellular content, reductions in baseline pulmonary function, and enhanced response to methacholine provocation. Ten cytokines were identified that accurately predicted this group. Classification methods for predicting methacholine sensitivity were developed. The best model analysis predicted hyperresponders with 88% accuracy in 10 trials by using a 10-fold cross-validation. The cytokines that contributed to this model were IL-2, IL-4, and IL-5. On the basis of this classifier, 3 distinct hyperresponder classes were identified that varied in BAL eosinophil count and PC20 methacholine. Cytokine expression patterns in BAL can be used to identify distinct types of asthma and identify distinct subsets of methacholine hyperresponders. Further biomarker discovery in BAL may be informative.

Sex-specific evolution during the diversification of live-bearing fishes.

PubMed

Culumber, Zachary W; Tobler, Michael

2017-08-01

Natural selection is often assumed to drive parallel functional diversification of the sexes. But males and females exhibit fundamental differences in their biology, and it remains largely unknown how sex differences affect macroevolutionary patterns. On microevolutionary scales, we understand how natural and sexual selection interact to give rise to sex-specific evolution during phenotypic diversification and speciation. Here we show that ignoring sex-specific patterns of functional trait evolution misrepresents the macroevolutionary adaptive landscape and evolutionary rates for 112 species of live-bearing fishes (Poeciliidae). Males and females of the same species evolve in different adaptive landscapes. Major axes of female morphology were correlated with environmental variables but not reproductive investment, while male morphological variation was primarily associated with sexual selection. Despite the importance of both natural and sexual selection in shaping sex-specific phenotypic diversification, species diversification was overwhelmingly associated with ecological divergence. Hence, the inter-predictability of mechanisms of phenotypic and species diversification may be limited in many systems. These results underscore the importance of explicitly addressing sex-specific diversification in empirical and theoretical frameworks of evolutionary radiations to elucidate the roles of different sources of selection and constraint.

Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics

PubMed Central

LaBarge, Mark A; Parvin, Bahram; Lorens, James B

2014-01-01

The field of bioengineering has pioneered the application of new precision fabrication technologies to model the different geometric, physical or molecular components of tissue microenvironments on solid-state substrata. Tissue engineering approaches building on these advances are used to assemble multicellular mimetic-tissues where cells reside within defined spatial contexts. The functional responses of cells in fabricated microenvironments has revealed a rich interplay between the genome and extracellular effectors in determining cellular phenotypes, and in a number of cases has revealed the dominance of microenvironment over genotype. Precision bioengineered substrata are limited to a few aspects, whereas cell/tissue-derived microenvironments have many undefined components. Thus introducing a computational module may serve to integrate these types of platforms to create reasonable models of drug responses in human tissues. This review discusses how combinatorial microenvironment microarrays and other biomimetic microenvironments have revealed emergent properties of cells in particular microenvironmental contexts, the platforms that can measure phenotypic changes within those contexts, and the computational tools that can unify the microenvironment-imposed functional phenotypes with underlying constellations of proteins and genes. Ultimately we propose that a merger of these technologies will enable more accurate pre-clinical drug discovery. PMID:24582543

Single nucleotide polymorphism coverage and inference of N-acetyltransferase-2 acetylator phenotypes in wordwide population groups.

PubMed

Suarez-Kurtz, Guilherme; Fuchshuber-Moraes, Mateus; Struchiner, Claudio J; Parra, Esteban J

2016-08-01

Several algorithms have been proposed to reduce the genotyping effort and cost, while retaining the accuracy of N-acetyltransferase-2 (NAT2) phenotype prediction. Data from the 1000 Genomes (1KG) project and an admixed cohort of Black Brazilians were used to assess the accuracy of NAT2 phenotype prediction using algorithms based on paired single nucleotide polymorphisms (SNPs) (rs1041983 and rs1801280) or a tag SNP (rs1495741). NAT2 haplotypes comprising SNPs rs1801279, rs1041983, rs1801280, rs1799929, rs1799930, rs1208 and rs1799931 were assigned according to the arylamine N-acetyltransferases database. Contingency tables were used to visualize the agreement between the NAT2 acetylator phenotypes on the basis of these haplotypes versus phenotypes inferred by the prediction algorithms. The paired and tag SNP algorithms provided more than 96% agreement with the 7-SNP derived phenotypes in Europeans, East Asians, South Asians and Admixed Americans, but discordance of phenotype prediction occurred in 30.2 and 24.8% 1KG Africans and in 14.4 and 18.6% Black Brazilians, respectively. Paired SNP panel misclassification occurs in carriers of NATs haplotypes *13A (282T alone), *12B (282T and 803G), *6B (590A alone) and *14A (191A alone), whereas haplotype *14, defined by the 191A allele, is the major culprit of misclassification by the tag allele. Both the paired SNP and the tag SNP algorithms may be used, with economy of scale, to infer NAT2 acetylator phenotypes, including the ultra-slow phenotype, in European, East Asian, South Asian and American populations represented in the 1KG cohort. Both algorithms, however, perform poorly in populations of predominant African descent, including admixed African-Americans, African Caribbeans and Black Brazilians.

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

PubMed Central

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

Phenotype analysis of early risk factors from electronic medical records improves image-derived diagnostic classifiers for optic nerve pathology

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Inference and Prediction of Metabolic Network Fluxes

PubMed Central

Nikoloski, Zoran; Perez-Storey, Richard; Sweetlove, Lee J.

2015-01-01

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping. PMID:26392262

Predicting multicellular function through multi-layer tissue networks

PubMed Central

Zitnik, Marinka; Leskovec, Jure

2017-01-01

Abstract Motivation: Understanding functions of proteins in specific human tissues is essential for insights into disease diagnostics and therapeutics, yet prediction of tissue-specific cellular function remains a critical challenge for biomedicine. Results: Here, we present OhmNet, a hierarchy-aware unsupervised node feature learning approach for multi-layer networks. We build a multi-layer network, where each layer represents molecular interactions in a different human tissue. OhmNet then automatically learns a mapping of proteins, represented as nodes, to a neural embedding-based low-dimensional space of features. OhmNet encourages sharing of similar features among proteins with similar network neighborhoods and among proteins activated in similar tissues. The algorithm generalizes prior work, which generally ignores relationships between tissues, by modeling tissue organization with a rich multiscale tissue hierarchy. We use OhmNet to study multicellular function in a multi-layer protein interaction network of 107 human tissues. In 48 tissues with known tissue-specific cellular functions, OhmNet provides more accurate predictions of cellular function than alternative approaches, and also generates more accurate hypotheses about tissue-specific protein actions. We show that taking into account the tissue hierarchy leads to improved predictive power. Remarkably, we also demonstrate that it is possible to leverage the tissue hierarchy in order to effectively transfer cellular functions to a functionally uncharacterized tissue. Overall, OhmNet moves from flat networks to multiscale models able to predict a range of phenotypes spanning cellular subsystems. Availability and implementation: Source code and datasets are available at http://snap.stanford.edu/ohmnet. Contact: jure@cs.stanford.edu PMID:28881986

Molecular mechanisms governing differential robustness of development and environmental responses in plants

PubMed Central

Lachowiec, Jennifer; Queitsch, Christine; Kliebenstein, Daniel J.

2016-01-01

Background Robustness to genetic and environmental perturbation is a salient feature of multicellular organisms. Loss of developmental robustness can lead to severe phenotypic defects and fitness loss. However, perfect robustness, i.e. no variation at all, is evolutionarily unfit as organisms must be able to change phenotype to properly respond to changing environments and biotic challenges. Plasticity is the ability to adjust phenotypes predictably in response to specific environmental stimuli, which can be considered a transient shift allowing an organism to move from one robust phenotypic state to another. Plants, as sessile organisms that undergo continuous development, are particularly dependent on an exquisite fine-tuning of the processes that balance robustness and plasticity to maximize fitness. Scope and Conclusions This paper reviews recently identified mechanisms, both systems-level and molecular, that modulate robustness, and discusses their implications for the optimization of plant fitness. Robustness in living systems arises from the structure of genetic networks, the specific molecular functions of the underlying genes, and their interactions. This very same network responsible for the robustness of specific developmental states also has to be built such that it enables plastic yet robust shifts in response to environmental changes. In plants, the interactions and functions of signal transduction pathways activated by phytohormones and the tendency for plants to tolerate whole-genome duplications, tandem gene duplication and hybridization are emerging as major regulators of robustness in development. Despite their obvious implications for plant evolution and plant breeding, the mechanistic underpinnings by which plants modulate precise levels of robustness, plasticity and evolvability in networks controlling different phenotypes are under-studied. PMID:26473020

Functional Manipulation of Root Endophyte Populations for Feedstock Improvement- Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dangl, Jeffery L.

This study provides a systemic analysis of the influence of the abiotic environment on the assembly of plant microbiomes. We show that under controlled conditions, community assembly cues are robust and predictable across multiple abiotic gradients. Plant colonization patterns are largely driven by phylogeny, and colonization phenotypes are ubiquitous across different specimens of the same phylogenetic class. Subsets of the full synthetic community were shown to induce different root morphologies, and the morphology observed with the full community is an outcome of epistasis between two functional guilds.

Ontogenetic loss of phenotypic plasticity of age at metamorphosis in tadpoles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hensley, F.R.

1993-12-01

Amphibian larvae exhibit phenotypic plasticity in size at metamorphosis and duration of the larval period. I used Pseudacris crucifer tadpoles to test two models for predicting tadpole age and size at metamorphosis under changing environmental conditions. The Wilbur-Collins model states that metamorphosis is initiated as a function of a tadpole's size and relative growth rate, and predicts that changes in growth rate throughout the larval period affect age and size at metamorphosis. An alternative model, the fixed-rate model, states that age at metamorphosis is fixed early in larval life, and subsequent changes in growth rate will have no effect onmore » the length of the larval period. My results confirm that food supplies affect both age and size at metamorphosis, but developmental rates became fixed at approximately Gosner (1960) stages 35-37. Neither model completely predicted these results. I suggest that the generally accepted Wilbur-Collins model is improved by incorporating a point of fixed developmental timing. Growth trajectories predicted from this modified model fit the results of this study better than trajectories based on either of the original models. The results of this study suggests a constraint that limits the simultaneous optimization of age and size at metamorphosis. 32 refs., 5 figs., 1 tab.« less

CK2 phosphorylates and inhibits TAp73 tumor suppressor function to promote expression of cancer stem cell genes and phenotype in head and neck cancer.

PubMed

Lu, Hai; Yan, Carol; Quan, Xin Xin; Yang, Xinping; Zhang, Jialing; Bian, Yansong; Chen, Zhong; Van Waes, Carter

2014-10-01

Cancer stem cells (CSC) and genes have been linked to cancer development and therapeutic resistance, but the signaling mechanisms regulating CSC genes and phenotype are incompletely understood. CK2 has emerged as a key signal serine/threonine kinase that modulates diverse signal cascades regulating cell fate and growth. We previously showed that CK2 is often aberrantly expressed and activated in head and neck squamous cell carcinomas (HNSCC), concomitantly with mutant (mt) tumor suppressor TP53, and inactivation of its family member, TAp73. Unexpectedly, we observed that classical stem cell genes Nanog, Sox2, and Oct4, are overexpressed in HNSCC with inactivated TAp73 and mtTP53. However, the potential relationship between CK2, TAp73 inactivation, and CSC phenotype is unknown. We reveal that inhibition of CK2 by pharmacologic inhibitors or siRNA inhibits the expression of CSC genes and side population (SP), while enhancing TAp73 mRNA and protein expression. Conversely, CK2 inhibitor attenuation of CSC protein expression and the SP by was abrogated by TAp73 siRNA. Bioinformatic analysis uncovered a single predicted CK2 threonine phosphorylation site (T27) within the N-terminal transactivation domain of TAp73. Nuclear CK2 and TAp73 interaction, confirmed by co-immunoprecipitation, was attenuated by CK2 inhibitor, or a T27A point-mutation of this predicted CK2 threonine phospho-acceptor site of TAp73. Further, T27A mutation attenuated phosphorylation, while enhancing TAp73 function in repressing CSC gene expression and SP cells. A new CK2 inhibitor, CX-4945, inhibited CSC related SP cells, clonogenic survival, and spheroid formation. Our study unveils a novel regulatory mechanism whereby aberrant CK2 signaling inhibits TAp73 to promote the expression of CSC genes and phenotype.

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

PubMed

Kong, Ru; Li, Jingwei; Orban, Csaba; Sabuncu, Mert R; Liu, Hesheng; Schaefer, Alexander; Sun, Nanbo; Zuo, Xi-Nian; Holmes, Avram J; Eickhoff, Simon B; Yeo, B T Thomas

2018-06-06

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Stargardt disease: towards developing a model to predict phenotype.

PubMed

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.

Stargardt Disease: towards developing a model to predict phenotype

PubMed Central

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 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. PMID:23695285

Diverse Functional Properties of Wilson Disease ATP7B Variants

PubMed Central

Huster, Dominik; Kühne, Angelika; Bhattacharjee, Ashima; Raines, Lily; Jantsch, Vanessa; Noe, Johannes; Schirrmeister, Wiebke; Sommerer, Ines; Sabri, Osama; Berr, Frieder; Mössner, Joachim; Stieger, Bruno; Caca, Karel; Lutsenko, Svetlana

2012-01-01

BACKGROUND & AIMS Wilson disease is a severe disorder of copper metabolism caused by mutations in ATP7B, which encodes a copper-transporting adenosine triphosphatase. The disease presents with a variable phenotype that complicates the diagnostic process and treatment. Little is known about the mechanisms that contribute to the different phenotypes of the disease. METHODS We analyzed 28 variants of ATP7B from patients with Wilson disease that affected different functional domains; the gene products were expressed using the baculovirus expression system in Sf9 cells. Protein function was analyzed by measuring catalytic activity and copper (64Cu) transport into vesicles. We studied intracellular localization of variants of ATP7B that had measurable transport activities and were tagged with green fluorescent protein in mammalian cells using confocal laser scanning microscopy. RESULTS Properties of ATP7B variants with pathogenic amino-acid substitution varied greatly even if substitutions were in the same functional domain. Some variants had complete loss of catalytic and transport activity, whereas others lost transport activity but retained phosphor-intermediate formation or had partial losses of activity. In mammalian cells, transport-competent variants differed in stability and subcellular localization. CONCLUSIONS Variants in ATP7B associated with Wilson disease disrupt the protein’s transport activity, result in its mislocalization, and reduce its stability. Single assays are insufficient to accurately predict the effects of ATP7B variants the function of its product and development of Wilson disease. These findings will contribute to our understanding of genotype–phenotype correlation and mechanisms of disease pathogenesis. PMID:22240481

Fat-Free Mass Index for Evaluating the Nutritional Status and Disease Severity in COPD.

PubMed

Luo, Yuwen; Zhou, Luqian; Li, Yun; Guo, Songwen; Li, Xiuxia; Zheng, Jingjing; Zhu, Zhe; Chen, Yitai; Huang, Yuxia; Chen, Rui; Chen, Xin

2016-05-01

Despite the high prevalence of weight loss in subjects with COPD, the 2011 COPD management guidelines do not include an index measuring nutritional status. Fat-free mass index (FFMI) can accurately determine the nutritional status of subjects and may be closely correlated with COPD severity. We aimed to determine the nutritional status evaluated by FFMI according to the 2011 Global Initiative for Chronic Obstructive Lung Disease (GOLD) levels in stable subjects with COPD and the association between nutritional status and respiratory symptoms, exercise capacity, and respiratory muscle function. We included 235 stable subjects with COPD in this cross-sectional study. All of the subjects were divided into the 2011 GOLD Groups A, B, C, and D. FFMI (measured by bioelectrical impedance), spirometry (FEV1, percent-of-predicted FEV1, and FEV1/FVC), respiratory muscle function (peak inspiratory and peak expiratory pressures), exercise capacity (6-min walk distance), and dyspnea severity (Modified Medical Research Council dyspnea scale) were measured and compared between the GOLD groups. Malnutrition was identified in 48.5% of subjects and most prevalent in Group D (Group A: 41%, Group B: 41%, Group C: 31%, and Group D: 62%). FFMI was significantly lower in Group D (P < .001), with both sexes considered malnourished. Low FFMI significantly correlated with frequent exacerbation, older age, decreased pulmonary function, 6-min walk distance, peak inspiratory pressure, and worsened dyspnea. FFMI was significantly lower in the emphysema-dominant phenotype and mixed phenotype compared with the normal phenotype and airway-dominant phenotype. A stepwise multiple linear regression analysis identified peak inspiratory pressures and older age as independent predictors of FFMI. Malnutrition is highly prevalent in all COPD groups, particularly in Group D subjects, who warrant special attention for nutritional intervention and pulmonary rehabilitation. FFMI significantly correlated with exercise capacity, dyspnea, respiratory muscle function, and pulmonary function and may be a useful predictor of COPD severity. Copyright © 2016 by Daedalus Enterprises.

Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity.

PubMed

Saleheen, Danish; Natarajan, Pradeep; Armean, Irina M; Zhao, Wei; Rasheed, Asif; Khetarpal, Sumeet A; Won, Hong-Hee; Karczewski, Konrad J; O'Donnell-Luria, Anne H; Samocha, Kaitlin E; Weisburd, Benjamin; Gupta, Namrata; Zaidi, Mozzam; Samuel, Maria; Imran, Atif; Abbas, Shahid; Majeed, Faisal; Ishaq, Madiha; Akhtar, Saba; Trindade, Kevin; Mucksavage, Megan; Qamar, Nadeem; Zaman, Khan Shah; Yaqoob, Zia; Saghir, Tahir; Rizvi, Syed Nadeem Hasan; Memon, Anis; Hayyat Mallick, Nadeem; Ishaq, Mohammad; Rasheed, Syed Zahed; Memon, Fazal-Ur-Rehman; Mahmood, Khalid; Ahmed, Naveeduddin; Do, Ron; Krauss, Ronald M; MacArthur, Daniel G; Gabriel, Stacey; Lander, Eric S; Daly, Mark J; Frossard, Philippe; Danesh, John; Rader, Daniel J; Kathiresan, Sekar

2017-04-12

A major goal of biomedicine is to understand the function of every gene in the human genome. Loss-of-function mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such 'human knockouts' can provide insight into gene function. Consanguineous unions are more likely to result in offspring carrying homozygous loss-of-function mutations. In Pakistan, consanguinity rates are notably high. Here we sequence the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS), designed to understand the determinants of cardiometabolic diseases in individuals from South Asia. We identified individuals carrying homozygous predicted loss-of-function (pLoF) mutations, and performed phenotypic analysis involving more than 200 biochemical and disease traits. We enumerated 49,138 rare (<1% minor allele frequency) pLoF mutations. These pLoF mutations are estimated to knock out 1,317 genes, each in at least one participant. Homozygosity for pLoF mutations at PLA2G7 was associated with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; at TREH, with lower concentrations of apoB-containing lipoprotein subfractions; at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations; and at SLC9A3R1, with mediators of calcium and phosphate signalling. Heterozygous deficiency of APOC3 has been shown to protect against coronary heart disease; we identified APOC3 homozygous pLoF carriers in our cohort. We recruited these human knockouts and challenged them with an oral fat load. Compared with family members lacking the mutation, individuals with APOC3 knocked out displayed marked blunting of the usual post-prandial rise in plasma triglycerides. Overall, these observations provide a roadmap for a 'human knockout project', a systematic effort to understand the phenotypic consequences of complete disruption of genes in humans.

Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

PubMed

Watkins, S M

2000-09-01

The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma

PubMed Central

Gossage, Lucy; Pires, Douglas E. V.; Olivera-Nappa, Álvaro; Asenjo, Juan; Bycroft, Mark; Blundell, Tom L.; Eisen, Tim

2014-01-01

Mutations in the von Hippel–Lindau (VHL) gene are pathogenic in VHL disease, congenital polycythaemia and clear cell renal carcinoma (ccRCC). pVHL forms a ternary complex with elongin C and elongin B, critical for pVHL stability and function, which interacts with Cullin-2 and RING-box protein 1 to target hypoxia-inducible factor for polyubiquitination and proteasomal degradation. We describe a comprehensive database of missense VHL mutations linked to experimental and clinical data. We use predictions from in silico tools to link the functional effects of missense VHL mutations to phenotype. The risk of ccRCC in VHL disease is linked to the degree of destabilization resulting from missense mutations. An optimized binary classification system (symphony), which integrates predictions from five in silico methods, can predict the risk of ccRCC associated with VHL missense mutations with high sensitivity and specificity. We use symphony to generate predictions for risk of ccRCC for all possible VHL missense mutations and present these predictions, in association with clinical and experimental data, in a publically available, searchable web server. PMID:24969085

Patterns of adiposity, vascular phenotypes and cognitive function in the 1946 British Birth Cohort.

PubMed

Masi, Stefano; Georgiopoulos, Georgios; Khan, Tauseef; Johnson, William; Wong, Andrew; Charakida, Marietta; Whincup, Peter; Hughes, Alun D; Richards, Marcus; Hardy, Rebecca; Deanfield, John

2018-05-28

The relationship between long-term exposure to whole body or central obesity and cognitive function, as well as its potential determinants, remain controversial. In this study, we assessed (1) the potential impact of 30 years exposure to different patterns of whole body and central adiposity on cognitive function at 60-64 years, (2) whether trajectories of central adiposity can provide additional information on later cognitive function compared to trajectories of whole body adiposity, and (3) the influence of vascular phenotypes on these associations. The study included 1249 participants from the prospective cohort MRC National Survey of Health and Development. Body mass index (BMI), waist circumference (WC), and vascular (carotid intima-media thickness, carotid-femoral pulse wave velocity) and cognitive function (memory, processing speed, reaction time) data, at 60-64 years, were used to assess the associations between different patterns of adult WC or BMI (from 36 years of age) and late midlife cognitive performance, as well as the proportion of this association explained by cardiovascular phenotypes. Longer exposure to elevated WC was related to lower memory performance (p < 0.001 for both) and longer choice reaction time (p = 0.003). A faster gain of WC between 36 and 43 years of age was associated with the largest change in reaction time and memory test (P < 0.05 for all). Similar associations were observed when patterns of WC were substituted with patterns of BMI, but when WC and BMI were included in the same model, only patterns of WC remained significantly associated with cognitive function. Participants who dropped one BMI category and maintained a lower BMI had similar memory performance to those of normal weight during the whole follow-up. Conversely, those who dropped and subsequently regained one BMI category had a memory function similar to those with 30 years exposure to elevated BMI. Adjustment for vascular phenotypes, levels of cardiovascular risk factors, physical activity, education, childhood cognition and socioeconomic position did not affect these associations. Longer exposure to elevated WC or BMI and faster WC or BMI gains between 36 and 43 years are related to lower cognitive function at 60-64 years. Patterns of WC in adulthood could provide additional information in predicting late midlife cognitive function than patterns of BMI. The acquisition of an adverse cardiovascular phenotype associated with adiposity is unlikely to account for these relationships.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines.

PubMed

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

PubMed Central

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

Literature-based prediction of novel drug indications considering relationships between entities.

PubMed

Jang, Giup; Lee, Taekeon; Lee, Byung Mun; Yoon, Youngmi

2017-06-27

There have been many attempts to identify and develop new uses for existing drugs, which is known as drug repositioning. Among these efforts, text mining is an effective means of discovering novel knowledge from a large amount of literature data. We identify a gene regulation by a drug and a phenotype based on the biomedical literature. Drugs or phenotypes can activate or inhibit gene regulation. We calculate the therapeutic possibility that a drug acts on a phenotype by means of these two types of regulation. We assume that a drug treats a phenotype if the genes regulated by the phenotype are inversely correlated with the genes regulated by the drug. Based on this hypothesis, we identify drug-phenotype associations with therapeutic possibility. To validate the drug-phenotype associations predicted by our method, we make an enrichment comparison with known drug-phenotype associations. We also identify candidate drugs for drug repositioning from novel associations and thus reveal that our method is a novel approach to drug repositioning.

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

PubMed

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 go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

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

PubMed Central

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 example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals). Conclusions and Relevance These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual’s risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence. PMID:28196230

Parasitism and the biodiversity-functioning relationship

USGS Publications Warehouse

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.

Dynamic fMRI networks predict success in a behavioral weight loss program among older adults.

PubMed

Mokhtari, Fatemeh; Rejeski, W Jack; Zhu, Yingying; Wu, Guorong; Simpson, Sean L; Burdette, Jonathan H; Laurienti, Paul J

2018-06-01

More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to examine whether these models have clinical utility in tailoring treatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Genome-enabled prediction models for yield related traits in chickpea

USDA-ARS?s Scientific Manuscript database

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

PubMed

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

2015-02-01

Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have specific patterns and tissue-specificity, which are driven by aging and other cancer-inducing agents. This framework represents the logics of complex cancer biology as a myriad of phenotypic complexities governed by a limited set of underlying organizing principles. It therefore adds to our understanding of tumor evolution and tumorigenesis, and moreover, potential usefulness of predicting tumors' evolutionary paths and clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for cancer patients, as well as cancer risks for healthy individuals are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial impact on timely diagnosis, personalized treatment and personalized prevention of cancer. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Prognosis of Pain and Physical Functioning in Patients With Knee Osteoarthritis: A Systematic Review and Meta-Analysis.

PubMed

de Rooij, Mariëtte; van der Leeden, Marike; Heymans, Martijn W; Holla, Jasmijn F M; Häkkinen, Arja; Lems, Willem F; Roorda, Leo D; Veenhof, Cindy; Sanchez-Ramirez, Diana C; de Vet, Henrica C W; Dekker, Joost

2016-04-01

To systematically summarize the literature on the course of pain in patients with knee osteoarthritis (OA), prognostic factors that predict deterioration of pain, the course of physical functioning, and prognostic factors that predict deterioration of physical functioning in persons with knee OA. A search was conducted in PubMed, CINAHL, Embase, Psych-INFO, and SPORTDiscus up to January 2014. A meta-analysis and a qualitative data synthesis were performed. Of the 58 studies included, 39 were of high quality. High heterogeneity across studies (I(2)  >90%) and within study populations (reflected by large SDs of change scores) was found. Therefore, the course of pain and physical functioning was interpreted to be indistinct. We found strong evidence for a number of prognostic factors predicting deterioration in pain (e.g., higher knee pain at baseline, bilateral knee symptoms, and depressive symptoms). We also found strong evidence for a number of prognostic factors predicting deterioration in physical functioning (e.g., worsening in radiographic OA, worsening of knee pain, lower knee extension muscle strength, lower walking speed, and higher comorbidity count). Because of high heterogeneity across studies and within study populations, no conclusions can be drawn with regard to the course of pain and physical functioning. These findings support current research efforts to define subgroups or phenotypes within knee OA populations. Strong evidence was found for knee characteristics, clinical factors, and psychosocial factors as prognostics of deterioration of pain and physical functioning. © 2016, American College of Rheumatology.

First TILLING Platform in Cucurbita pepo: A New Mutant Resource for Gene Function and Crop Improvement

PubMed Central

Vicente-Dólera, Nelly; Troadec, Christelle; Moya, Manuel; del Río-Celestino, Mercedes; Pomares-Viciana, Teresa; Bendahmane, Abdelhafid; Picó, Belén; Román, Belén; Gómez, Pedro

2014-01-01

Although the availability of genetic and genomic resources for Cucurbita pepo has increased significantly, functional genomic resources are still limited for this crop. In this direction, we have developed a high throughput reverse genetic tool: the first TILLING (Targeting Induced Local Lesions IN Genomes) resource for this species. Additionally, we have used this resource to demonstrate that the previous EMS mutant population we developed has the highest mutation density compared with other cucurbits mutant populations. The overall mutation density in this first C. pepo TILLING platform was estimated to be 1/133 Kb by screening five additional genes. In total, 58 mutations confirmed by sequencing were identified in the five targeted genes, thirteen of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was studied in a peroxidase gene, revealing that the phenotype of seedling homozygous for one of the isolated mutant alleles was albino. These results indicate that the TILLING approach in this species was successful at providing new mutations and can address the major challenge of linking sequence information to biological function and also the identification of novel variation for crop breeding. PMID:25386735

Correlation of RNA secondary structure and attenuation of Sabin vaccine strains of poliovirus in tissue culture.

PubMed

Macadam, A J; Ferguson, G; Burlison, J; Stone, D; Skuce, R; Almond, J W; Minor, P D

1992-08-01

Part of the 5' noncoding regions of all three Sabin vaccine strains of poliovirus contains determinants of attenuation that are shown here to influence the ability of these strains to grow at elevated temperatures in BGM cells. The predicted RNA secondary structure of this region (nt 464-542 in P3/Sabin) suggests that both phenotypes are due to perturbation of base-paired stems. Ts phenotypes of site-directed mutants with defined changes in this region correlated well with predicted secondary structure stabilities. Reversal of base-pair orientation had little effect whereas stem disruption led to marked increases in temperature sensitivity. Phenotypic revertants of such viruses displayed mutations on either side of the stem. Mutations destabilizing stems led to intermediate phenotypes. These results provided evidence for the biological significance of the predicted RNA secondary structure.

The PLIN4 Variant rs8887 Modulates Obesity Related Phenotypes in Humans through Creation of a Novel miR-522 Seed Site

PubMed Central

Richardson, Kris; Louie-Gao, Qiong; Arnett, Donna K.; Parnell, Laurence D.; Lai, Chao-Qiang; Davalos, Alberto; Fox, Caroline S.; Demissie, Serkalem; Cupples, L. Adrienne; Fernandez-Hernando, Carlos; Ordovas, Jose M.

2011-01-01

PLIN4 is a member of the PAT family of lipid storage droplet (LSD) proteins. Associations between seven single nucleotide polymorphisms (SNPs) at human PLIN4 with obesity related phenotypes were investigated using meta-analysis followed by a determination if these phenotypes are modulated by interactions between PLIN4 SNPs and dietary PUFA. Samples consisted of subjects from two populations of European ancestry. We demonstrated association of rs8887 with anthropometrics. Meta-analysis demonstrated significant interactions between the rs8887 minor allele with PUFA n3 modulating anthropometrics. rs884164 showed interaction with both n3 and n6 PUFA modulating anthropometric and lipid phenotypes. In silico analysis of the PLIN4 3′UTR sequence surrounding the rs8887 minor A allele predicted a seed site for the human microRNA-522 (miR-522), suggesting a functional mechanism. Our data showed that a PLIN4 3′UTR luciferase reporter carrying the A allele of rs8887 was reduced in response to miR-522 mimics compared to the G allele. These results suggest variation at the PLIN4 locus, and its interaction with PUFA as a modulator of obesity related phenotypes, acts in part through creation of a miR-522 regulatory site. PMID:21533135

Towards precision medicine: from quantitative imaging to radiomics

PubMed Central

Acharya, U. Rajendra; Hagiwara, Yuki; Sudarshan, Vidya K.; Chan, Wai Yee; Ng, Kwan Hoong

2018-01-01

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine. PMID:29308604

Simulating cyanobacterial phenotypes by integrating flux balance analysis, kinetics, and a light distribution function

DOE PAGES

He, Lian; Wu, Stephen G.; Wan, Ni; ...

2015-12-24

In this study, genome-scale models (GSMs) are widely used to predict cyanobacterial phenotypes in photobioreactors (PBRs). However, stoichiometric GSMs mainly focus on fluxome that result in maximal yields. Cyanobacterial metabolism is controlled by both intracellular enzymes and photobioreactor conditions. To connect both intracellular and extracellular information and achieve a better understanding of PBRs productivities, this study integrates a genome-scale metabolic model of Synechocystis 6803 with growth kinetics, cell movements, and a light distribution function. The hybrid platform not only maps flux dynamics in cells of sub-populations but also predicts overall production titer and rate in PBRs. Analysis of the integratedmore » GSM demonstrates several results. First, cyanobacteria are capable of reaching high biomass concentration (>20 g/L in 21 days) in PBRs without light and CO 2 mass transfer limitations. Second, fluxome in a single cyanobacterium may show stochastic changes due to random cell movements in PBRs. Third, insufficient light due to cell self-shading can activate the oxidative pentose phosphate pathway in subpopulation cells. Fourth, the model indicates that the removal of glycogen synthesis pathway may not improve cyanobacterial bio-production in large-size PBRs, because glycogen can support cell growth in the dark zones. Based on experimental data, the integrated GSM estimates that Synechocystis 6803 in shake flask conditions has a photosynthesis efficiency of ~2.7 %. Conclusions: The multiple-scale integrated GSM, which examines both intracellular and extracellular domains, can be used to predict production yield/rate/titer in large-size PBRs. More importantly, genetic engineering strategies predicted by a traditional GSM may work well only in optimal growth conditions. In contrast, the integrated GSM may reveal mutant physiologies in diverse bioreactor conditions, leading to the design of robust strains with high chances of success in industrial settings.« less

Model-driven discovery of underground metabolic functions in Escherichia coli.

PubMed

Guzmán, Gabriela I; Utrilla, José; Nurk, Sergey; Brunk, Elizabeth; Monk, Jonathan M; Ebrahim, Ali; Palsson, Bernhard O; Feist, Adam M

2015-01-20

Enzyme promiscuity toward substrates has been discussed in evolutionary terms as providing the flexibility to adapt to novel environments. In the present work, we describe an approach toward exploring such enzyme promiscuity in the space of a metabolic network. This approach leverages genome-scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence of unknown underground pathways stemming from enzymatic cross-reactivity. We demonstrate a workflow that couples constraint-based modeling and bioinformatic tools with KO strain analysis and adaptive laboratory evolution for the purpose of predicting promiscuity at the genome scale. Three cases of genes that are incorrectly predicted as essential in Escherichia coli--aspC, argD, and gltA--are examined, and isozyme functions are uncovered for each to a different extent. Seven isozyme functions based on genetic and transcriptional evidence are suggested between the genes aspC and tyrB, argD and astC, gabT and puuE, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations.

The Urinary Microbiome Differs Significantly Between Patients With Chronic Prostatitis/Chronic Pelvic Pain Syndrome and Controls as Well as Between Patients With Different Clinical Phenotypes.

PubMed

Shoskes, Daniel A; Altemus, Jessica; Polackwich, Alan S; Tucky, Barbara; Wang, Hannah; Eng, Charis

2016-06-01

To study the urinary microbiome of patients with Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) compared with controls. We identified 25 patients with CP/CPPS and 25 men who were either asymptomatic or only had urinary symptoms. Midstream urine was collected. Symptom severity was measured with the National Institutes of Health Chronic Prostatitis Symptom Index and clinical phenotype with UPOINT. Total DNA was extracted from the urine pellet and bacterial-specific 16Sr-DNA-capture identified by MiSeq sequencing. Taxonomic and functional bioinformatic analyses used principal coordinate analysis (PCoA)/MacQIIME, LEfSe, and PiCRUSt algorithms. Patients and controls were similar ages (52.3 vs 57.0 years, P = .27). For patients, median duration was 48 months, mean Chronic Prostatitis Symptom Index was 26.0, and mean UPOINT domains was 3.6. Weighted 3D UniFrac PCoA revealed tighter clustering of controls distinct from the wider clustering of cases (P = .001; α-diversity P = .005). Seventeen clades were overrepresented in patients, for example, Clostridia, and 5 were underrepresented, eg, Bacilli, resulting in predicted perturbations in functional pathways. PiCRUSt inferred differentially regulated pathways between cases and controls that may be of relevance including sporulation, chemotaxis, and pyruvate metabolism. PCoA-derived microbiomic differences were noted for neurologic/systemic domains (P = .06), whereas LEfSe identified differences associated with each of the 6 clinical features. Urinary microbiomes from patients with CP/CPPS have significantly higher alpha(phylogenetic) diversity which cluster differently from controls, and higher counts of Clostridia compared with controls, resulting in predicted perturbations of functional pathways which could suggest metabolite-specific targeted treatment. Several measures of severity and clinical phenotype have significant microbiome differences. Copyright © 2016 Elsevier Inc. All rights reserved.

On the role of mid-infrared predicted phenotypes in fertility and health dairy breeding programs.

PubMed

Bastin, C; Théron, L; Lainé, A; Gengler, N

2016-05-01

Fertility and health traits are of prime importance in dairy breeding programs. However, these traits are generally complex, difficult to record, and lowly heritable (<0.10), thereby hampering genetic improvement in disease resistance and fertility. Hence, indicators are useful in the prediction of genetic merit for fertility and health traits as long as they are easier to measure than direct fitness traits, heritable, and genetically correlated. Considering that changes in (fine) milk composition over a lactation reflect the physiological status of the cow, mid-infrared (MIR) analysis of milk opens the door to a wide range of potential indicator traits of fertility and health. Previous studies investigated the phenotypic and genetic relationships between fertility and MIR-predicted phenotypes, most being related to negative postpartum energy balance and body fat mobilization (e.g., fat:protein ratio, urea, fatty acids profile). Results showed that a combination of various fatty acid traits (e.g., C18:1 cis-9 and C10:0) could be used to improve fertility. Furthermore, occurrence of (sub)clinical ketosis has been related to milk-based phenotypes such as fat:protein ratio, fatty acids, and ketone bodies. Hence, MIR-predicted acetone and β-hydroxybutyrate contents in milk could be useful for breeding cows less susceptible to ketosis. Although studies investigating the genetic association among mastitis and MIR-predicted phenotypes are scarce, a wide range of traits, potentially predicted by MIR spectrometry, are worthy of consideration. These include traits related to the disease response of the cow (e.g., lactoferrin), reduced secretory activity (e.g., casein), and the alteration of the blood-milk barrier (e.g., minerals). Moreover, direct MIR prediction of fertility and health traits should be further considered. To conclude, MIR-predicted phenotypes have a role to play in the improvement of dairy cow fertility and health. However, further studies are warranted to (1) grasp underlying associations among MIR-predicted indicator and fitness traits, (2) estimate the genetic parameters, and (3) include these traits in broader breeding strategies. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Diguanylate cyclase activity of the Mycobacterium leprae T cell antigen ML1419c

PubMed Central

Rotcheewaphan, Suwatchareeporn; Belisle, John T.; Webb, Kristofor J.; Kim, Hee-Jin; Spencer, John S.

2016-01-01

The second messenger, bis-(3′,5′)-cyclic dimeric guanosine monophosphate (cyclic di-GMP), is involved in the control of multiple bacterial phenotypes, including those that impact host–pathogen interactions. Bioinformatics analyses predicted that Mycobacterium leprae, an obligate intracellular bacterium and the causative agent of leprosy, encodes three active diguanylate cyclases. In contrast, the related pathogen Mycobacterium tuberculosis encodes only a single diguanylate cyclase. One of the M. leprae unique diguanylate cyclases (ML1419c) was previously shown to be produced early during the course of leprosy. Thus, functional analysis of ML1419c was performed. The gene encoding ML1419c was cloned and expressed in Pseudomonas aeruginosa PAO1 to allow for assessment of cyclic di-GMP production and cyclic di-GMP-mediated phenotypes. Phenotypic studies revealed that ml1419c expression altered colony morphology, motility and biofilm formation of P. aeruginosa PAO1 in a manner consistent with increased cyclic di-GMP production. Direct measurement of cyclic di-GMP levels by liquid chromatography–mass spectrometry confirmed that ml1419c expression increased cyclic di-GMP production in P. aeruginosa PAO1 cultures in comparison to the vector control. The observed phenotypes and increased levels of cyclic di-GMP detected in P. aeruginosa expressing ml1419c could be abrogated by mutation of the active site in ML1419c. These studies demonstrated that ML1419c of M. leprae functions as diguanylate cyclase to synthesize cyclic di-GMP. Thus, this protein was renamed DgcA (Diguanylate cyclase A). These results also demonstrated the ability to use P. aeruginosa as a heterologous host for characterizing the function of proteins involved in the cyclic di-GMP pathway of a pathogen refractory to in vitro growth, M. leprae. PMID:27450520

Diguanylate cyclase activity of the Mycobacterium leprae T cell antigen ML1419c.

PubMed

Rotcheewaphan, Suwatchareeporn; Belisle, John T; Webb, Kristofor J; Kim, Hee-Jin; Spencer, John S; Borlee, Bradley R

2016-09-01

The second messenger, bis-(3',5')-cyclic dimeric guanosine monophosphate (cyclic di-GMP), is involved in the control of multiple bacterial phenotypes, including those that impact host-pathogen interactions. Bioinformatics analyses predicted that Mycobacterium leprae, an obligate intracellular bacterium and the causative agent of leprosy, encodes three active diguanylate cyclases. In contrast, the related pathogen Mycobacterium tuberculosis encodes only a single diguanylate cyclase. One of the M. leprae unique diguanylate cyclases (ML1419c) was previously shown to be produced early during the course of leprosy. Thus, functional analysis of ML1419c was performed. The gene encoding ML1419c was cloned and expressed in Pseudomonas aeruginosa PAO1 to allow for assessment of cyclic di-GMP production and cyclic di-GMP-mediated phenotypes. Phenotypic studies revealed that ml1419c expression altered colony morphology, motility and biofilm formation of P. aeruginosa PAO1 in a manner consistent with increased cyclic di-GMP production. Direct measurement of cyclic di-GMP levels by liquid chromatography-mass spectrometry confirmed that ml1419c expression increased cyclic di-GMP production in P. aeruginosa PAO1 cultures in comparison to the vector control. The observed phenotypes and increased levels of cyclic di-GMP detected in P. aeruginosa expressing ml1419c could be abrogated by mutation of the active site in ML1419c. These studies demonstrated that ML1419c of M. leprae functions as diguanylate cyclase to synthesize cyclic di-GMP. Thus, this protein was renamed DgcA (Diguanylate cyclase A). These results also demonstrated the ability to use P. aeruginosa as a heterologous host for characterizing the function of proteins involved in the cyclic di-GMP pathway of a pathogen refractory to in vitro growth, M. leprae.

Dominant KCNA2 mutation causes episodic ataxia and pharmacoresponsive epilepsy.

PubMed

Corbett, Mark A; Bellows, Susannah T; Li, Melody; Carroll, Renée; Micallef, Silvana; Carvill, Gemma L; Myers, Candace T; Howell, Katherine B; Maljevic, Snezana; Lerche, Holger; Gazina, Elena V; Mefford, Heather C; Bahlo, Melanie; Berkovic, Samuel F; Petrou, Steven; Scheffer, Ingrid E; Gecz, Jozef

2016-11-08

To identify the genetic basis of a family segregating episodic ataxia, infantile seizures, and heterogeneous epilepsies and to study the phenotypic spectrum of KCNA2 mutations. A family with 7 affected individuals over 3 generations underwent detailed phenotyping. Whole genome sequencing was performed on a mildly affected grandmother and her grandson with epileptic encephalopathy (EE). Segregating variants were filtered and prioritized based on functional annotations. The effects of the mutation on channel function were analyzed in vitro by voltage clamp assay and in silico by molecular modeling. KCNA2 was sequenced in 35 probands with heterogeneous phenotypes. The 7 family members had episodic ataxia (5), self-limited infantile seizures (5), evolving to genetic generalized epilepsy (4), focal seizures (2), and EE (1). They had a segregating novel mutation in the shaker type voltage-gated potassium channel KCNA2 (CCDS_827.1: c.765_773del; p.255_257del). A rare missense SCN2A (rs200884216) variant was also found in 2 affected siblings and their unaffected mother. The p.255_257del mutation caused dominant negative loss of channel function. Molecular modeling predicted repositioning of critical arginine residues in the voltage-sensing domain. KCNA2 sequencing revealed 1 de novo mutation (CCDS_827.1: c.890G>A; p.Arg297Gln) in a girl with EE, ataxia, and tremor. A KCNA2 mutation caused dominantly inherited episodic ataxia, mild infantile-onset seizures, and later generalized and focal epilepsies in the setting of normal intellect. This observation expands the KCNA2 phenotypic spectrum from EE often associated with chronic ataxia, reflecting the marked variation in severity observed in many ion channel disorders. © 2016 American Academy of Neurology.

The "Transport Specificity Ratio": a structure-function tool to search the protein fold for loci that control transition state stability in membrane transport catalysis

PubMed Central

King, Steven C

2004-01-01

Background In establishing structure-function relationships for membrane transport proteins, the interpretation of phenotypic changes can be problematic, owing to uncertainties in protein expression levels, sub-cellular localization, and protein-folding fidelity. A dual-label competitive transport assay called "Transport Specificity Ratio" (TSR) analysis has been developed that is simple to perform, and circumvents the "expression problem," providing a reliable TSR phenotype (a constant) for comparison to other transporters. Results Using the Escherichia coli GABA (4-aminobutyrate) permease (GabP) as a model carrier, it is demonstrated that the TSR phenotype is largely independent of assay conditions, exhibiting: (i) indifference to the particular substrate concentrations used, (ii) indifference to extreme changes (40-fold) in transporter expression level, and within broad limits (iii) indifference to assay duration. The theoretical underpinnings of TSR analysis predict all of the above observations, supporting that TSR has (i) applicability in the analysis of membrane transport, and (ii) particular utility in the face of incomplete information on protein expression levels and initial reaction rate intervals (e.g., in high-throughput screening situations). The TSR was used to identify gab permease (GabP) variants that exhibit relative changes in catalytic specificity (kcat/Km) for [14C]GABA (4-aminobutyrate) versus [3H]NA (nipecotic acid). Conclusions The TSR phenotype is an easily measured constant that reflects innate molecular properties of the transition state, and provides a reliable index of the difference in catalytic specificity that a carrier exhibits toward a particular pair of substrates. A change in the TSR phenotype, called a Δ(TSR), represents a specificity shift attributable to underlying changes in the intrinsic substrate binding energy (ΔGb) that translocation catalysts rely upon to decrease activation energy (). TSR analysis is therefore a structure-function tool that enables parsimonious scanning for positions in the protein fold that couple to the transition state, creating stability and thereby serving as functional determinants of catalytic power (efficiency, or specificity). PMID:15548327

Self-reported pigmentary phenotypes and race are significant but incomplete predictors of Fitzpatrick skin phototype in an ethnically diverse population.

PubMed

He, Steven Y; McCulloch, Charles E; Boscardin, W John; Chren, Mary-Margaret; Linos, Eleni; Arron, Sarah T

2014-10-01

Fitzpatrick skin phototype (FSPT) is the most common method used to assess sunburn risk and is an independent predictor of skin cancer risk. Because of a conventional assumption that FSPT is predictable based on pigmentary phenotypes, physicians frequently estimate FSPT based on patient appearance. We sought to determine the degree to which self-reported race and pigmentary phenotypes are predictive of FSPT in a large, ethnically diverse population. A cross-sectional survey collected responses from 3386 individuals regarding self-reported FSPT, pigmentary phenotypes, race, age, and sex. Univariate and multivariate logistic regression analyses were performed to determine variables that significantly predict FSPT. Race, sex, skin color, eye color, and hair color are significant but weak independent predictors of FSPT (P<.0001). A multivariate model constructed using all independent predictors of FSPT only accurately predicted FSPT to within 1 point on the Fitzpatrick scale with 92% accuracy (weighted kappa statistic 0.53). Our study enriched for responses from ethnic minorities and does not fully represent the demographics of the US population. Patient self-reported race and pigmentary phenotypes are inaccurate predictors of sun sensitivity as defined by FSPT. There are limitations to using patient-reported race and appearance in predicting individual sunburn risk. Copyright © 2014 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

News from the protein mutability landscape.

PubMed

Hecht, Maximilian; Bromberg, Yana; Rost, Burkhard

2013-11-01

Some mutations of protein residues matter more than others, and these are often conserved evolutionarily. The explosion of deep sequencing and genotyping increasingly requires the distinction between effect and neutral variants. The simplest approach predicts all mutations of conserved residues to have an effect; however, this works poorly, at best. Many computational tools that are optimized to predict the impact of point mutations provide more detail. Here, we expand the perspective from the view of single variants to the level of sketching the entire mutability landscape. This landscape is defined by the impact of substituting every residue at each position in a protein by each of the 19 non-native amino acids. We review some of the powerful conclusions about protein function, stability and their robustness to mutation that can be drawn from such an analysis. Large-scale experimental and computational mutagenesis experiments are increasingly furthering our understanding of protein function and of the genotype-phenotype associations. We also discuss how these can be used to improve predictions of protein function and pathogenicity of missense variants. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications.

PubMed

Howrylak, Judie A; Fuhlbrigge, Anne L; Strunk, Robert C; Zeiger, Robert S; Weiss, Scott T; Raby, Benjamin A

2014-05-01

Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P < .0001) or additional controller medications (P = .001), as well as longitudinal differences in pulmonary function (P < .0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P = .02) and nedocromil (P = .01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P = .12) and nedocromil (P = .56) compared with placebo. Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

Seed maturation associated transcriptional programs and regulatory networks underlying genotypic difference in seed dormancy and size/weight in wheat (Triticum aestivum L.).

PubMed

Yamasaki, Yuji; Gao, Feng; Jordan, Mark C; Ayele, Belay T

2017-09-16

Maturation forms one of the critical seed developmental phases and it is characterized mainly by programmed cell death, dormancy and desiccation, however, the transcriptional programs and regulatory networks underlying acquisition of dormancy and deposition of storage reserves during the maturation phase of seed development are poorly understood in wheat. The present study performed comparative spatiotemporal transcriptomic analysis of seed maturation in two wheat genotypes with contrasting seed weight/size and dormancy phenotype. The embryo and endosperm tissues of maturing seeds appeared to exhibit genotype-specific temporal shifts in gene expression profile that might contribute to the seed phenotypic variations. Functional annotations of gene clusters suggest that the two tissues exhibit distinct but genotypically overlapping molecular functions. Motif enrichment predicts genotypically distinct abscisic acid (ABA) and gibberellin (GA) regulated transcriptional networks contribute to the contrasting seed weight/size and dormancy phenotypes between the two genotypes. While other ABA responsive element (ABRE) motifs are enriched in both genotypes, the prevalence of G-box-like motif specifically in tissues of the dormant genotype suggests distinct ABA mediated transcriptional mechanisms control the establishment of dormancy during seed maturation. In agreement with this, the bZIP transcription factors that co-express with ABRE enriched embryonic genes differ with genotype. The enrichment of SITEIIATCYTC motif specifically in embryo clusters of maturing seeds irrespective of genotype predicts a tissue specific role for the respective TCP transcription factors with no or minimal contribution to the variations in seed dormancy. The results of this study advance our understanding of the seed maturation associated molecular mechanisms underlying variation in dormancy and weight/size in wheat seeds, which is a critical step towards the designing of molecular strategies for enhancing seed yield and quality.

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

PubMed

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.

Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs.

PubMed

Hidalgo, A M; Bastiaansen, J W M; Lopes, M S; Veroneze, R; Groenen, M A M; de Koning, D-J

2015-07-01

Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.

Kindler syndrome: extension of FERMT1 mutational spectrum and natural history.

PubMed

Has, Cristina; Castiglia, Daniele; del Rio, Marcela; Diez, Marta Garcia; Piccinni, Eugenia; Kiritsi, Dimitra; Kohlhase, Jürgen; Itin, Peter; Martin, Ludovic; Fischer, Judith; Zambruno, Giovanna; Bruckner-Tuderman, Leena

2011-11-01

Mutations in the FERMT1 gene (also known as KIND1), encoding the focal adhesion protein kindlin-1, underlie the Kindler syndrome (KS), an autosomal recessive skin disorder with an intriguing progressive phenotype comprising skin blistering, photosensitivity, progressive poikiloderma with extensive skin atrophy, and propensity to skin cancer. Herein we review the clinical and genetic data of 62 patients, and delineate the natural history of the disorder, for example, age at onset of symptoms, or risk of malignancy. Although most mutations are predicted to lead to premature termination of translation, and to loss of kindlin-1 function, significant clinical variability is observed among patients. There is an association of FERMT1 missense and in-frame deletion mutations with milder disease phenotypes, and later onset of complications. Nevertheless, the clinical variability is not fully explained by genotype-phenotype correlations. Environmental factors and yet unidentified modifiers may play a role. Better understanding of the molecular pathogenesis of KS should enable the development of prevention strategies for disease complications. © 2011 Wiley Periodicals, Inc.

Modeling the clinical phenotype of BTK inhibition in the mature murine immune system.

PubMed

Benson, Micah J; Rodriguez, Varenka; von Schack, David; Keegan, Sean; Cook, Tim A; Edmonds, Jason; Benoit, Stephen; Seth, Nilufer; Du, Sarah; Messing, Dean; Nickerson-Nutter, Cheryl L; Dunussi-Joannopoulos, Kyri; Rankin, Andrew L; Ruzek, Melanie; Schnute, Mark E; Douhan, John

2014-07-01

Inhibitors of Bruton's tyrosine kinase (BTK) possess much promise for the treatment of oncologic and autoimmune indications. However, our current knowledge of the role of BTK in immune competence has been gathered in the context of genetic inactivation of btk in both mice and man. Using the novel BTK inhibitor PF-303, we model the clinical phenotype of BTK inhibition by systematically examining the impact of PF-303 on the mature immune system in mice. We implicate BTK in tonic BCR signaling, demonstrate dependence of the T3 B cell subset and IgM surface expression on BTK activity, and find that B1 cells survive and function independently of BTK. Although BTK inhibition does not impact humoral memory survival, Ag-driven clonal expansion of memory B cells and Ab-secreting cell generation are inhibited. These data define the role of BTK in the mature immune system and mechanistically predict the clinical phenotype of chronic BTK inhibition. Copyright © 2014 by The American Association of Immunologists, Inc.

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

PubMed

Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

2015-03-01

A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

Automated Protocol for Large-Scale Modeling of Gene Expression Data.

PubMed

Hall, Michelle Lynn; Calkins, David; Sherman, Woody

2016-11-28

With the continued rise of phenotypic- and genotypic-based screening projects, computational methods to analyze, process, and ultimately make predictions in this field take on growing importance. Here we show how automated machine learning workflows can produce models that are predictive of differential gene expression as a function of a compound structure using data from A673 cells as a proof of principle. In particular, we present predictive models with an average accuracy of greater than 70% across a highly diverse ∼1000 gene expression profile. In contrast to the usual in silico design paradigm, where one interrogates a particular target-based response, this work opens the opportunity for virtual screening and lead optimization for desired multitarget gene expression profiles.

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

PubMed

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.

Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

USDA-ARS?s Scientific Manuscript database

The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

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

Treesearch

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...

Enabling phenotypic big data with PheNorm.

PubMed

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

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

PubMed Central

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

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

PubMed

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.

Pre-mRNA Splicing in Plants: In Vivo Functions of RNA-Binding Proteins Implicated in the Splicing Process

PubMed Central

Meyer, Katja; Koester, Tino; Staiger, Dorothee

2015-01-01

Alternative pre-messenger RNA splicing in higher plants emerges as an important layer of regulation upon exposure to exogenous and endogenous cues. Accordingly, mutants defective in RNA-binding proteins predicted to function in the splicing process show severe phenotypic alterations. Among those are developmental defects, impaired responses to pathogen threat or abiotic stress factors, and misregulation of the circadian timing system. A suite of splicing factors has been identified in the model plant Arabidopsis thaliana. Here we summarize recent insights on how defects in these splicing factors impair plant performance. PMID:26213982

Molecular deconstruction, detection, and computational prediction of microenvironment-modulated cellular responses to cancer therapeutics.

PubMed

Labarge, Mark A; Parvin, Bahram; Lorens, James B

2014-04-01

The field of bioengineering has pioneered the application of new precision fabrication technologies to model the different geometric, physical or molecular components of tissue microenvironments on solid-state substrata. Tissue engineering approaches building on these advances are used to assemble multicellular mimetic-tissues where cells reside within defined spatial contexts. The functional responses of cells in fabricated microenvironments have revealed a rich interplay between the genome and extracellular effectors in determining cellular phenotypes and in a number of cases have revealed the dominance of microenvironment over genotype. Precision bioengineered substrata are limited to a few aspects, whereas cell/tissue-derived microenvironments have many undefined components. Thus, introducing a computational module may serve to integrate these types of platforms to create reasonable models of drug responses in human tissues. This review discusses how combinatorial microenvironment microarrays and other biomimetic microenvironments have revealed emergent properties of cells in particular microenvironmental contexts, the platforms that can measure phenotypic changes within those contexts, and the computational tools that can unify the microenvironment-imposed functional phenotypes with underlying constellations of proteins and genes. Ultimately we propose that a merger of these technologies will enable more accurate pre-clinical drug discovery. Copyright © 2014 Elsevier B.V. All rights reserved.

Polarity-defective mutants of Aspergillus nidulans.

PubMed

Osherov, N; Mathew, J; May, G S

2000-12-01

We have identified two polarity-defective (pod) mutants in Aspergillus nidulans from a collection of heat-sensitive lethal mutants. At restrictive temperature, these mutants are capable of nuclear division but are unable to establish polar hyphal growth. We cloned the two pod genes by complementation of their heat-sensitive lethal phenotypes. The libraries used to clone the pod genes are under the control of the bidirectional niaD and niiA promoters. Complementation of the pod mutants is dependent on growth on inducing medium. We show that rescue of the heat-sensitive phenotype on inducing media is independent of the orientation of the gene relative to the niaD or niiA promoters, demonstrating that the intergenic region between the niaD and the niiA genes functions as an orientation-independent enhancer and repressor that is capable of functioning over long distances. The products of the podG and the podH genes were identified as homologues of the alpha subunit of yeast mitochondrial phenylalanyl--tRNA synthetase and transcription factor IIF interacting component of the CTD phosphatase. Neither of these gene products would have been predicted to produce a pod mutant phenotype based on studies of cellular polarity mutants in other organisms. The implications of these results are discussed. Copyright 2000 Academic Press.

WormQTLHD—a web database for linking human disease to natural variation data in C. elegans

PubMed Central

van der Velde, K. Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L. Basten; Kammenga, Jan E.; Jansen, Ritsert C.; Swertz, Morris A.; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism—Caenorhabditis elegans—has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTLHD (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene–disease associations in man. WormQTLHD, available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene–disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench. PMID:24217915

WormQTLHD--a web database for linking human disease to natural variation data in C. elegans.

PubMed

van der Velde, K Joeri; de Haan, Mark; Zych, Konrad; Arends, Danny; Snoek, L Basten; Kammenga, Jan E; Jansen, Ritsert C; Swertz, Morris A; Li, Yang

2014-01-01

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism-Caenorhabditis elegans-has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTL(HD) (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene-disease associations in man. WormQTL(HD), available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene-disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench.

Transcriptome analysis of a wild bird reveals physiological responses to the urban environment

PubMed Central

Watson, Hannah; Videvall, Elin; Andersson, Martin N.; Isaksson, Caroline

2017-01-01

Identifying the molecular basis of environmentally induced phenotypic variation presents exciting opportunities for furthering our understanding of how ecological processes and the environment can shape the phenotype. Urban and rural environments present free-living organisms with different challenges and opportunities, which have marked consequences for the phenotype, yet little is known about responses at the molecular level. We characterised transcriptomes from an urban and a rural population of great tits Parus major, demonstrating striking differences in gene expression profiles in both blood and liver tissues. Differentially expressed genes had functions related to immune and inflammatory responses, detoxification, protection against oxidative stress, lipid metabolism, and regulation of gene expression. Many genes linked to stress responses were expressed at higher levels in the urban birds, in accordance with our prediction that urban animals are exposed to greater environmental stress. This is one of the first studies to reveal transcriptional differences between urban- and rural-dwelling animals and suggests an important role for epigenetics in mediating environmentally induced physiological variation. The study provides valuable resources for developing further in-depth studies of the mechanisms driving phenotypic variation in the urban context at larger spatial and temporal scales. PMID:28290496

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine.

PubMed

Martell, Henry J; Wong, Kathie A; Martin, Juan F; Kassam, Ziyan; Thomas, Kay; Wass, Mark N

2017-08-11

Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria.

Phenotypic switching in bacteria

NASA Astrophysics Data System (ADS)

Merrin, Jack

Living matter is a non-equilibrium system in which many components work in parallel to perpetuate themselves through a fluctuating environment. Physiological states or functionalities revealed by a particular environment are called phenotypes. Transitions between phenotypes may occur either spontaneously or via interaction with the environment. Even in the same environment, genetically identical bacteria can exhibit different phenotypes of a continuous or discrete nature. In this thesis, we pursued three lines of investigation into discrete phenotypic heterogeneity in bacterial populations: the quantitative characterization of the so-called bacterial persistence, a theoretical model of phenotypic switching based on those measurements, and the design of artificial genetic networks which implement this model. Persistence is the phenotype of a subpopulation of bacteria with a reduced sensitivity to antibiotics. We developed a microfluidic apparatus, which allowed us to monitor the growth rates of individual cells while applying repeated cycles of antibiotic treatments. We were able to identify distinct phenotypes (normal and persistent) and characterize the stochastic transitions between them. We also found that phenotypic heterogeneity was present prior to any environmental cue such as antibiotic exposure. Motivated by the experiments with persisters, we formulated a theoretical model describing the dynamic behavior of several discrete phenotypes in a periodically varying environment. This theoretical framework allowed us to quantitatively predict the fitness of dynamic populations and to compare survival strategies according to environmental time-symmetries. These calculations suggested that persistence is a strategy used by bacterial populations to adapt to fluctuating environments. Knowledge of the phenotypic transition rates for persistence may provide statistical information about the typical environments of bacteria. We also describe a design of artificial genetic networks that would implement a more general theoretical model of phenotypic switching. We will use a new cloning strategy in order to systematically assemble a large number of genetic features, such as site-specific recombination components from the R64 plasmid, which invert several coexisting DNA segments. The inversion of these segments would lead to discrete phenotypic transitions inside a living cell. These artificial phenotypic switches can be controlled precisely in experiments and may serve as a benchmark for their natural counterparts.

Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus

NASA Astrophysics Data System (ADS)

Lobo, Daniel; Lobikin, Maria; Levin, Michael

2017-01-01

Progress in regenerative medicine requires reverse-engineering cellular control networks to infer perturbations with desired systems-level outcomes. Such dynamic models allow phenotypic predictions for novel perturbations to be rapidly assessed in silico. Here, we analyzed a Xenopus model of conversion of melanocytes to a metastatic-like phenotype only previously observed in an all-or-none manner. Prior in vivo genetic and pharmacological experiments showed that individual animals either fully convert or remain normal, at some characteristic frequency after a given perturbation. We developed a Machine Learning method which inferred a model explaining this complex, stochastic all-or-none dataset. We then used this model to ask how a new phenotype could be generated: animals in which only some of the melanocytes converted. Systematically performing in silico perturbations, the model predicted that a combination of altanserin (5HTR2 inhibitor), reserpine (VMAT inhibitor), and VP16-XlCreb1 (constitutively active CREB) would break the all-or-none concordance. Remarkably, applying the predicted combination of three reagents in vivo revealed precisely the expected novel outcome, resulting in partial conversion of melanocytes within individuals. This work demonstrates the capability of automated analysis of dynamic models of signaling networks to discover novel phenotypes and predictively identify specific manipulations that can reach them.

The structural effects of mutations can aid in differential phenotype prediction of beta-myosin heavy chain (Myosin-7) missense variants.

PubMed

Al-Numair, Nouf S; Lopes, Luis; Syrris, Petros; Monserrat, Lorenzo; Elliott, Perry; Martin, Andrew C R

2016-10-01

High-throughput sequencing platforms are increasingly used to screen patients with genetic disease for pathogenic mutations, but prediction of the effects of mutations remains challenging. Previously we developed SAAPdap (Single Amino Acid Polymorphism Data Analysis Pipeline) and SAAPpred (Single Amino Acid Polymorphism Predictor) that use a combination of rule-based structural measures to predict whether a missense genetic variant is pathogenic. Here we investigate whether the same methodology can be used to develop a differential phenotype predictor, which, once a mutation has been predicted as pathogenic, is able to distinguish between phenotypes-in this case the two major clinical phenotypes (hypertrophic cardiomyopathy, HCM and dilated cardiomyopathy, DCM) associated with mutations in the beta-myosin heavy chain (MYH7) gene product (Myosin-7). A random forest predictor trained on rule-based structural analyses together with structural clustering data gave a Matthews' correlation coefficient (MCC) of 0.53 (accuracy, 75%). A post hoc removal of machine learning models that performed particularly badly, increased the performance (MCC = 0.61, Acc = 79%). This proof of concept suggests that methods used for pathogenicity prediction can be extended for use in differential phenotype prediction. Analyses were implemented in Perl and C and used the Java-based Weka machine learning environment. Please contact the authors for availability. andrew@bioinf.org.uk or andrew.martin@ucl.ac.uk Supplementary data are available at Bioinformatics online. © The Authors 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evidence-Based Annotation of Gene Function in Shewanella oneidensis MR-1 Using Genome-Wide Fitness Profiling across 121 Conditions

PubMed Central

Deutschbauer, Adam; Price, Morgan N.; Wetmore, Kelly M.; Shao, Wenjun; Baumohl, Jason K.; Xu, Zhuchen; Nguyen, Michelle; Tamse, Raquel; Davis, Ronald W.; Arkin, Adam P.

2011-01-01

Most genes in bacteria are experimentally uncharacterized and cannot be annotated with a specific function. Given the great diversity of bacteria and the ease of genome sequencing, high-throughput approaches to identify gene function experimentally are needed. Here, we use pools of tagged transposon mutants in the metal-reducing bacterium Shewanella oneidensis MR-1 to probe the mutant fitness of 3,355 genes in 121 diverse conditions including different growth substrates, alternative electron acceptors, stresses, and motility. We find that 2,350 genes have a pattern of fitness that is significantly different from random and 1,230 of these genes (37% of our total assayed genes) have enough signal to show strong biological correlations. We find that genes in all functional categories have phenotypes, including hundreds of hypotheticals, and that potentially redundant genes (over 50% amino acid identity to another gene in the genome) are also likely to have distinct phenotypes. Using fitness patterns, we were able to propose specific molecular functions for 40 genes or operons that lacked specific annotations or had incomplete annotations. In one example, we demonstrate that the previously hypothetical gene SO_3749 encodes a functional acetylornithine deacetylase, thus filling a missing step in S. oneidensis metabolism. Additionally, we demonstrate that the orphan histidine kinase SO_2742 and orphan response regulator SO_2648 form a signal transduction pathway that activates expression of acetyl-CoA synthase and is required for S. oneidensis to grow on acetate as a carbon source. Lastly, we demonstrate that gene expression and mutant fitness are poorly correlated and that mutant fitness generates more confident predictions of gene function than does gene expression. The approach described here can be applied generally to create large-scale gene-phenotype maps for evidence-based annotation of gene function in prokaryotes. PMID:22125499

The Gemin associates of survival motor neuron are required for motor function in Drosophila.

PubMed

Borg, Rebecca; Cauchi, Ruben J

2013-01-01

Membership of the survival motor neuron (SMN) complex extends to nine factors, including the SMN protein, the product of the spinal muscular atrophy (SMA) disease gene, Gemins 2-8 and Unrip. The best-characterised function of this macromolecular machine is the assembly of the Sm-class of uridine-rich small nuclear ribonucleoprotein (snRNP) particles and each SMN complex member has a key role during this process. So far, however, only little is known about the function of the individual Gemin components in vivo. Here, we make use of the Drosophila model organism to uncover loss-of-function phenotypes of Gemin2, Gemin3 and Gemin5, which together with SMN form the minimalistic fly SMN complex. We show that ectopic overexpression of the dead helicase Gem3(ΔN) mutant or knockdown of Gemin3 result in similar motor phenotypes, when restricted to muscle, and in combination cause lethality, hence suggesting that Gem3(ΔN) overexpression mimics a loss-of-function. Based on the localisation pattern of Gem3(ΔN), we predict that the nucleus is the primary site of the antimorphic or dominant-negative mechanism of Gem3(ΔN)-mediated interference. Interestingly, phenotypes induced by human SMN overexpression in Drosophila exhibit similarities to those induced by overexpression of Gem3(ΔN). Through enhanced knockdown we also uncover a requirement of Gemin2, Gemin3 and Gemin5 for viability and motor behaviour, including locomotion as well as flight, in muscle. Notably, in the case of Gemin3 and Gemin5, such function also depends on adequate levels of the respective protein in neurons. Overall, these findings lead us to speculate that absence of any one member is sufficient to arrest the SMN-Gemins complex function in a nucleocentric pathway, which is critical for motor function in vivo.

Parametric and Nonparametric Statistical Methods for Genomic Selection of Traits with Additive and Epistatic Genetic Architectures

PubMed Central

Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.

2014-01-01

Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289

Integrating Milk Metabolite Profile Information for the Prediction of Traditional Milk Traits Based on SNP Information for Holstein Cows

PubMed Central

Melzer, Nina; Wittenburg, Dörte; Repsilber, Dirk

2013-01-01

In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach). To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL) were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317) SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype). PMID:23990900

Single nucleotide variations: Biological impact and theoretical interpretation

PubMed Central

Katsonis, Panagiotis; Koire, Amanda; Wilson, Stephen Joseph; Hsu, Teng-Kuei; Lua, Rhonald C; Wilkins, Angela Dawn; Lichtarge, Olivier

2014-01-01

Genome-wide association studies (GWAS) and whole-exome sequencing (WES) generate massive amounts of genomic variant information, and a major challenge is to identify which variations drive disease or contribute to phenotypic traits. Because the majority of known disease-causing mutations are exonic non-synonymous single nucleotide variations (nsSNVs), most studies focus on whether these nsSNVs affect protein function. Computational studies show that the impact of nsSNVs on protein function reflects sequence homology and structural information and predict the impact through statistical methods, machine learning techniques, or models of protein evolution. Here, we review impact prediction methods and discuss their underlying principles, their advantages and limitations, and how they compare to and complement one another. Finally, we present current applications and future directions for these methods in biological research and medical genetics. PMID:25234433

Predicting the Pathogenicity of Aminoacyl-tRNA Synthetase Mutations

PubMed Central

Oprescu, Stephanie N.; Griffin, Laurie B.; Beg, Asim A.; Antonellis, Anthony

2016-01-01

Aminoacyl-tRNA synthetases (ARSs) are ubiquitously expressed, essential enzymes responsible for charging tRNA with cognate amino acids—the first step in protein synthesis. ARSs are required for protein translation in the cytoplasm and mitochondria of all cells. Surprisingly, mutations in 28 of the 37 nuclear-encoded human ARS genes have been linked to a variety of recessive and dominant tissue-specific disorders. Current data sustains that impaired enzyme function is a robust predictor of the pathogenicity of ARS mutations. However, experimental model systems that distinguish between pathogenic and non-pathogenic ARS variants are required for implicating newly identified ARS mutations in disease. Here, we outline strategies to assist in predicting the pathogenicity of ARS variants and urge cautious evaluation of genetic and functional data prior to linking an ARS mutation to a human disease phenotype. PMID:27876679

CSF tau and tau/Aβ42 predict cognitive decline in Parkinson's disease.

PubMed

Liu, Changqin; Cholerton, Brenna; Shi, Min; Ginghina, Carmen; Cain, Kevin C; Auinger, Peggy; Zhang, Jing

2015-03-01

A substantial proportion of patients with Parkinson's disease (PD) have concomitant cognitive dysfunction. Identification of biomarker profiles that predict which PD patients have a greater likelihood for progression of cognitive symptoms is pressingly needed for future treatment and prevention approaches. Subjects were drawn from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, a large clinical trial that enrolled initially untreated PD patients. For the current study, Phase One encompassed trial baseline until just prior to levodopa administration (n = 403), and Phase Two spanned the initiation of levodopa treatment until the end of cognitive follow-up (n = 305). Correlations and linear mixed models were performed to determine cross-sectional and longitudinal associations between baseline amyloid β1-42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF) and measures of memory and executive function. Analyses also considered APOE genotype and tremor- vs. rigidity-dominant phenotype. No association was found between baseline CSF biomarkers and cognitive test performance during Phase One. However, once levodopa treatment was initiated, higher p-tau and p-tau/Aβ42 predicted subsequent decline on cognitive tasks involving both memory and executive functions. The interactions between biomarkers and cognition decline did not appear to be influenced by levodopa dosage, APOE genotype or motor phenotype. The current study has, for the first time, demonstrated the possible involvement of tau species, whose gene (MAPT) has been consistently linked to the risk of PD by genome-wide association studies, in the progression of cognitive symptoms in PD. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification and Characterization of LFD-2, a Predicted Fringe Protein Required for Membrane Integrity during Cell Fusion in Neurospora crassa

PubMed Central

Palma-Guerrero, Javier; Zhao, Jiuhai; Gonçalves, A. Pedro; Starr, Trevor L.

2015-01-01

The molecular mechanisms of membrane merger during somatic cell fusion in eukaryotic species are poorly understood. In the filamentous fungus Neurospora crassa, somatic cell fusion occurs between genetically identical germinated asexual spores (germlings) and between hyphae to form the interconnected network characteristic of a filamentous fungal colony. In N. crassa, two proteins have been identified to function at the step of membrane fusion during somatic cell fusion: PRM1 and LFD-1. The absence of either one of these two proteins results in an increase of germling pairs arrested during cell fusion with tightly appressed plasma membranes and an increase in the frequency of cell lysis of adhered germlings. The level of cell lysis in ΔPrm1 or Δlfd-1 germlings is dependent on the extracellular calcium concentration. An available transcriptional profile data set was used to identify genes encoding predicted transmembrane proteins that showed reduced expression levels in germlings cultured in the absence of extracellular calcium. From these analyses, we identified a mutant (lfd-2, for late fusion defect-2) that showed a calcium-dependent cell lysis phenotype. lfd-2 encodes a protein with a Fringe domain and showed endoplasmic reticulum and Golgi membrane localization. The deletion of an additional gene predicted to encode a low-affinity calcium transporter, fig1, also resulted in a strain that showed a calcium-dependent cell lysis phenotype. Genetic analyses showed that LFD-2 and FIG1 likely function in separate pathways to regulate aspects of membrane merger and repair during cell fusion. PMID:25595444

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

USDA-ARS?s Scientific Manuscript database

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...

Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

Non-additive genetic variation in growth, carcass and fertility traits of beef cattle.

PubMed

Bolormaa, Sunduimijid; Pryce, Jennie E; Zhang, Yuandan; Reverter, Antonio; Barendse, William; Hayes, Ben J; Goddard, Michael E

2015-04-02

A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance. Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.

Understanding epigenetic architecture of suicide neurobiology: A critical perspective

PubMed Central

Roy, Bhaskar; Dwivedi, Yogesh

2016-01-01

Current understanding of environmental cross-talk with genetic makeup is found to be mediated through an epigenetic interface which is associated with prominent reversible and heritable changes at gene expression level. Recent emergence of epigenetic modulation in shaping the genetic information has become a key regulatory factor in answering the underlying complexities associated with several mental disorders. A comprehensive understanding of the pertinent changes in the epigenetic makeup of suicide phenotype exhibits a characteristic signature with the possibility of using it as a biomarker to help predict the risk factors associated with suicide. Within the scope of this current review, the most sought after epigenetic changes of DNA methylation and histone modification are thoroughly scrutinized to understand their close functional association with the broad spectrum of suicide phenotype. PMID:27836463

Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors

PubMed Central

Guo, Maozu; Guo, Yahong; Li, Jinbao; Ding, Jian; Liu, Yong; Dai, Qiguo; Li, Jin; Teng, Zhixia; Huang, Yufei

2013-01-01

Background The identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies. Methodology/Principal Findings It is known that miRNAs with similar functions are often associated with similar diseases and vice versa. Therefore, the functional similarity of two miRNAs has been successfully estimated by measuring the semantic similarity of their associated diseases. To effectively predict disease miRNAs, we calculated the functional similarity by incorporating the information content of disease terms and phenotype similarity between diseases. Furthermore, the members of miRNA family or cluster are assigned higher weight since they are more probably associated with similar diseases. A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs. Experiments validated that HDMP achieved significantly higher prediction performance than existing methods. In addition, the case studies examining prostatic neoplasms, breast neoplasms, and lung neoplasms, showed that HDMP can uncover potential disease miRNA candidates. Conclusions The superior performance of HDMP can be attributed to the accurate measurement of miRNA functional similarity, the weight assignment based on miRNA family or cluster, and the effective prediction based on weighted k most similar neighbors. The online prediction and analysis tool is freely available at http://nclab.hit.edu.cn/hdmpred. PMID:23950912

Punctuated Emergences of Genetic and Phenotypic Innovations in Eumetazoan, Bilaterian, Euteleostome, and Hominidae Ancestors

PubMed Central

Wenger, Yvan; Galliot, Brigitte

2013-01-01

Phenotypic traits derive from the selective recruitment of genetic materials over macroevolutionary times, and protein-coding genes constitute an essential component of these materials. We took advantage of the recent production of genomic scale data from sponges and cnidarians, sister groups from eumetazoans and bilaterians, respectively, to date the emergence of human proteins and to infer the timing of acquisition of novel traits through metazoan evolution. Comparing the proteomes of 23 eukaryotes, we find that 33% human proteins have an ortholog in nonmetazoan species. This premetazoan proteome associates with 43% of all annotated human biological processes. Subsequently, four major waves of innovations can be inferred in the last common ancestors of eumetazoans, bilaterians, euteleostomi (bony vertebrates), and hominidae, largely specific to each epoch, whereas early branching deuterostome and chordate phyla show very few innovations. Interestingly, groups of proteins that act together in their modern human functions often originated concomitantly, although the corresponding human phenotypes frequently emerged later. For example, the three cnidarians Acropora, Nematostella, and Hydra express a highly similar protein inventory, and their protein innovations can be affiliated either to traits shared by all eumetazoans (gut differentiation, neurogenesis); or to bilaterian traits present in only some cnidarians (eyes, striated muscle); or to traits not identified yet in this phylum (mesodermal layer, endocrine glands). The variable correspondence between phenotypes predicted from protein enrichments and observed phenotypes suggests that a parallel mechanism repeatedly produce similar phenotypes, thanks to novel regulatory events that independently tie preexisting conserved genetic modules. PMID:24065732

Predicting plant biomass accumulation from image-derived parameters

PubMed Central

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

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Recessive NRL mutations in patients with clumped pigmentary retinal degeneration and relative preservation of blue cone function.

PubMed

Nishiguchi, Koji M; Friedman, James S; Sandberg, Michael A; Swaroop, Anand; Berson, Eliot L; Dryja, Thaddeus P

2004-12-21

Mice lacking the transcription factor Nrl have no rod photoreceptors and an increased number of short-wavelength-sensitive cones. Missense mutations in NRL are associated with autosomal dominant retinitis pigmentosa; however, the phenotype associated with the loss of NRL function in humans has not been reported. We identified two siblings who carried two allelic mutations: a predicted null allele (L75fs) and a missense mutation (L160P) altering a highly conserved residue in the domain involved in DNA-binding-site recognition. In vitro luciferase reporter assays demonstrated that the NRL-L160P mutant had severely reduced transcriptional activity compared with the WT NRL protein, consistent with a severe loss of function. The affected patients had night blindness since early childhood, consistent with a severe reduction in rod function. Color vision was normal, suggesting the presence of all cone color types; nevertheless, a comparison of central visual fields evaluated with white-on-white and blue-on-yellow light stimuli was consistent with a relatively enhanced function of short-wavelength-sensitive cones in the macula. The fundi had signs of retinal degeneration (such as vascular attenuation) and clusters of large, clumped, pigment deposits in the peripheral fundus at the level of the retinal pigment epithelium (clumped pigmentary retinal degeneration). Our report presents an unusual clinical phenotype in humans with loss-of-function mutations in NRL.

Chemical Fluxes in Cellular Steady States Measured by Fluorescence Correlation Spectroscopy

NASA Astrophysics Data System (ADS)

Qian, Hong; Elson, Elliot L.

Genetically, identical cells adopt phenotypes that have different structures, functions, and metabolic properties. In multi-cellular organisms, for example, tissue-specific phenotypes distinguish muscle cells, liver cells, fibroblasts, and blood cells that differ in biochemical functions, geometric forms, and interactions with extracellular environments. Tissue-specific cells usually have different metabolic functions such as synthesis of distinct spectra of secreted proteins, e.g., by liver or pancreatic cells, or of structural proteins, e.g., muscle vs. epithelial cells. But more importantly, a phenotype should include a dynamic aspect: different phenotypes can have distinctly different dynamic functions such as contraction of muscle cells and locomotion of leukocytes. The phenotypes of differentiated tissue cells are typically stable, but they can respond to changes in external conditions, e.g., as in the hypertrophy of muscle cells in response to extra load [1] or the phenotypic shift of fibroblasts to myofibroblasts as part of the wound healing response [2]. Cells pass through sequences of phenotypes during development and also undergo malignant phenotypic transformations as occur in cancer and heart disease.

Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction: An empirical test of the predictive adaptive response hypothesis.

PubMed

Workman, Megan; Baker, Jack; Lancaster, Jane B; Mermier, Christine; Alcock, Joe

2016-07-01

Aiming to test the evolutionary significance of relationships linking prenatal growth conditions to adult phenotypes, this study examined whether birth size predicts energetic savings during fasting. We specifically tested a Predictive Adaptive Response (PAR) model that predicts greater energetic saving among adults who were born small. Data were collected from a convenience sample of young adults living in Albuquerque, NM (n = 34). Indirect calorimetry quantified changes in resting energy expenditure (REE) and active muscular efficiency that occurred in response to a 29-h fast. Multiple regression analyses linked birth weight to baseline and postfast metabolic values while controlling for appropriate confounders (e.g., sex, body mass). Birth weight did not moderate the relationship between body size and energy expenditure, nor did it predict the magnitude change in REE or muscular efficiency observed from baseline to after fasting. Alternative indicators of birth size were also examined (e.g., low v. normal birth weight, comparison of tertiles), with no effects found. However, baseline muscular efficiency improved by 1.1% per 725 g (S.D.) increase in birth weight (P = 0.037). Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

PubMed

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.

Ecological Impacts of Reverse Speciation in Threespine Stickleback.

PubMed

Rudman, Seth M; Schluter, Dolph

2016-02-22

Young species are highly prone to extinction via increased gene flow after human-caused environmental changes. This mechanism of biodiversity loss, often termed reverse speciation or introgressive extinction, is of exceptional interest because the parent species are typically highly differentiated ecologically. Reverse speciation events are potentially powerful case studies for the role of evolution in driving ecological changes, as the phenotypic shifts associated with introgressive extinction can be large and they occur over particularly short timescales. Furthermore, reverse speciation can lead to novel phenotypes, which may in turn produce novel ecological effects. Here we investigate the ecological shift associated with reverse speciation in threespine stickleback fish using a field study and a replicated experiment. We find that an instance of introgressive extinction had cascading ecological consequences that altered the abundance of both aquatic prey and the pupating aquatic insects that emerged into the terrestrial ecosystem. The community and ecosystem impacts of reverse speciation were novel, and yet they were also predictable based on ecological and morphological considerations. The study suggests that knowledge about the community ecology and changes in functional morphology of a dominant species may lead to some predictive power for the ecological effects of evolutionary change. Moreover, the rapid nature and resultant ecological impacts associated with reverse speciation demonstrates the interplay between biodiversity, evolutionary change, and ecosystem function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rapid functional analysis of computationally complex rare human IRF6 gene variants using a novel zebrafish model.

PubMed

Li, Edward B; Truong, Dawn; Hallett, Shawn A; Mukherjee, Kusumika; Schutte, Brian C; Liao, Eric C

2017-09-01

Large-scale sequencing efforts have captured a rapidly growing catalogue of genetic variations. However, the accurate establishment of gene variant pathogenicity remains a central challenge in translating personal genomics information to clinical decisions. Interferon Regulatory Factor 6 (IRF6) gene variants are significant genetic contributors to orofacial clefts. Although approximately three hundred IRF6 gene variants have been documented, their effects on protein functions remain difficult to interpret. Here, we demonstrate the protein functions of human IRF6 missense gene variants could be rapidly assessed in detail by their abilities to rescue the irf6 -/- phenotype in zebrafish through variant mRNA microinjections at the one-cell stage. The results revealed many missense variants previously predicted by traditional statistical and computational tools to be loss-of-function and pathogenic retained partial or full protein function and rescued the zebrafish irf6 -/- periderm rupture phenotype. Through mRNA dosage titration and analysis of the Exome Aggregation Consortium (ExAC) database, IRF6 missense variants were grouped by their abilities to rescue at various dosages into three functional categories: wild type function, reduced function, and complete loss-of-function. This sensitive and specific biological assay was able to address the nuanced functional significances of IRF6 missense gene variants and overcome many limitations faced by current statistical and computational tools in assigning variant protein function and pathogenicity. Furthermore, it unlocked the possibility for characterizing yet undiscovered human IRF6 missense gene variants from orofacial cleft patients, and illustrated a generalizable functional genomics paradigm in personalized medicine.

The role of physiological traits in assortment among and within fish shoals

PubMed Central

Marras, Stefano

2017-01-01

Individuals of gregarious species often group with conspecifics to which they are phenotypically similar. This among-group assortment has been studied for body size, sex and relatedness. However, the role of physiological traits has been largely overlooked. Here, we discuss mechanisms by which physiological traits—particularly those related to metabolism and locomotor performance—may result in phenotypic assortment not only among but also within animal groups. At the among-group level, varying combinations of passive assortment, active assortment, phenotypic plasticity and selective mortality may generate phenotypic differences among groups. Even within groups, however, individual variation in energy requirements, aerobic and anaerobic capacity, neurological lateralization and tolerance to environmental stressors are likely to produce differences in the spatial location of individuals or associations between group-mates with specific physiological phenotypes. Owing to the greater availability of empirical research, we focus on groups of fishes (i.e. shoals and schools). Increased knowledge of physiological mechanisms influencing among- and within-group assortment will enhance our understanding of fundamental concepts regarding optimal group size, predator avoidance, group cohesion, information transfer, life-history strategies and the evolutionary effects of group membership. In a broader perspective, predicting animal responses to environmental change will be impossible without a comprehensive understanding of the physiological basis of the formation and functioning of animal social groups. This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’. PMID:28673911

Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.

PubMed

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations.

Tumor Evolution in Space: The Effects of Competition Colonization Tradeoffs on Tumor Invasion Dynamics

PubMed Central

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations. PMID:23508890

Identification of cancer-cytotoxic modulators of PDE3A by predictive chemogenomics | Office of Cancer Genomics

Cancer.gov

High cancer death rates indicate the need for new anticancer therapeutic agents. Approaches to discovering new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds through phenotypic compound library screening and target deconvolution by predictive chemogenomics.

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

PubMed Central

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

NDST1 missense mutations in autosomal recessive intellectual disability.

PubMed

Reuter, Miriam S; Musante, Luciana; Hu, Hao; Diederich, Stefan; Sticht, Heinrich; Ekici, Arif B; Uebe, Steffen; Wienker, Thomas F; Bartsch, Oliver; Zechner, Ulrich; Oppitz, Cornelia; Keleman, Krystyna; Jamra, Rami Abou; Najmabadi, Hossein; Schweiger, Susann; Reis, André; Kahrizi, Kimia

2014-11-01

NDST1 was recently proposed as a candidate gene for autosomal recessive intellectual disability in two families. It encodes a bifunctional GlcNAc N-deacetylase/N-sulfotransferase with important functions in heparan sulfate biosynthesis. In mice, Ndst1 is crucial for embryonic development and homozygous null mutations are perinatally lethal. We now report on two additional unrelated families with homozygous missense NDST1 mutations. All mutations described to date predict the substitution of conserved amino acids in the sulfotransferase domain, and mutation modeling predicts drastic alterations in the local protein conformation. Comparing the four families, we noticed significant overlap in the clinical features, including both demonstrated and apparent intellectual disability, muscular hypotonia, epilepsy, and postnatal growth deficiency. Furthermore, in Drosophila, knockdown of sulfateless, the NDST ortholog, impairs long-term memory, highlighting its function in cognition. Our data confirm NDST1 mutations as a cause of autosomal recessive intellectual disability with a distinctive phenotype, and support an important function of NDST1 in human development. © 2014 Wiley Periodicals, Inc.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

PubMed Central

Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

2015-01-01

The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

The alignment between phenotypic plasticity, the major axis of genetic variation and the response to selection.

PubMed

Lind, Martin I; Yarlett, Kylie; Reger, Julia; Carter, Mauricio J; Beckerman, Andrew P

2015-10-07

Phenotypic plasticity is the ability of a genotype to produce more than one phenotype in order to match the environment. Recent theory proposes that the major axis of genetic variation in a phenotypically plastic population can align with the direction of selection. Therefore, theory predicts that plasticity directly aids adaptation by increasing genetic variation in the direction favoured by selection and reflected in plasticity. We evaluated this theory in the freshwater crustacean Daphnia pulex, facing predation risk from two contrasting size-selective predators. We estimated plasticity in several life-history traits, the G matrix of these traits, the selection gradients on reproduction and survival, and the predicted responses to selection. Using these data, we tested whether the genetic lines of least resistance and the predicted response to selection aligned with plasticity. We found predator environment-specific G matrices, but shared genetic architecture across environments resulted in more constraint in the G matrix than in the plasticity of the traits, sometimes preventing alignment of the two. However, as the importance of survival selection increased, the difference between environments in their predicted response to selection increased and resulted in closer alignment between the plasticity and the predicted selection response. Therefore, plasticity may indeed aid adaptation to new environments. © 2015 The Authors.

Mechanobiological simulations of peri-acetabular bone ingrowth: a comparative analysis of cell-phenotype specific and phenomenological algorithms.

PubMed

Mukherjee, Kaushik; Gupta, Sanjay

2017-03-01

Several mechanobiology algorithms have been employed to simulate bone ingrowth around porous coated implants. However, there is a scarcity of quantitative comparison between the efficacies of commonly used mechanoregulatory algorithms. The objectives of this study are: (1) to predict peri-acetabular bone ingrowth using cell-phenotype specific algorithm and to compare these predictions with those obtained using phenomenological algorithm and (2) to investigate the influences of cellular parameters on bone ingrowth. The variation in host bone material property and interfacial micromotion of the implanted pelvis were mapped onto the microscale model of implant-bone interface. An overall variation of 17-88 % in peri-acetabular bone ingrowth was observed. Despite differences in predicted tissue differentiation patterns during the initial period, both the algorithms predicted similar spatial distribution of neo-tissue layer, after attainment of equilibrium. Results indicated that phenomenological algorithm, being computationally faster than the cell-phenotype specific algorithm, might be used to predict peri-prosthetic bone ingrowth. The cell-phenotype specific algorithm, however, was found to be useful in numerically investigating the influence of alterations in cellular activities on bone ingrowth, owing to biologically related factors. Amongst the host of cellular activities, matrix production rate of bone tissue was found to have predominant influence on peri-acetabular bone ingrowth.

A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence.

PubMed

Hill, W D; Marioni, R E; Maghzian, O; Ritchie, S J; Hagenaars, S P; McIntosh, A M; Gale, C R; Davies, G; Deary, I J

2018-01-11

Intelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including a wide range of physical, and mental health variables. Education is strongly genetically correlated with intelligence (r g  = 0.70). We used these findings as foundations for our use of a novel approach-multi-trait analysis of genome-wide association studies (MTAG; Turley et al. 2017)-to combine two large genome-wide association studies (GWASs) of education and intelligence, increasing statistical power and resulting in the largest GWAS of intelligence yet reported. Our study had four goals: first, to facilitate the discovery of new genetic loci associated with intelligence; second, to add to our understanding of the biology of intelligence differences; third, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predicts phenotypic intelligence in an independent sample. By combining datasets using MTAG, our functional sample size increased from 199,242 participants to 248,482. We found 187 independent loci associated with intelligence, implicating 538 genes, using both SNP-based and gene-based GWAS. We found evidence that neurogenesis and myelination-as well as genes expressed in the synapse, and those involved in the regulation of the nervous system-may explain some of the biological differences in intelligence. The results of our combined analysis demonstrated the same pattern of genetic correlations as those from previous GWASs of intelligence, providing support for the meta-analysis of these genetically-related phenotypes.

Electromobility Shift Assay Reveals Evidence in Favor of Allele-Specific Binding of RUNX1 to the 5' Hypersensitive Site 4-Locus Control Region.

PubMed

Dehghani, Hossein; Ghobakhloo, Sepideh; Neishabury, Maryam

2016-08-01

In our previous studies on the Iranian β-thalassemia (β-thal) patients, we identified an association between the severity of the β-thal phenotype and the polymorphic palindromic site at the 5' hypersensitive site 4-locus control region (5'HS4-LCR) of the β-globin gene cluster. Furthermore, a linkage disequilibrium was observed between this region and XmnI-HBG2 in the patient population. Based on this data, it was suggested that the well-recognized phenotype-ameliorating role assigned to positive XmnI could be associated with its linked elements in the LCR. To investigate the functional significance of polymorphisms at the 5'HS4-LCR, we studied its influence on binding of transcription factors. Web-based predictions of transcription factor binding revealed a binding site for runt-related transcription factor 1 (RUNX1), when the allele at the center of the palindrome (TGGGG(A/G)CCCCA) was A but not when it was G. Furthermore, electromobility shift assay (EMSA) presented evidence in support of allele-specific binding of RUNX1 to 5'HS4. Considering that RUNX1 is a well-known regulator of hematopoiesis, these preliminary data suggest the importance of further studies to confirm this interaction and consequently investigate its functional and phenotypical relevance. These studies could help us to understand the molecular mechanism behind the phenotype modifying role of the 5'HS4-LCR polymorphic palindromic region (rs16912979), which has been observed in previous studies.

Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence.

PubMed

Barczak, Amy K; Avraham, Roi; Singh, Shantanu; Luo, Samantha S; Zhang, Wei Ran; Bray, Mark-Anthony; Hinman, Amelia E; Thompson, Matthew; Nietupski, Raymond M; Golas, Aaron; Montgomery, Paul; Fitzgerald, Michael; Smith, Roger S; White, Dylan W; Tischler, Anna D; Carpenter, Anne E; Hung, Deborah T

2017-05-01

A key to the pathogenic success of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the capacity to survive within host macrophages. Although several factors required for this survival have been identified, a comprehensive knowledge of such factors and how they work together to manipulate the host environment to benefit bacterial survival are not well understood. To systematically identify Mtb factors required for intracellular growth, we screened an arrayed, non-redundant Mtb transposon mutant library by high-content imaging to characterize the mutant-macrophage interaction. Based on a combination of imaging features, we identified mutants impaired for intracellular survival. We then characterized the phenotype of infection with each mutant by profiling the induced macrophage cytokine response. Taking a systems-level approach to understanding the biology of identified mutants, we performed a multiparametric analysis combining pathogen and host phenotypes to predict functional relationships between mutants based on clustering. Strikingly, mutants defective in two well-known virulence factors, the ESX-1 protein secretion system and the virulence lipid phthiocerol dimycocerosate (PDIM), clustered together. Building upon the shared phenotype of loss of the macrophage type I interferon (IFN) response to infection, we found that PDIM production and export are required for coordinated secretion of ESX-1-substrates, for phagosomal permeabilization, and for downstream induction of the type I IFN response. Multiparametric clustering also identified two novel genes that are required for PDIM production and induction of the type I IFN response. Thus, multiparametric analysis combining host and pathogen infection phenotypes can be used to identify novel functional relationships between genes that play a role in infection.

Functional integration of skeletal traits: an intraskeletal assessment of bone size, mineralization, and volume covariance.

PubMed

Schlecht, Stephen H; Jepsen, Karl J

2013-09-01

Understanding the functional integration of skeletal traits and how they naturally vary within and across populations will benefit assessments of functional adaptation directed towards interpreting bone stiffness in contemporary and past humans. Moreover, investigating how these traits intraskeletally vary will guide us closer towards predicting fragility from a single skeletal site. Using an osteological collection of 115 young adult male and female African-Americans, we assessed the functional relationship between bone robustness (i.e. total area/length), cortical tissue mineral density (Ct.TMD), and cortical area (Ct.Ar) for the upper and lower limbs. All long bones demonstrated significant trait covariance (p < 0.005) independent of body size, with slender bones having 25-50% less Ct.Ar and 5-8% higher Ct.TMD compared to robust bones. Robustness statistically explained 10.2-28% of Ct.TMD and 26.6-64.6% of Ct.Ar within male and female skeletal elements. This covariance is systemic throughout the skeleton, with either the slender or robust phenotype consistently represented within all long bones for each individual. These findings suggest that each person attains a unique trait set by adulthood that is both predictable by robustness and partially independent of environmental influences. The variation in these functionally integrated traits allows for the maximization of tissue stiffness and minimization of mass so that regardless of which phenotype is present, a given bone is reasonably stiff and strong, and sufficiently adapted to perform routine, habitual loading activities. Covariation intrinsic to functional adaptation suggests that whole bone stiffness depends upon particular sets of traits acquired during growth, presumably through differing levels of cellular activity, resulting in differing tissue morphology and composition. The outcomes of this intraskeletal examination of robustness and its correlates may have significant value in our progression towards improved clinical assessments of bone strength and fragility. Copyright © 2013 Elsevier Inc. All rights reserved.

PREDICT-CP: study protocol of implementation of comprehensive surveillance to predict outcomes for school-aged children with cerebral palsy

PubMed Central

Boyd, Roslyn N; Davies, Peter SW; Ziviani, Jenny; Trost, Stewart; Barber, Lee; Ware, Robert; Rose, Stephen; Whittingham, Koa; Bell, Kristie; Carty, Christopher; Obst, Steven; Benfer, Katherine; Reedman, Sarah; Edwards, Priya; Kentish, Megan; Copeland, Lisa; Weir, Kelly; Davenport, Camilla; Brooks, Denise; Coulthard, Alan; Pelekanos, Rebecca; Guzzetta, Andrea; Fiori, Simona; Wynter, Meredith; Finn, Christine; Burgess, Andrea; Morris, Kym; Walsh, John; Lloyd, Owen; Whitty, Jennifer A; Scuffham, Paul A

2017-01-01

Objectives Cerebral palsy (CP) remains the world’s most common childhood physical disability with total annual costs of care and lost well-being of $A3.87b. The PREDICT-CP (NHMRC 1077257 Partnership Project: Comprehensive surveillance to PREDICT outcomes for school age children with CP) study will investigate the influence of brain structure, body composition, dietary intake, oropharyngeal function, habitual physical activity, musculoskeletal development (hip status, bone health) and muscle performance on motor attainment, cognition, executive function, communication, participation, quality of life and related health resource use costs. The PREDICT-CP cohort provides further follow-up at 8–12 years of two overlapping preschool-age cohorts examined from 1.5 to 5 years (NHMRC 465128 motor and brain development; NHMRC 569605 growth, nutrition and physical activity). Methods and analyses This population-based cohort study undertakes state-wide surveillance of 245 children with CP born in Queensland (birth years 2006–2009). Children will be classified for Gross Motor Function Classification System; Manual Ability Classification System, Communication Function Classification System and Eating and Drinking Ability Classification System. Outcomes include gross motor function, musculoskeletal development (hip displacement, spasticity, muscle contracture), upper limb function, communication difficulties, oropharyngeal dysphagia, dietary intake and body composition, participation, parent-reported and child-reported quality of life and medical and allied health resource use. These detailed phenotypical data will be compared with brain macrostructure and microstructure using 3 Tesla MRI (3T MRI). Relationships between brain lesion severity and outcomes will be analysed using multilevel mixed-effects models. Ethics and dissemination The PREDICT-CP protocol is a prospectively registered and ethically accepted study protocol. The study combines data at 1.5–5 then 8–12 years of direct clinical assessment to enable prediction of outcomes and healthcare needs essential for tailoring interventions (eg, rehabilitation, orthopaedic surgery and nutritional supplements) and the projected healthcare utilisation. Trial registration number ACTRN: 12616001488493 PMID:28706091

Prospects for Genomic Selection in Cassava Breeding.

PubMed

Wolfe, Marnin D; Del Carpio, Dunia Pino; Alabi, Olumide; Ezenwaka, Lydia C; Ikeogu, Ugochukwu N; Kayondo, Ismail S; Lozano, Roberto; Okeke, Uche G; Ozimati, Alfred A; Williams, Esuma; Egesi, Chiedozie; Kawuki, Robert S; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

2017-11-01

Cassava ( Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden. Copyright © 2017 Crop Science Society of America.

CYBRD1 as a modifier gene that modulates iron phenotype in HFE p.C282Y homozygous patients.

PubMed

Pelucchi, Sara; Mariani, Raffaella; Calza, Stefano; Fracanzani, Anna Ludovica; Modignani, Giulia Litta; Bertola, Francesca; Busti, Fabiana; Trombini, Paola; Fraquelli, Mirella; Forni, Gian Luca; Girelli, Domenico; Fargion, Silvia; Specchia, Claudia; Piperno, Alberto

2012-12-01

Most patients with hereditary hemochromatosis in the Caucasian population are homozygous for the p.C282Y mutation in the HFE gene. The penetrance and expression of hereditary hemochromatosis differ largely among cases of homozygous p.C282Y. Genetic factors might be involved in addition to environmental factors. In the present study, we analyzed 50 candidate genes involved in iron metabolism and evaluated the association between 214 single nucleotide polymorphisms in these genes and three phenotypic outcomes of iron overload (serum ferritin, iron removed and transferrin saturation) in a large group of 296 p.C282Y homozygous Italians. Polymorphisms were tested for genetic association with each single outcome using linear regression models adjusted for age, sex and alcohol consumption. We found a series of 17 genetic variants located in different genes with possible additive effects on the studied outcomes. In order to evaluate whether the selected polymorphisms could provide a predictive signature for adverse phenotype, we re-evaluated data by dividing patients in two extreme phenotype classes based on the three phenotypic outcomes. We found that only a small improvement in prediction could be achieved by adding genetic information to clinical data. Among the selected polymorphisms, a significant association was observed between rs3806562, located in the 5'UTR of CYBRD1, and transferrin saturation. This variant belongs to the same haplotype block that contains the CYBRD1 polymorphism rs884409, found to be associated with serum ferritin in another population of p.C282Y homozygotes, and able to modulate promoter activity. A luciferase assay indicated that rs3806562 does not have a significant functional role, suggesting that it is a genetic marker linked to the putative genetic modifier rs884409. While our results support the hypothesis that polymorphisms in genes regulating iron metabolism may modulate penetrance of HFE-hereditary hemochromatosis, with emphasis on CYBRD1, they strengthen the notion that none of these polymorphisms alone is a major modifier of the phenotype of hereditary hemochromatosis.

From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer.

PubMed

Weimann, Aaron; Mooren, Kyra; Frank, Jeremy; Pope, Phillip B; Bremges, Andreas; McHardy, Alice C

2016-01-01

The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel Clostridiales species based on draft genomes recovered from commercial biogas reactors. Traitar is available at https://github.com/hzi-bifo/traitar. IMPORTANCE Bacteria are ubiquitous in our ecosystem and have a major impact on human health, e.g., by supporting digestion in the human gut. Bacterial communities can also aid in biotechnological processes such as wastewater treatment or decontamination of polluted soils. Diverse bacteria contribute with their unique capabilities to the functioning of such ecosystems, but lab experiments to investigate those capabilities are labor-intensive. Major advances in sequencing techniques open up the opportunity to study bacteria by their genome sequences. For this purpose, we have developed Traitar, software that predicts traits of bacteria on the basis of their genomes. It is applicable to studies with tens or hundreds of bacterial genomes. Traitar may help researchers in microbiology to pinpoint the traits of interest, reducing the amount of wet lab work required.

CYBRD1 as a modifier gene that modulates iron phenotype in HFE p.C282Y homozygous patients

PubMed Central

Pelucchi, Sara; Mariani, Raffaella; Calza, Stefano; Fracanzani, Anna Ludovica; Modignani, Giulia Litta; Bertola, Francesca; Busti, Fabiana; Trombini, Paola; Fraquelli, Mirella; Forni, Gian Luca; Girelli, Domenico; Fargion, Silvia; Specchia, Claudia; Piperno, Alberto

2012-01-01

Background Most patients with hereditary hemochromatosis in the Caucasian population are homozygous for the p.C282Y mutation in the HFE gene. The penetrance and expression of hereditary hemochromatosis differ largely among cases of homozygous p.C282Y. Genetic factors might be involved in addition to environmental factors. Design and Methods: In the present study, we analyzed 50 candidate genes involved in iron metabolism and evaluated the association between 214 single nucleotide polymorphisms in these genes and three phenotypic outcomes of iron overload (serum ferritin, iron removed and transferrin saturation) in a large group of 296 p.C282Y homozygous Italians. Polymorphisms were tested for genetic association with each single outcome using linear regression models adjusted for age, sex and alcohol consumption. Results We found a series of 17 genetic variants located in different genes with possible additive effects on the studied outcomes. In order to evaluate whether the selected polymorphisms could provide a predictive signature for adverse phenotype, we re-evaluated data by dividing patients in two extreme phenotype classes based on the three phenotypic outcomes. We found that only a small improvement in prediction could be achieved by adding genetic information to clinical data. Among the selected polymorphisms, a significant association was observed between rs3806562, located in the 5'UTR of CYBRD1, and transferrin saturation. This variant belongs to the same haplotype block that contains the CYBRD1 polymorphism rs884409, found to be associated with serum ferritin in another population of p.C282Y homozygotes, and able to modulate promoter activity. A luciferase assay indicated that rs3806562 does not have a significant functional role, suggesting that it is a genetic marker linked to the putative genetic modifier rs884409. Conclusions While our results support the hypothesis that polymorphisms in genes regulating iron metabolism may modulate penetrance of HFE-hereditary hemochromatosis, with emphasis on CYBRD1, they strengthen the notion that none of these polymorphisms alone is a major modifier of the phenotype of hereditary hemochromatosis. PMID:22773607

Electronic health record analysis via deep poisson factor models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

PubMed Central

Lomnitz, Jason G.; Savageau, Michael A.

2016-01-01

Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count, and a negative channel that decreases the count. This example shows the power of these new automated methods to rapidly identify behaviors of interest and efficiently predict parameter values for their realization. These tools may be applied to understand complex natural circuitry and to aid in the rational design of synthetic circuits. PMID:27462346

Tau, amyloid, and cascading network failure across the Alzheimer's disease spectrum.

PubMed

Jones, David T; Graff-Radford, Jonathan; Lowe, Val J; Wiste, Heather J; Gunter, Jeffrey L; Senjem, Matthew L; Botha, Hugo; Kantarci, Kejal; Boeve, Bradley F; Knopman, David S; Petersen, Ronald C; Jack, Clifford R

2017-12-01

Functionally related brain regions are selectively vulnerable to Alzheimer's disease pathophysiology. However, molecular markers of this pathophysiology (i.e., beta-amyloid and tau aggregates) have discrepant spatial and temporal patterns of progression within these selectively vulnerable brain regions. Existing reductionist pathophysiologic models cannot account for these large-scale spatiotemporal inconsistencies. Within the framework of the recently proposed cascading network failure model of Alzheimer's disease, however, these large-scale patterns are to be expected. This model postulates the following: 1) a tau-associated, circumscribed network disruption occurs in brain regions specific to a given phenotype in clinically normal individuals; 2) this disruption can trigger phenotype independent, stereotypic, and amyloid-associated compensatory brain network changes indexed by changes in the default mode network; 3) amyloid deposition marks a saturation of functional compensation and portends an acceleration of the inciting phenotype specific, and tau-associated, network failure. With the advent of in vivo molecular imaging of tau pathology, combined with amyloid and functional network imaging, it is now possible to investigate the relationship between functional brain networks, tau, and amyloid across the disease spectrum within these selectively vulnerable brain regions. In a large cohort (n = 218) spanning the Alzheimer's disease spectrum from young, amyloid negative, cognitively normal subjects to Alzheimer's disease dementia, we found several distinct spatial patterns of tau deposition, including 'Braak-like' and 'non-Braak-like', across functionally related brain regions. Rather than arising focally and spreading sequentially, elevated tau signal seems to occur system-wide based on inferences made from multiple cross-sectional analyses we conducted looking at regional patterns of tau signal. Younger age-of-disease-onset was associated with 'non-Braak-like' patterns of tau, suggesting an association with atypical clinical phenotypes. As predicted by the cascading network failure model of Alzheimer's disease, we found that amyloid is a partial mediator of the relationship between functional network failure and tau deposition in functionally connected brain regions. This study implicates large-scale brain networks in the pathophysiology of tau deposition and offers support to models incorporating large-scale network physiology into disease models linking tau and amyloid, such as the cascading network failure model of Alzheimer's disease. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The common occurrence of epistasis in the determination of human pigmentation and its impact on DNA-based pigmentation phenotype prediction.

PubMed

Pośpiech, Ewelina; Wojas-Pelc, Anna; Walsh, Susan; Liu, Fan; Maeda, Hitoshi; Ishikawa, Takaki; Skowron, Małgorzata; Kayser, Manfred; Branicki, Wojciech

2014-07-01

The role of epistatic effects in the determination of complex traits is often underlined but its significance in the prediction of pigmentation phenotypes has not been evaluated so far. The prediction of pigmentation from genetic data can be useful in forensic science to describe the physical appearance of an unknown offender, victim, or missing person who cannot be identified via conventional DNA profiling. Available forensic DNA prediction systems enable the reliable prediction of several eye and hair colour categories. However, there is still space for improvement. Here we verified the association of 38 candidate DNA polymorphisms from 13 genes and explored the extent to which interactions between them may be involved in human pigmentation and their impact on forensic DNA prediction in particular. The model-building set included 718 Polish samples and the model-verification set included 307 independent Polish samples and additional 72 samples from Japan. In total, 29 significant SNP-SNP interactions were found with 5 of them showing an effect on phenotype prediction. For predicting green eye colour, interactions between HERC2 rs12913832 and OCA2 rs1800407 as well as TYRP1 rs1408799 raised the prediction accuracy expressed by AUC from 0.667 to 0.697 and increased the prediction sensitivity by >3%. Interaction between MC1R 'R' variants and VDR rs731236 increased the sensitivity for light skin by >1% and by almost 3% for dark skin colour prediction. Interactions between VDR rs1544410 and TYR rs1042602 as well as between MC1R 'R' variants and HERC2 rs12913832 provided an increase in red/non-red hair prediction accuracy from an AUC of 0.902-0.930. Our results thus underline epistasis as a common phenomenon in human pigmentation genetics and demonstrate that considering SNP-SNP interactions in forensic DNA phenotyping has little impact on eye, hair and skin colour prediction. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A rice kinase-protein interaction map.

PubMed

Ding, Xiaodong; Richter, Todd; Chen, Mei; Fujii, Hiroaki; Seo, Young Su; Xie, Mingtang; Zheng, Xianwu; Kanrar, Siddhartha; Stevenson, Rebecca A; Dardick, Christopher; Li, Ying; Jiang, Hao; Zhang, Yan; Yu, Fahong; Bartley, Laura E; Chern, Mawsheng; Bart, Rebecca; Chen, Xiuhua; Zhu, Lihuang; Farmerie, William G; Gribskov, Michael; Zhu, Jian-Kang; Fromm, Michael E; Ronald, Pamela C; Song, Wen-Yuan

2009-03-01

Plants uniquely contain large numbers of protein kinases, and for the vast majority of the 1,429 kinases predicted in the rice (Oryza sativa) genome, little is known of their functions. Genetic approaches often fail to produce observable phenotypes; thus, new strategies are needed to delineate kinase function. We previously developed a cost-effective high-throughput yeast two-hybrid system. Using this system, we have generated a protein interaction map of 116 representative rice kinases and 254 of their interacting proteins. Overall, the resulting interaction map supports a large number of known or predicted kinase-protein interactions from both plants and animals and reveals many new functional insights. Notably, we found a potential widespread role for E3 ubiquitin ligases in pathogen defense signaling mediated by receptor-like kinases, particularly by the kinases that may have evolved from recently expanded kinase subfamilies in rice. We anticipate that the data provided here will serve as a foundation for targeted functional studies in rice and other plants. The application of yeast two-hybrid and TAPtag analyses for large-scale plant protein interaction studies is also discussed.

AlloRep: A Repository of Sequence, Structural and Mutagenesis Data for the LacI/GalR Transcription Regulators.

PubMed

Sousa, Filipa L; Parente, Daniel J; Shis, David L; Hessman, Jacob A; Chazelle, Allen; Bennett, Matthew R; Teichmann, Sarah A; Swint-Kruse, Liskin

2016-02-22

Protein families evolve functional variation by accumulating point mutations at functionally important amino acid positions. Homologs in the LacI/GalR family of transcription regulators have evolved to bind diverse DNA sequences and allosteric regulatory molecules. In addition to playing key roles in bacterial metabolism, these proteins have been widely used as a model family for benchmarking structural and functional prediction algorithms. We have collected manually curated sequence alignments for >3000 sequences, in vivo phenotypic and biochemical data for >5750 LacI/GalR mutational variants, and noncovalent residue contact networks for 65 LacI/GalR homolog structures. Using this rich data resource, we compared the noncovalent residue contact networks of the LacI/GalR subfamilies to design and experimentally validate an allosteric mutant of a synthetic LacI/GalR repressor for use in biotechnology. The AlloRep database (freely available at www.AlloRep.org) is a key resource for future evolutionary studies of LacI/GalR homologs and for benchmarking computational predictions of functional change. Copyright © 2015 Elsevier Ltd. All rights reserved.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Characterization of novel StAR (steroidogenic acute regulatory protein) mutations causing non-classic lipoid adrenal hyperplasia.

PubMed

Flück, Christa E; Pandey, Amit V; Dick, Bernhard; Camats, Núria; Fernández-Cancio, Mónica; Clemente, María; Gussinyé, Miquel; Carrascosa, Antonio; Mullis, Primus E; Audi, Laura

2011-01-01

Steroidogenic acute regulatory protein (StAR) is crucial for transport of cholesterol to mitochondria where biosynthesis of steroids is initiated. Loss of StAR function causes lipoid congenital adrenal hyperplasia (LCAH). StAR gene mutations causing partial loss of function manifest atypical and may be mistaken as familial glucocorticoid deficiency. Only a few mutations have been reported. To report clinical, biochemical, genetic, protein structure and functional data on two novel StAR mutations, and to compare them with published literature. Collaboration between the University Children's Hospital Bern, Switzerland, and the CIBERER, Hospital Vall d'Hebron, Autonomous University, Barcelona, Spain. Two subjects of a non-consanguineous Caucasian family were studied. The 46,XX phenotypic normal female was diagnosed with adrenal insufficiency at the age of 10 months, had normal pubertal development and still has no signs of hypergonodatropic hypogonadism at 32 years of age. Her 46,XY brother was born with normal male external genitalia and was diagnosed with adrenal insufficiency at 14 months. Puberty was normal and no signs of hypergonadotropic hypogonadism are present at 29 years of age. StAR gene analysis revealed two novel compound heterozygote mutations T44HfsX3 and G221S. T44HfsX3 is a loss-of-function StAR mutation. G221S retains partial activity (∼30%) and is therefore responsible for a milder, non-classic phenotype. G221S is located in the cholesterol binding pocket and seems to alter binding/release of cholesterol. StAR mutations located in the cholesterol binding pocket (V187M, R188C, R192C, G221D/S) seem to cause non-classic lipoid CAH. Accuracy of genotype-phenotype prediction by in vitro testing may vary with the assays employed.

AtLAZY1 is a signaling component required for gravitropism of the Arabidopsis thaliana inflorescence.

PubMed

Yoshihara, Takeshi; Spalding, Edgar P; Iino, Moritoshi

2013-04-01

The present study identified a family of six A. thaliana genes that share five limited regions of sequence similarity with LAZY1, a gene in Oryza sativa (rice) shown to participate in the early gravity signaling for shoot gravitropism. A T-DNA insertion into the Arabidopsis gene (At5g14090) most similar to LAZY1 increased the inflorescence branch angle to 81° from the wild type value of 42°. RNA interference lines and molecular rescue experiments confirmed the linkage between the branch-angle phenotype and the gene consequently named AtLAZY1. Time-resolved gravitropism measurements of atlazy1 hypocotyls and primary inflorescence stems showed a significantly reduced bending rate during the first hour of response. The subcellular localization of AtLAZY1 protein was investigated to determine if the nuclear localization predicted from the gene sequence was observable and important to its function in shoot gravity responses. AtLAZY1 fused to green fluorescent protein largely rescued the branch-angle phenotype of atlazy1, and was observed by confocal microscopy at the cell periphery and within the nucleus. Mutation of the nuclear localization signal prevented detectable levels of AtLAZY1 in the nucleus without affecting the ability of the gene to rescue the atlazy1 branch-angle phenotype. These results indicate that AtLAZY1 functions in gravity signaling during shoot gravitropism, being a functional ortholog of rice LAZY1. The nuclear pool of the protein appears to be unnecessary for this function, which instead relies on a pool that appears to reside at the cell periphery. © 2013 The Authors The Plant Journal © 2013 Blackwell Publishing Ltd.

Proteome-wide search for functional motifs altered in tumors: Prediction of nuclear export signals inactivated by cancer-related mutations

PubMed Central

Prieto, Gorka; Fullaondo, Asier; Rodríguez, Jose A.

2016-01-01

Large-scale sequencing projects are uncovering a growing number of missense mutations in human tumors. Understanding the phenotypic consequences of these alterations represents a formidable challenge. In silico prediction of functionally relevant amino acid motifs disrupted by cancer mutations could provide insight into the potential impact of a mutation, and guide functional tests. We have previously described Wregex, a tool for the identification of potential functional motifs, such as nuclear export signals (NESs), in proteins. Here, we present an improved version that allows motif prediction to be combined with data from large repositories, such as the Catalogue of Somatic Mutations in Cancer (COSMIC), and to be applied to a whole proteome scale. As an example, we have searched the human proteome for candidate NES motifs that could be altered by cancer-related mutations included in the COSMIC database. A subset of the candidate NESs identified was experimentally tested using an in vivo nuclear export assay. A significant proportion of the selected motifs exhibited nuclear export activity, which was abrogated by the COSMIC mutations. In addition, our search identified a cancer mutation that inactivates the NES of the human deubiquitinase USP21, and leads to the aberrant accumulation of this protein in the nucleus. PMID:27174732

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution

PubMed Central

Mannakee, Brian K.; Gutenkunst, Ryan N.

2016-01-01

The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces. PMID:27380265

Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

PubMed

Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu

2017-09-01

Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

PubMed

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

Antimicrobial Resistance Prediction in PATRIC and RAST.

PubMed

Davis, James J; Boisvert, Sébastien; Brettin, Thomas; Kenyon, Ronald W; Mao, Chunhong; Olson, Robert; Overbeek, Ross; Santerre, John; Shukla, Maulik; Wattam, Alice R; Will, Rebecca; Xia, Fangfang; Stevens, Rick

2016-06-14

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88-99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71-88%. This set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Computational approaches to identify functional genetic variants in cancer genomes

PubMed Central

Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

2014-01-01

The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change

PubMed Central

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

Phenotypic interactions between tree hosts and invasive forest pathogens in the light of globalization and climate change.

PubMed

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).

Transgressive Hybrids as Hopeful Monsters.

PubMed

Dittrich-Reed, Dylan R; Fitzpatrick, Benjamin M

2013-06-01

The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt's infamous "hopeful monster". Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, "monstrous" phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts "hopeless" monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts "hopeful" monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant "hopeful monsters" will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.

Extending the ‘cross-disorder’ relevance of executive functions to dimensional neuropsychiatric traits in youth

PubMed Central

McGrath, Lauren M.; Braaten, Ellen B.; Doty, Nathan D.; Willoughby, Brian L.; Wilson, H. Kent; O’Donnell, Ellen H.; Colvin, Mary K.; Ditmars, Hillary L.; Blais, Jessica E.; Hill, Erin N.; Metzger, Aaron; Perlis, Roy H.; Willcutt, Erik G.; Smoller, Jordan W.; Waldman, Irwin D.; Faraone, Stephen V.; Seidman, Larry J.; Doyle, Alysa E.

2016-01-01

Background Evidence that different neuropsychiatric conditions share genetic liability has increased interest in phenotypes with ‘cross-disorder’ relevance, as they may contribute to revised models of psychopathology. Cognition is a promising construct for study; yet, evidence that the same cognitive functions are impaired across different forms of psychopathology comes primarily from separate studies of individual categorical diagnoses versus controls. Given growing support for dimensional models that cut across traditional diagnostic boundaries, we aimed to determine, within a single cohort, whether performance on measures of executive functions (EFs) predicted dimensions of different psychopathological conditions known to share genetic liability. Methods Data are from 393 participants, ages 8 to 17, consecutively enrolled in the Longitudinal Study of Genetic Influences on Cognition (LOGIC). This project is conducting deep phenotyping and genomic analyses in youth referred for neuropsychiatric evaluation. Using structural equation modeling, we examined whether EFs predicted variation in core dimensions of autism spectrum disorder, bipolar illness and schizophrenia, including social responsiveness, mania/emotion regulation, and positive symptoms of psychosis, respectively. Results We modeled three cognitive factors (working memory, shifting, and executive processing speed) that loaded on a second-order EF factor. The EF factor predicted variation in our three target traits but not in a negative control (somatization). Moreover, this EF factor was primarily associated with the overlapping (rather than unique) variance across the three outcome measures, suggesting it related to a general increase in psychopathology symptoms across those dimensions. Conclusions Findings extend support for the relevance of cognition to neuropsychiatric conditions that share underlying genetic risk. They suggest that higher-order cognition, including EFs, relate to the dimensional spectrum of each of these disorders and not just the clinical diagnoses. Moreover, results have implications for bottom-up models linking genes, cognition, and a general psychopathology liability. PMID:26411927

Mutation in GM2A Leads to a Progressive Chorea-dementia Syndrome

PubMed Central

Salih, Mustafa A.; Seidahmed, Mohammed Z.; El Khashab, Heba Y.; Hamad, Muddathir H. A.; Bosley, Thomas M.; Burn, Sabrina; Myers, Angela; Landsverk, Megan L.; Crotwell, Patricia L.; Bilguvar, Kaya; Mane, Shrikant; Kruer, Michael C.

2015-01-01

Background The etiology of many cases of childhood-onset chorea remains undetermined, although advances in genomics are revealing both new disease-associated genes and variant phenotypes associated with known genes. Methods We report a Saudi family with a neurodegenerative course dominated by progressive chorea and dementia in whom we performed homozygosity mapping and whole exome sequencing. Results We identified a homozygous missense mutation in GM2A within a prominent block of homozygosity. This mutation is predicted to impair protein function. Discussion Although discovered more than two decades ago, to date, only five patients with this rare form of GM2 gangliosidosis have been reported. The phenotype of previously described GM2A patients has been typified by onset in infancy, profound hypotonia and impaired volitional movement, intractable seizures, hyperacusis, and a macular cherry red spot. Our findings expand the phenotypic spectrum of GM2A mutation-positive gangliosidosis to include generalized chorea without macular findings or hyperacusis and highlight how mutations in neurodegenerative disease genes may present in unexpected ways. PMID:26203402

The after-hours circadian mutant has reduced phenotypic plasticity in behaviors at multiple timescales and in sleep homeostasis.

PubMed

Maggi, Silvia; Balzani, Edoardo; Lassi, Glenda; Garcia-Garcia, Celina; Plano, Andrea; Espinoza, Stefano; Mus, Liudmila; Tinarelli, Federico; Nolan, Patrick M; Gainetdinov, Raul R; Balci, Fuat; Nieus, Thierry; Tucci, Valter

2017-12-19

Circadian clock is known to adapt to environmental changes and can significantly influence cognitive and physiological functions. In this work, we report specific behavioral, cognitive, and sleep homeostatic defects in the after hours (Afh) circadian mouse mutant, which is characterized by lengthened circadian period. We found that the circadian timing irregularities in Afh mice resulted in higher interval timing uncertainty and suboptimal decisions due to incapability of processing probabilities. Our phenotypic observations further suggested that Afh mutants failed to exhibit the necessary phenotypic plasticity for adapting to temporal changes at multiple time scales (seconds-to-minutes to circadian). These behavioral effects of Afh mutation were complemented by the specific disruption of the Per/Cry circadian regulatory complex in brain regions that govern food anticipatory behaviors, sleep, and timing. We derive statistical predictions, which indicate that circadian clock and sleep are complementary processes in controlling behavioral/cognitive performance during 24 hrs. The results of this study have pivotal implications for understanding how the circadian clock modulates sleep and behavior.

Lipid-lowering effects of anti-angiopoietin-like 4 antibody recapitulate the lipid phenotype found in angiopoietin-like 4 knockout mice

PubMed Central

Desai, Urvi; Lee, E-Chiang; Chung, Kyu; Gao, Cuihua; Gay, Jason; Key, Billie; Hansen, Gwenn; Machajewski, Dennis; Platt, Kenneth A.; Sands, Arthur T.; Schneider, Matthias; Van Sligtenhorst, Isaac; Suwanichkul, Adisak; Vogel, Peter; Wilganowski, Nat; Wingert, June; Zambrowicz, Brian P.; Landes, Greg; Powell, David R.

2007-01-01

We used gene knockout mice to explore the role of Angiopoietin-like-4 (Angptl4) in lipid metabolism as well as to generate anti-Angptl4 mAbs with pharmacological activity. Angptl4 −/− mice had lower triglyceride (TG) levels resulting both from increased very low-density lipoprotein (VLDL) clearance and decreased VLDL production and had modestly lower cholesterol levels. Also, both Angptl4 −/− suckling mice and adult mice fed a high-fat diet showed reduced viability associated with lipogranulomatous lesions of the intestines and their draining lymphatics and mesenteric lymph nodes. Treating C57BL/6J, ApoE −/−, LDLr −/−, and db/db mice with the anti-Angptl4 mAb 14D12 recapitulated the lipid and histopathologic phenotypes noted in Angptl4 −/− mice. This demonstrates that the knockout phenotype reflects not only the physiologic function of the Angptl4 gene but also predicts the pharmacologic consequences of Angptl4 protein inhibition with a neutralizing antibody in relevant models of human disease. PMID:17609370

Molecular cloning and functional characterization of the sex-determination gene doublesex in the sexually dimorphic broad-horned beetle Gnatocerus cornutus (Coleoptera, Tenebrionidae)

PubMed Central

Gotoh, Hiroki; Ishiguro, Mai; Nishikawa, Hideto; Morita, Shinichi; Okada, Kensuke; Miyatake, Takahisa; Yaginuma, Toshinobu; Niimi, Teruyuki

2016-01-01

Various types of weapon traits found in insect order Coleoptera are known as outstanding examples of sexually selected exaggerated characters. It is known that the sex determination gene doublesex (dsx) plays a significant role in sex-specific expression of weapon traits in various beetles belonging to the superfamily Scarabaeoidea. Although sex-specific weapon traits have evolved independently in various Coleopteran groups, developmental mechanisms of sex-specific expression have not been studied outside of the Scarabaeoidea. In order to test the hypothesis that dsx-dependent sex-specific expression of weapon traits is a general mechanism among the Coleoptera, we have characterized the dsx in the sexually dimorphic broad-horned beetle Gnatocerus cornutus (Tenebrionidea, Tenebirionidae). By using molecular cloning, we identified five splicing variants of Gnatocerus cornutus dsx (Gcdsx), which are predicted to code four different isoforms. We found one male-specific variant (GcDsx-M), two female-specific variants (GcDsx-FL and GcDsx-FS) and two non-sex-specific variants (correspond to a single isoform, GcDsx-C). Knockdown of all Dsx isoforms resulted in intersex phenotype both in male and female. Also, knockdown of all female-specific isoforms transformed females to intersex phenotype, while did not affect male phenotype. Our results clearly illustrate the important function of Gcdsx in determining sex-specific trait expression in both sexes. PMID:27404087

Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle.

PubMed

Yin, T; Pinent, T; Brügemann, K; Simianer, H; König, S

2015-08-01

This study presents an approach combining phenotypes from novel traits, deterministic equations from cattle nutrition, and stochastic simulation techniques from animal breeding to generate test-day methane emissions (MEm) of dairy cows. Data included test-day production traits (milk yield, fat percentage, protein percentage, milk urea nitrogen), conformation traits (wither height, hip width, body condition score), female fertility traits (days open, calving interval, stillbirth), and health traits (clinical mastitis) from 961 first lactation Brown Swiss cows kept on 41 low-input farms in Switzerland. Test-day MEm were predicted based on the traits from the current data set and 2 deterministic prediction equations, resulting in the traits labeled MEm1 and MEm2. Stochastic simulations were used to assign individual concentrate intake in dependency of farm-type specifications (requirement when calculating MEm2). Genetic parameters for MEm1 and MEm2 were estimated using random regression models. Predicted MEm had moderate heritabilities over lactation and ranged from 0.15 to 0.37, with highest heritabilities around DIM 100. Genetic correlations between MEm1 and MEm2 ranged between 0.91 and 0.94. Antagonistic genetic correlations in the range from 0.70 to 0.92 were found for the associations between MEm2 and milk yield. Genetic correlations between MEm with days open and with calving interval increased from 0.10 at the beginning to 0.90 at the end of lactation. Genetic relationships between MEm2 and stillbirth were negative (0 to -0.24) from the beginning to the peak phase of lactation. Positive genetic relationships in the range from 0.02 to 0.49 were found between MEm2 with clinical mastitis. Interpretation of genetic (co)variance components should also consider the limitations when using data generated by prediction equations. Prediction functions only describe that part of MEm which is dependent on the factors and effects included in the function. With high probability, there are more important effects contributing to variations of MEm that are not explained or are independent from these functions. Furthermore, autocorrelations exist between indicator traits and predicted MEm. Nevertheless, this integrative approach, combining information from dairy cattle nutrition with dairy cattle genetics, generated novel traits which are difficult to record on a large scale. The simulated data basis for MEm was used to determine the size of a cow calibration group for genomic selection. A calibration group including 2,581 cows with MEm phenotypes was competitive with conventional breeding strategies. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Nutritional and non-nutritional food components modulate phenotypic variation but not physiological trade-offs in an insect.

PubMed

Pascacio-Villafán, Carlos; Williams, Trevor; Birke, Andrea; Aluja, Martín

2016-07-12

Our understanding of how food modulates animal phenotypes and mediate trade-offs between life-history traits has benefited greatly from the study of combinations of nutritional and non-nutritional food components, such as plant secondary metabolites. We used a fruit fly pest, Anastrepha ludens, to examine phenotypic variation across larval, pupal and adult stages as a function of larval food with varying nutrient balance and content of chlorogenic acid, a secondary metabolite. Larval insects that fed on carbohydrate-biased diets relative to protein exhibited longer larval and pupal developmental periods, were often heavier as pupae and resisted desiccation and starvation for longer periods in the adult stage than insects fed on highly protein-biased diets. Except for a potential conflict between pupal development time and adult desiccation and starvation resistance, we did not detect physiological trade-offs mediated by the nutritional balance in larval food. Chlorogenic acid affected A. ludens development in a concentration and nutrient-dependent manner. Nutrients and host plant secondary metabolites in the larval diet induced changes in A. ludens phenotype and could influence fruit fly ecological interactions. We provide a unique experimental and modelling approach useful in generating predictive models of life history traits in a variety of organisms.

Nutritional and non-nutritional food components modulate phenotypic variation but not physiological trade-offs in an insect

PubMed Central

Pascacio-Villafán, Carlos; Williams, Trevor; Birke, Andrea; Aluja, Martín

2016-01-01

Our understanding of how food modulates animal phenotypes and mediate trade-offs between life-history traits has benefited greatly from the study of combinations of nutritional and non-nutritional food components, such as plant secondary metabolites. We used a fruit fly pest, Anastrepha ludens, to examine phenotypic variation across larval, pupal and adult stages as a function of larval food with varying nutrient balance and content of chlorogenic acid, a secondary metabolite. Larval insects that fed on carbohydrate-biased diets relative to protein exhibited longer larval and pupal developmental periods, were often heavier as pupae and resisted desiccation and starvation for longer periods in the adult stage than insects fed on highly protein-biased diets. Except for a potential conflict between pupal development time and adult desiccation and starvation resistance, we did not detect physiological trade-offs mediated by the nutritional balance in larval food. Chlorogenic acid affected A. ludens development in a concentration and nutrient-dependent manner. Nutrients and host plant secondary metabolites in the larval diet induced changes in A. ludens phenotype and could influence fruit fly ecological interactions. We provide a unique experimental and modelling approach useful in generating predictive models of life history traits in a variety of organisms. PMID:27406923

A novel two-nucleotide deletion in the ATP7A gene associated with delayed infantile onset of Menkes disease.

PubMed

Wada, Takahito; Haddad, Marie Reine; Yi, Ling; Murakami, Tomomi; Sasaki, Akiko; Shimbo, Hiroko; Kodama, Hiroko; Osaka, Hitoshi; Kaler, Stephen G

2014-04-01

Determining the relationship between clinical phenotype and genotype in genetic diseases is important in clinical practice. In general, frameshift mutations are expected to produce premature termination codons, leading to production of mutant transcripts destined for degradation by nonsense-mediated decay. In X-linked recessive diseases, male patients with frameshift mutations typically have a severe or even lethal phenotype. We report a case of a 17-month-old boy with Menkes disease (NIM #309400), an X-linked recessive copper metabolism disorder caused by mutations in the ATP7A copper transporter gene. He exhibited an unexpectedly late onset and experienced milder symptoms. His genomic DNA showed a de novo two-nucleotide deletion in exon 4 of ATP7A, predicting a translational frameshift and premature stop codon, and a classic severe phenotype. Characterization of his ATP7A mRNA showed no abnormal splicing. We speculate that translation reinitiation could occur downstream to the premature termination codon and produce a partially functional ATP7A protein. Study of the child's fibroblasts found no evidence of translation reinitiation; however, the possibility remains that this phenomenon occurred in neural tissues and influenced the clinical phenotype. Copyright © 2014 Elsevier Inc. All rights reserved.

Loss-of-function mutations in the ethylene receptor ETR1 cause enhanced sensitivity and exaggerated response to ethylene in Arabidopsis.

PubMed

Cancel, Jesse D; Larsen, Paul B

2002-08-01

Ethylene signaling in Arabidopsis begins at a family of five ethylene receptors that regulate activity of a downstream mitogen-activated protein kinase kinase kinase, CTR1. Triple and quadruple loss-of-function ethylene receptor mutants display a constitutive ethylene response phenotype, indicating they function as negative regulators in this pathway. No ethylene-related phenotype has been described for single loss-of-function receptor mutants, although it was reported that etr1 loss-of-function mutants display a growth defect limiting plant size. In actuality, this apparent growth defect results from enhanced responsiveness to ethylene; a phenotype manifested in all tissues tested. The phenotype displayed by etr1 loss-of-function mutants was rescued by treatment with an inhibitor of ethylene perception, indicating that it is ethylene dependent. Identification of an ethylene-dependent phenotype for a loss-of-function receptor mutant gave a unique opportunity for genetic and biochemical analysis of upstream events in ethylene signaling, including demonstration that the dominant ethylene-insensitive phenotype of etr2-1 is partially dependent on ETR1. This work demonstrates that mutational loss of the ethylene receptor ETR1 alters responsiveness to ethylene in Arabidopsis and that enhanced ethylene response in Arabidopsis not only results in increased sensitivity but exaggeration of response.

Loss-of-Function Mutations in the Ethylene Receptor ETR1 Cause Enhanced Sensitivity and Exaggerated Response to Ethylene in Arabidopsis

PubMed Central

Cancel, Jesse D.; Larsen, Paul B.

2002-01-01

Ethylene signaling in Arabidopsis begins at a family of five ethylene receptors that regulate activity of a downstream mitogen-activated protein kinase kinase kinase, CTR1. Triple and quadruple loss-of-function ethylene receptor mutants display a constitutive ethylene response phenotype, indicating they function as negative regulators in this pathway. No ethylene-related phenotype has been described for single loss-of-function receptor mutants, although it was reported that etr1 loss-of-function mutants display a growth defect limiting plant size. In actuality, this apparent growth defect results from enhanced responsiveness to ethylene; a phenotype manifested in all tissues tested. The phenotype displayed by etr1 loss-of-function mutants was rescued by treatment with an inhibitor of ethylene perception, indicating that it is ethylene dependent. Identification of an ethylene-dependent phenotype for a loss-of-function receptor mutant gave a unique opportunity for genetic and biochemical analysis of upstream events in ethylene signaling, including demonstration that the dominant ethylene-insensitive phenotype of etr2-1 is partially dependent on ETR1. This work demonstrates that mutational loss of the ethylene receptor ETR1 alters responsiveness to ethylene in Arabidopsis and that enhanced ethylene response in Arabidopsis not only results in increased sensitivity but exaggeration of response. PMID:12177468

Plasticity in functional traits in the context of climate change: a case study of the subalpine forb Boechera stricta (Brassicaceae).

PubMed

Anderson, Jill T; Gezon, Zachariah J

2015-04-01

Environmental variation often induces shifts in functional traits, yet we know little about whether plasticity will reduce extinction risks under climate change. As climate change proceeds, phenotypic plasticity could enable species with limited dispersal capacity to persist in situ, and migrating populations of other species to establish in new sites at higher elevations or latitudes. Alternatively, climate change could induce maladaptive plasticity, reducing fitness, and potentially stalling adaptation and migration. Here, we quantified plasticity in life history, foliar morphology, and ecophysiology in Boechera stricta (Brassicaceae), a perennial forb native to the Rocky Mountains. In this region, warming winters are reducing snowpack and warming springs are advancing the timing of snow melt. We hypothesized that traits that were historically advantageous in hot and dry, low-elevation locations will be favored at higher elevation sites due to climate change. To test this hypothesis, we quantified trait variation in natural populations across an elevational gradient. We then estimated plasticity and genetic variation in common gardens at two elevations. Finally, we tested whether climatic manipulations induce plasticity, with the prediction that plants exposed to early snow removal would resemble individuals from lower elevation populations. In natural populations, foliar morphology and ecophysiology varied with elevation in the predicted directions. In the common gardens, trait plasticity was generally concordant with phenotypic clines from the natural populations. Experimental snow removal advanced flowering phenology by 7 days, which is similar in magnitude to flowering time shifts over 2-3 decades of climate change. Therefore, snow manipulations in this system can be used to predict eco-evolutionary responses to global change. Snow removal also altered foliar morphology, but in unexpected ways. Extensive plasticity could buffer against immediate fitness declines due to changing climates. © 2014 John Wiley & Sons Ltd.

Extent of QTL Reuse During Repeated Phenotypic Divergence of Sympatric Threespine Stickleback.

PubMed

Conte, Gina L; Arnegard, Matthew E; Best, Jacob; Chan, Yingguang Frank; Jones, Felicity C; Kingsley, David M; Schluter, Dolph; Peichel, Catherine L

2015-11-01

How predictable is the genetic basis of phenotypic adaptation? Answering this question begins by estimating the repeatability of adaptation at the genetic level. Here, we provide a comprehensive estimate of the repeatability of the genetic basis of adaptive phenotypic evolution in a natural system. We used quantitative trait locus (QTL) mapping to discover genomic regions controlling a large number of morphological traits that have diverged in parallel between pairs of threespine stickleback (Gasterosteus aculeatus species complex) in Paxton and Priest lakes, British Columbia. We found that nearly half of QTL affected the same traits in the same direction in both species pairs. Another 40% influenced a parallel phenotypic trait in one lake but not the other. The remaining 10% of QTL had phenotypic effects in opposite directions in the two species pairs. Similarity in the proportional contributions of all QTL to parallel trait differences was about 0.4. Surprisingly, QTL reuse was unrelated to phenotypic effect size. Our results indicate that repeated use of the same genomic regions is a pervasive feature of parallel phenotypic adaptation, at least in sticklebacks. Identifying the causes of this pattern would aid prediction of the genetic basis of phenotypic evolution. Copyright © 2015 by the Genetics Society of America.

Adaptation to local ultraviolet radiation conditions among neighbouring Daphnia populations

PubMed Central

Miner, Brooks E.; Kerr, Benjamin

2011-01-01

Understanding the historical processes that generated current patterns of phenotypic diversity in nature is particularly challenging in subdivided populations. Populations often exhibit heritable genetic differences that correlate with environmental variables, but the non-independence among neighbouring populations complicates statistical inference of adaptation. To understand the relative influence of adaptive and non-adaptive processes in generating phenotypes requires joint evaluation of genetic and phenotypic divergence in an integrated and statistically appropriate analysis. We investigated phenotypic divergence, population-genetic structure and potential fitness trade-offs in populations of Daphnia melanica inhabiting neighbouring subalpine ponds of widely differing transparency to ultraviolet radiation (UVR). Using a combination of experimental, population-genetic and statistical techniques, we separated the effects of shared population ancestry and environmental variables in predicting phenotypic divergence among populations. We found that native water transparency significantly predicted divergence in phenotypes among populations even after accounting for significant population structure. This result demonstrates that environmental factors such as UVR can at least partially account for phenotypic divergence. However, a lack of evidence for a hypothesized trade-off between UVR tolerance and growth rates in the absence of UVR prevents us from ruling out the possibility that non-adaptive processes are partially responsible for phenotypic differentiation in this system. PMID:20943691

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

PubMed

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.

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

PubMed Central

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. PMID:26483754

Predictable Phenotypes of Antibiotic Resistance Mutations.

PubMed

Knopp, M; Andersson, D I

2018-05-15

Antibiotic-resistant bacteria represent a major threat to our ability to treat bacterial infections. Two factors that determine the evolutionary success of antibiotic resistance mutations are their impact on resistance level and the fitness cost. Recent studies suggest that resistance mutations commonly show epistatic interactions, which would complicate predictions of their stability in bacterial populations. We analyzed 13 different chromosomal resistance mutations and 10 host strains of Salmonella enterica and Escherichia coli to address two main questions. (i) Are there epistatic interactions between different chromosomal resistance mutations? (ii) How does the strain background and genetic distance influence the effect of chromosomal resistance mutations on resistance and fitness? Our results show that the effects of combined resistance mutations on resistance and fitness are largely predictable and that epistasis remains rare even when up to four mutations were combined. Furthermore, a majority of the mutations, especially target alteration mutations, demonstrate strain-independent phenotypes across different species. This study extends our understanding of epistasis among resistance mutations and shows that interactions between different resistance mutations are often predictable from the characteristics of the individual mutations. IMPORTANCE The spread of antibiotic-resistant bacteria imposes an urgent threat to public health. The ability to forecast the evolutionary success of resistant mutants would help to combat dissemination of antibiotic resistance. Previous studies have shown that the phenotypic effects (fitness and resistance level) of resistance mutations can vary substantially depending on the genetic context in which they occur. We conducted a broad screen using many different resistance mutations and host strains to identify potential epistatic interactions between various types of resistance mutations and to determine the effect of strain background on resistance phenotypes. Combinations of several different mutations showed a large amount of phenotypic predictability, and the majority of the mutations displayed strain-independent phenotypes. However, we also identified a few outliers from these patterns, illustrating that the choice of host organism can be critically important when studying antibiotic resistance mutations. Copyright © 2018 Knopp and Andersson.

Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates.

PubMed

Low, Andrew J; Dong, Winnie; Chan, Dennison; Sing, Tobias; Swanstrom, Ronald; Jensen, Mark; Pillai, Satish; Good, Benjamin; Harrigan, P Richard

2007-09-12

Integrating CCR5 antagonists into clinical practice would benefit from accurate assays of co-receptor usage (CCR5 versus CXCR4) with fast turnaround and low cost. Published HIV V3-loop based predictors of co-receptor usage were compared with actual phenotypic tropism results in a large cohort of antiretroviral naive individuals to determine accuracy on clinical samples and identify areas for improvement. Aligned HIV envelope V3 loop sequences (n = 977), derived by bulk sequencing were analyzed by six methods: the 11/25 rule; a neural network (NN), two support vector machines, and two subtype-B position specific scoring matrices (PSSM). Co-receptor phenotype results (Trofile Co-receptor Phenotype Assay; Monogram Biosciences) were stratified by CXCR4 relative light unit (RLU) readout and CD4 cell count. Co-receptor phenotype was available for 920 clinical samples with V3 genotypes having fewer than seven amino acid mixtures (n = 769 R5; n = 151 X4-capable). Sensitivity and specificity for predicting X4 capacity were evaluated for the 11/25 rule (30% sensitivity/93% specificity), NN (44%/88%), PSSM(sinsi) (34%/96%), PSSM(x4r5) (24%/97%), SVMgenomiac (22%/90%) and SVMgeno2pheno (50%/89%). Quantitative increases in sensitivity could be obtained by optimizing the cut-off for methods with continuous output (PSSM methods), and/or integrating clinical data (CD4%). Sensitivity was directly proportional to strength of X4 signal in the phenotype assay (P < 0.05). Current default implementations of co-receptor prediction algorithms are inadequate for predicting HIV X4 co-receptor usage in clinical samples, particularly those X4 phenotypes with low CXCR4 RLU signals. Significant improvements can be made to genotypic predictors, including training on clinical samples, using additional data to improve predictions and optimizing cutoffs and increasing genotype sensitivity.

Characterizing behavioural ‘characters’: an evolutionary framework

PubMed Central

Araya-Ajoy, Yimen G.; Dingemanse, Niels J.

2014-01-01

Biologists often study phenotypic evolution assuming that phenotypes consist of a set of quasi-independent units that have been shaped by selection to accomplish a particular function. In the evolutionary literature, such quasi-independent functional units are called ‘evolutionary characters’, and a framework based on evolutionary principles has been developed to characterize them. This framework mainly focuses on ‘fixed’ characters, i.e. those that vary exclusively between individuals. In this paper, we introduce multi-level variation and thereby expand the framework to labile characters, focusing on behaviour as a worked example. We first propose a concept of ‘behavioural characters’ based on the original evolutionary character concept. We then detail how integration of variation between individuals (cf. ‘personality’) and within individuals (cf. ‘individual plasticity’) into the framework gives rise to a whole suite of novel testable predictions about the evolutionary character concept. We further propose a corresponding statistical methodology to test whether observed behaviours should be considered expressions of a hypothesized evolutionary character. We illustrate the application of our framework by characterizing the behavioural character ‘aggressiveness’ in wild great tits, Parus major. PMID:24335984

Morphological integration in the appendicular skeleton of two domestic taxa: the horse and donkey.

PubMed

Hanot, Pauline; Herrel, Anthony; Guintard, Claude; Cornette, Raphaël

2017-10-11

Organisms are organized into suites of anatomical structures that typically covary when developmentally or functionally related, and this morphological integration plays a determinant role in evolutionary processes. Artificial selection on domestic species causes strong morphological changes over short time spans, frequently resulting in a wide and exaggerated phenotypic diversity. This raises the question of whether integration constrains the morphological diversification of domestic species and how natural and artificial selection may impact integration patterns. Here, we study the morphological integration in the appendicular skeleton of domestic horses and donkeys, using three-dimensional geometric morphometrics on 75 skeletons. Our results indicate that a strong integration is inherited from developmental mechanisms which interact with functional factors. This strong integration reveals a specialization in the locomotion of domestic equids, partly for running abilities. We show that the integration is stronger in horses than in donkeys, probably because of a greater degree of specialization and predictability of their locomotion. Thus, the constraints imposed by integration are weak enough to allow important morphological changes and the phenotypic diversification of domestic species. © 2017 The Author(s).

miRNA profiling of high, low and non-producing CHO cells during biphasic fed-batch cultivation reveals process relevant targets for host cell engineering.

PubMed

Stiefel, Fabian; Fischer, Simon; Sczyrba, Alexander; Otte, Kerstin; Hesse, Friedemann

2016-05-10

Fed-batch cultivation of recombinant Chinese hamster ovary (CHO) cell lines is one of the most widely used production modes for commercial manufacturing of recombinant protein therapeutics. Furthermore, fed-batch cultivations are often conducted as biphasic processes where the culture temperature is decreased to maximize volumetric product yields. However, it remains to be elucidated which intracellular regulatory elements actually control the observed pro-productive phenotypes. Recently, several studies have revealed microRNAs (miRNAs) to be important molecular switches of cell phenotypes. In this study, we analyzed miRNA profiles of two different recombinant CHO cell lines (high and low producer), and compared them to a non-producing CHO DG44 host cell line during fed-batch cultivation at 37°C versus a temperature shift to 30°C. Taking advantage of next-generation sequencing combined with cluster, correlation and differential expression analyses, we could identify 89 different miRNAs, which were differentially expressed in the different cell lines and cultivation phases. Functional validation experiments using 19 validated target miRNAs confirmed that these miRNAs indeed induced changes in process relevant phenotypes. Furthermore, computational miRNA target prediction combined with functional clustering identified putative target genes and cellular pathways, which might be regulated by these miRNAs. This study systematically identified novel target miRNAs during different phases and conditions of a biphasic fed-batch production process and functionally evaluated their potential for host cell engineering. Copyright © 2016. Published by Elsevier B.V.

Long-term outcomes of youth who manifested the CBCL-Pediatric Bipolar Disorder phenotype during childhood and/or adolescence.

PubMed

Meyer, Stephanie E; Carlson, Gabrielle A; Youngstrom, Eric; Ronsaville, Donna S; Martinez, Pedro E; Gold, Philip W; Hakak, Rashelle; Radke-Yarrow, Marian

2009-03-01

Recent studies have identified a Child Behavior Checklist (CBCL) profile that characterizes children with severe aggression, inattention, and mood instability. This profile has been coined the CBCL-Pediatric Bipolar Disorder (PBD) phenotype, because it is commonly seen among children with bipolar disorder. However, mounting evidence suggests that the CBCL-PBD may be a better tool for identifying children with severe functional impairment and broad-ranging psychiatric comorbidities rather than bipolar disorder itself. No studies have followed individuals with the CBCL-PBD profile through adulthood, so its long-term implications remain unclear. The present authors examined diagnostic and functional trajectories of individuals with the CBCL-PBD profile from early childhood through young adulthood using data from a longitudinal high-risk study. Participants (n=101) are part of a 23-year study of youth at risk for major mood disorder who have completed diagnostic and functional assessments at regular intervals. Across development, participants with the CBCL-PBD phenotype exhibited marked psychosocial impairment, increased rates of suicidal thoughts and behaviors and heightened risk for comorbid anxiety, bipolar disorder, cluster B personality disorders and ADHD in young adulthood, compared to participants without this presentation. However, diagnostic accuracy for any one particular disorder was found to be low. Children with the CBCL-PBD profile are at risk for ongoing, severe, psychiatric symptomatology including behavior and emotional comorbidities in general, and bipolar disorder, anxiety, ADHD, cluster B personality disorders in particular. However, the value of this profile may be in predicting ongoing comorbidity and impairment, rather than any one specific DSM-IV diagnosis.

A systematic approach to identify therapeutic effects of natural products based on human metabolite information.

PubMed

Noh, Kyungrin; Yoo, Sunyong; Lee, Doheon

2018-06-13

Natural products have been widely investigated in the drug development field. Their traditional use cases as medicinal agents and their resemblance of our endogenous compounds show the possibility of new drug development. Many researchers have focused on identifying therapeutic effects of natural products, yet the resemblance of natural products and human metabolites has been rarely touched. We propose a novel method which predicts therapeutic effects of natural products based on their similarity with human metabolites. In this study, we compare the structure, target and phenotype similarities between natural products and human metabolites to capture molecular and phenotypic properties of both compounds. With the generated similarity features, we train support vector machine model to identify similar natural product and human metabolite pairs. The known functions of human metabolites are then mapped to the paired natural products to predict their therapeutic effects. With our selected three feature sets, structure, target and phenotype similarities, our trained model successfully paired similar natural products and human metabolites. When applied to the natural product derived drugs, we could successfully identify their indications with high specificity and sensitivity. We further validated the found therapeutic effects of natural products with the literature evidence. These results suggest that our model can match natural products to similar human metabolites and provide possible therapeutic effects of natural products. By utilizing the similar human metabolite information, we expect to find new indications of natural products which could not be covered by previous in silico methods.

Co-clustering phenome–genome for phenotype classification and disease gene discovery

PubMed Central

Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

2012-01-01

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

Relaxed selection is a precursor to the evolution of phenotypic plasticity.

PubMed

Hunt, Brendan G; Ometto, Lino; Wurm, Yannick; Shoemaker, DeWayne; Yi, Soojin V; Keller, Laurent; Goodisman, Michael A D

2011-09-20

Phenotypic plasticity allows organisms to produce alternative phenotypes under different conditions and represents one of the most important ways by which organisms adaptively respond to the environment. However, the relationship between phenotypic plasticity and molecular evolution remains poorly understood. We addressed this issue by investigating the evolution of genes associated with phenotypically plastic castes, sexes, and developmental stages of the fire ant Solenopsis invicta. We first determined if genes associated with phenotypic plasticity in S. invicta evolved at a rapid rate, as predicted under theoretical models. We found that genes differentially expressed between S. invicta castes, sexes, and developmental stages all exhibited elevated rates of evolution compared with ubiquitously expressed genes. We next investigated the evolutionary history of genes associated with the production of castes. Surprisingly, we found that orthologs of caste-biased genes in S. invicta and the social bee Apis mellifera evolved rapidly in lineages without castes. Thus, in contrast to some theoretical predictions, our results suggest that rapid rates of molecular evolution may not arise primarily as a consequence of phenotypic plasticity. Instead, genes evolving under relaxed purifying selection may more readily adopt new forms of biased expression during the evolution of alternate phenotypes. These results suggest that relaxed selective constraint on protein-coding genes is an important and underappreciated element in the evolutionary origin of phenotypic plasticity.

Genetic interaction networks: better understand to better predict

PubMed Central

Boucher, Benjamin; Jenna, Sarah

2013-01-01

A genetic interaction (GI) between two genes generally indicates that the phenotype of a double mutant differs from what is expected from each individual mutant. In the last decade, genome scale studies of quantitative GIs were completed using mainly synthetic genetic array technology and RNA interference in yeast and Caenorhabditis elegans. These studies raised questions regarding the functional interpretation of GIs, the relationship of genetic and molecular interaction networks, the usefulness of GI networks to infer gene function and co-functionality, the evolutionary conservation of GI, etc. While GIs have been used for decades to dissect signaling pathways in genetic models, their functional interpretations are still not trivial. The existence of a GI between two genes does not necessarily imply that these two genes code for interacting proteins or that the two genes are even expressed in the same cell. In fact, a GI only implies that the two genes share a functional relationship. These two genes may be involved in the same biological process or pathway; or they may also be involved in compensatory pathways with unrelated apparent function. Considering the powerful opportunity to better understand gene function, genetic relationship, robustness and evolution, provided by a genome-wide mapping of GIs, several in silico approaches have been employed to predict GIs in unicellular and multicellular organisms. Most of these methods used weighted data integration. In this article, we will review the later knowledge acquired on GI networks in metazoans by looking more closely into their relationship with pathways, biological processes and molecular complexes but also into their modularity and organization. We will also review the different in silico methods developed to predict GIs and will discuss how the knowledge acquired on GI networks can be used to design predictive tools with higher performances. PMID:24381582

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

PubMed

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.

Duffy blood group phenotype-genotype correlations using high-resolution melting analysis PCR and microarray reveal complex cases including a new null FY*A allele: the role for sequencing in genotyping algorithms.

PubMed

Lopez, G H; Morrison, J; Condon, J A; Wilson, B; Martin, J R; Liew, Y-W; Flower, R L; Hyland, C A

2015-10-01

Duffy blood group phenotypes can be predicted by genotyping for single nucleotide polymorphisms (SNPs) responsible for the Fy(a) /Fy(b) polymorphism, for weak Fy(b) antigen, and for the red cell null Fy(a-b-) phenotype. This study correlates Duffy phenotype predictions with serotyping to assess the most reliable procedure for typing. Samples, n = 155 (135 donors and 20 patients), were genotyped by high-resolution melt PCR and by microarray. Samples were in three serology groups: 1) Duffy patterns expected n = 79, 2) weak and equivocal Fy(b) patterns n = 29 and 3) Fy(a-b-) n = 47 (one with anti-Fy3 antibody). Discrepancies were observed for five samples. For two, SNP genotyping predicted weak Fy(b) expression discrepant with Fy(b-) (Group 1 and 3). For three, SNP genotyping predicted Fy(a) , discrepant with Fy(a-b-) (Group 3). DNA sequencing identified silencing mutations in these FY*A alleles. One was a novel FY*A 719delG. One, the sample with the anti-Fy3, was homozygous for a 14-bp deletion (FY*01N.02); a true null. Both the high-resolution melting analysis and SNP microarray assays were concordant and showed genotyping, as well as phenotyping, is essential to ensure 100% accuracy for Duffy blood group assignments. Sequencing is important to resolve phenotype/genotype conflicts which here identified alleles, one novel, that carry silencing mutations. The risk of alloimmunisation may be dependent on this zygosity status. © 2015 International Society of Blood Transfusion.

Association of various blood pressure variables and vascular phenotypes with coronary, stroke and renal deaths: Potential implications for prevention.

PubMed

Harbaoui, Brahim; Courand, Pierre-Yves; Milon, Hughes; Fauvel, Jean-Pierre; Khettab, Fouad; Mechtouff, Laura; Cassar, Emmanuel; Girerd, Nicolas; Lantelme, Pierre

2015-11-01

The relationship between blood pressure (BP) and cardiovascular diseases has been extensively documented. However, the benefit of anti-hypertensive drugs differs according to the type of cardiovascular event. Aortic stiffness is tightly intertwined with BP and aorta cross-talk with small arteries. We endeavored to elucidate which BP component and type of vessel remodeling was predictive of the following outcomes: fatal myocardial infarction (MI), fatal stroke, renal -, coronary- or cerebrovascular-related deaths. Large vessel remodeling was estimated by an aortography-based aortic atherosclerosis score (ATS) while small vessel disease was documented by the presence of a hypertensive retinopathy. We included 1031 subjects referred for hypertension workup and assessed outcomes 30 years later. After adjustment for major risk factors, ATS and pulse pressure (PP) were predictive of coronary events while mean BP (MBP) and retinopathy were not. On the contrary, MBP was predictive of cerebrovascular and renal related deaths while ATS and PP were not. Retinopathy was only predictive of cerebrovascular related deaths. Lastly, the aortic atherosclerosis phenotype and increased PP identified patients prone to develop fatal MI whereas the retinopathy phenotype and increased MBP identified patients at higher risk of fatal stroke. These results illustrate the particular feature of the resistive coronary circulation comparatively to the brain and kidneys' low-resistance circulation. Our results advocate for a rational preventive strategy based on the identification of distinct clinical phenotypes. Accordingly, decreasing MBP levels could help preventing stroke in retinopathy phenotypes whereas targeting PP is possibly more efficient in preventing MI in atherosclerotic phenotypes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

PHF21B overexpression promotes cancer stem cell-like traits in prostate cancer cells by activating the Wnt/β-catenin signaling pathway.

PubMed

Li, Qiji; Ye, Liping; Guo, Wei; Wang, Min; Huang, Shuai; Peng, Xinsheng

2017-06-23

PHF21B is newly identified to be involved in the tumor progression; however, its biological role and molecular mechanism in prostate cancer have not been defined. This study is aimed to study the role of PHF21B in the progression of prostate cancer. Real-time PCR, immunohistochemistry and western blotting analysis were used to determine PHF21B expression in prostate cancer cell lines and clinical specimens. The role of PHF21B in maintaining prostate cancer stem cell-like phenotype was examined by tumor-sphere formation assay and expression levels of stem cell markers. Luciferase reporter assay, western blot analysis, enzyme-linked immunosorbent assay and ChIP assay were used to determine whether PHF21B activates the Wnt/β-catenin signaling by transcriptionally downregulating SFRP1 and SFRP2. Our results revealed that PHF21B was markedly upregulated in prostate cancer cell lines and tissues. High PHF21B levels predicted poorer recurrence-free survival in prostate cancer patients. Gain-of-function and loss-of-function studies showed that overexpression of PHF21B enhanced, while downregulation suppressed, the cancer stem cell-like phenotype in prostate cancer cells. Xenograft tumor model showed that silencing PHF21B decreased the ability of tumorigenicity in vivo. Notably, Wnt/β-catenin signaling was hyperactivated in prostate cancer cells overexpressing PHF21B, and mediated PHF21B-induced cancer stem cell-like phenotype. Furthermore, PHF21B suppressed repressors of the Wnt/β-catenin signaling cascade, including SFRP1 and SFRP2. These results demonstrated that PHF21B constitutively activated wnt/β-catenin signaling by transcriptionally downregulating SFRP1 and SFRP2, which promotes prostate cancer stem cell-like phenotype. Our results revealed that PHF21B functions as an oncogene in prostate cancer, and may represent a promising prognostic biomarker and an attractive candidate for target therapy of prostate cancer.

Childhood CBCL Bipolar Profile and Adolescent/Young Adult Personality Disorders: A 9-year Follow-up

PubMed Central

Halperin, Jeffrey M.; Rucklidge, Julia J.; Powers, Robyn L.; Miller, Carlin J.; Newcorn, Jeffrey H.

2010-01-01

Background To assess the late adolescent psychiatric outcomes associated with a positive Child Behavior Checklist – Juvenile Bipolar Disorder Phenotype (CBCL-JBD) in children diagnosed with ADHD and followed over a 9-year period. Methods Parents of 152 children diagnosed as ADHD (ages 7–11 years) completed the CBCL. Ninety of these parents completed it again 9 years later as part of a comprehensive evaluation of Axis I and II diagnoses as assessed using semi-structured interviews. As previously proposed, the CBCL-JBD phenotype was defined as T-scores of 70 or greater on the Attention Problems, Aggression, and Anxiety/Depression subscales. Results The CBCL-JBD phenotype was found in 31% of those followed but only 4.9% of the sample continued to meet the phenotype criteria at follow up. Only two of the sample developed Bipolar Disorder by late adolescence and only one of those had the CBCL-JBD profile in childhood. The proxy did not predict any Axis I disorders. However, the CBCL-JBD proxy was highly predictive of later personality disorders. Limitations Only a subgroup of the original childhood sample was followed. Given this sample was confined to children with ADHD, it is not known whether the prediction of personality disorders from CBCL scores would generalize to a wider community or clinical population Conclusions A positive CBCL-JBD phenotype profile in childhood does not predict Axis I Disorders in late adolescence; however, it may be prognostic of the emergence of personality disorders. PMID:21056910

Similar predictions of etravirine sensitivity regardless of genotypic testing method used: comparison of available scoring systems.

PubMed

Vingerhoets, Johan; Nijs, Steven; Tambuyzer, Lotke; Hoogstoel, Annemie; Anderson, David; Picchio, Gaston

2012-01-01

The aims of this study were to compare various genotypic scoring systems commonly used to predict virological outcome to etravirine, and examine their concordance with etravirine phenotypic susceptibility. Six etravirine genotypic scoring systems were assessed: Tibotec 2010 (based on 20 mutations; TBT 20), Monogram, Stanford HIVdb, ANRS, Rega (based on 37, 30, 27 and 49 mutations, respectively) and virco(®)TYPE HIV-1 (predicted fold change based on genotype). Samples from treatment-experienced patients who participated in the DUET trials and with both genotypic and phenotypic data (n=403) were assessed using each scoring system. Results were retrospectively correlated with virological response in DUET. κ coefficients were calculated to estimate the degree of correlation between the different scoring systems. Correlation between the five scoring systems and the TBT 20 system was approximately 90%. Virological response by etravirine susceptibility was comparable regardless of which scoring system was utilized, with 70-74% of DUET patients determined as susceptible to etravirine by the different scoring systems achieving plasma viral load <50 HIV-1 RNA copies/ml. In samples classed as phenotypically susceptible to etravirine (fold change in 50% effective concentration ≤3), correlations with genotypic score were consistently high across scoring systems (≥70%). In general, the etravirine genotypic scoring systems produced similar results, and genotype-phenotype concordance was high. As such, phenotypic interpretations, and in their absence all genotypic scoring systems investigated, may be used to reliably predict the activity of etravirine.

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

PubMed

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.

Potential fitness benefits of the half-pounder life history in Klamath River steelhead

USGS Publications Warehouse

Hodge, Brian W.; Wilzbach, Peggy; Duffy, Walter G.

2014-01-01

Steelhead Oncorhynchus mykiss from several of the world's rivers display the half-pounder life history, a variant characterized by an amphidromous (and, less often, anadromous) return to freshwater in the year of initial ocean entry. We evaluated factors related to expression of the half-pounder life history in wild steelhead from the lower Klamath River basin, California. We also evaluated fitness consequences of the half-pounder phenotype using a simple life history model that was parameterized with our empirical data and outputs from a regional survival equation. The incidence of the half-pounder life history differed among subbasins of origin and smolt ages. Precocious maturation occurred in approximately 8% of half-pounders and was best predicted by individual length in freshwater preceding ocean entry. Adult steelhead of the half-pounder phenotype were smaller and less fecund at age than adult steelhead of the alternative (ocean contingent) phenotype. However, our data suggest that fish of the half-pounder phenotype are more likely to spawn repeatedly than are fish of the ocean contingent phenotype. Models predicted that if lifetime survivorship were equal between phenotypes, the fitness of the half-pounder phenotype would be 17–28% lower than that of the ocean contingent phenotype. To meet the condition of equal fitness between phenotypes would require that first-year ocean survival be 21–40% higher among half-pounders in freshwater than among their cohorts at sea. We concluded that continued expression of the half-pounder phenotype is favored by precocious maturation and increased survival relative to that of the ocean contingent phenotype.

Single Nucleotide Polymorphisms of Stemness Genes Predicted to Regulate RNA Splicing, microRNA and Oncogenic Signaling are Associated with Prostate Cancer Survival.

PubMed

Freedman, Jennifer A; Wang, Yanru; Li, Xuechan; Liu, Hongliang; Moorman, Patricia G; George, Daniel J; Lee, Norman H; Hyslop, Terry; Wei, Qingyi; Patierno, Steven R

2018-05-03

Prostate cancer is a clinically and molecularly heterogeneous disease, with variation in outcomes only partially predicted by grade and stage. Additional tools to distinguish indolent from aggressive disease are needed. Phenotypic characteristics of stemness correlate with poor cancer prognosis. Given this correlation, we identified single nucleotide polymorphisms (SNPs) of stemness-related genes and examined their associations with prostate cancer survival. SNPs within stemness-related genes were analyzed for association with overall survival of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Significant SNPs predicted to be functional were selected for linkage disequilibrium analysis and combined and stratified analyses. Identified SNPs were evaluated for association with gene expression. SNPs of CD44 (rs9666607), ABCC1 (rs35605 and rs212091) and GDF15 (rs1058587) were associated with prostate cancer survival and predicted to be functional. A role for rs9666607 of CD44 and rs35605 of ABCC1 in RNA splicing regulation, rs212091 of ABCC1 in miRNA binding site activity and rs1058587 of GDF15 in causing an amino acid change was predicted. These SNPs represent potential novel prognostic markers for overall survival of prostate cancer and support a contribution of the stemness pathway to prostate cancer patient outcome.

Predicting fibromyalgia, a narrative review: are we better than fools and children?

PubMed

Ablin, J N; Buskila, D

2014-09-01

Fibromyalgia syndrome (FMS) is a common and intriguing condition, manifest by chronic pain and fatigue. Although the pathogenesis of FMS is not yet completely understood, predicting the future development of FMS and chronic pain is a major challenge with great potential advantages, both from an individual as well as an epidemiological standpoint. Current knowledge indicates a genetic underpinning for FMS, and as increasing data are accumulated regarding the genetics involved, the prospect of utilizing these data for prediction becomes ever more attractive. The co-existence of FMS with multiple other functional disorders indicates that the clinical identification of such symptom constellations in a patient can alert the physician to the future development of FMS. Hypermobility syndrome is another clinical (as well as genetic) phenotype that has emerged as a risk factor for the development of FMS. Stressful events, including early life trauma, are also harbingers of the future development of FMS. Functional neuroimaging may help to elucidate the neural processes involved in central sensitization, and may ultimately also evolve into markers of predictive value. Last but not least, obesity and disturbed sleep are clinical (inter-related) features relevant for this spectrum. Future efforts will aim at integrating genetic, clinical and physiological data in the prediction of FMS and chronic pain. © 2014 European Pain Federation - EFIC®

Pre- and Post-Natal Maternal Depressive Symptoms in Relation with Infant Frontal Function, Connectivity, and Behaviors

PubMed Central

Soe, Ni Ni; Wen, Daniel J.; Poh, Joann S.; Li, Yue; Broekman, Birit F. P.; Chen, Helen; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Gluckman, Peter D.; Meaney, Michael J.; Rifkin-Graboi, Anne; Qiu, Anqi

2016-01-01

This study investigated the relationships between pre- and early post-natal maternal depression and their changes with frontal electroencephalogram (EEG) activity and functional connectivity in 6- and 18-month olds, as well as externalizing and internalizing behaviors in 24-month olds (n = 258). Neither prenatal nor postnatal maternal depressive symptoms independently predicted neither the frontal EEG activity nor functional connectivity in 6- and 18-month infants. However, increasing maternal depressive symptoms from the prenatal to postnatal period predicted greater right frontal activity and relative right frontal asymmetry amongst 6-month infants but these finding were not observed amongst 18-month infants after adjusted for post-conceptual age on the EEG visit day. Subsequently increasing maternal depressive symptoms from the prenatal to postnatal period predicted lower right frontal connectivity within 18-month infants but not among 6-month infants after controlling for post-conceptual age on the EEG visit day. These findings were observed in the full sample and the female sample but not in the male sample. Moreover, both prenatal and early postnatal maternal depressive symptoms independently predicted children’s externalizing and internalizing behaviors at 24 months of age. This suggests that the altered frontal functional connectivity in infants born to mothers whose depressive symptomatology increases in the early postnatal period compared to that during pregnancy may reflect a neural basis for the familial transmission of phenotypes associated with mood disorders, particularly in girls. PMID:27073881

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset. PMID:28846712

Transferrin saturation phenotype and HFE genotype screening for hemochromatosis and primary iron overload: predictions from a model based on national, racial, and ethnic group composition in central Alabama.

PubMed

Barton, J C; Acton, R T

2000-01-01

There is interest in general population screening for hemochromatosis and other primary iron overload disorders, although not all persons are at equal risk. We developed a model to estimate the numbers of persons in national, racial, or ethnic population subgroups in Jefferson County, Alabama, who would be detected using transferrin saturation (phenotype) or HFE mutation analysis (genotype) screening. Approximately 62% are Caucasians, 37% are African Americans, and the remainder are Hispanics, Asians, or Native Americans. The predicted phenotype frequencies are greatest in a Caucasian subgroup, ethnicity unspecified, which consists predominantly of persons of Scotch and Irish descent (0.0065 men, 0.0046 women), and in African Americans (0.0089 men, 0.0085 women). Frequencies of the HFE genotype C282Y/C282Y > or = 0.0001 are predicted to occur only among Caucasians; the greatest frequency (0.0080) was predicted to occur in the ethnicity-unspecified Caucasian population. C282Y/C282Y frequency estimates were lower in Italian, Greek, and Jewish subgroups. There is excellent agreement in the numbers of the ethnicity-unspecified Caucasians who would be detected using phenotype and genotype criteria. Our model also indicates that phenotyping would identify more persons with primary iron overload than would genotyping in our Italian Caucasian, Hispanic, and African American subgroups. This is consistent with previous observations that indicate that primary iron overload disorders in persons of southern Italian descent and African Americans are largely attributable to non-HFE alleles. Because the proportions of population subgroups and their genetic constitution may differ significantly in other geographic regions, we suggest that models similar to the present one be constructed to predict optimal screening strategies for primary iron overload disorders.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling.

PubMed

Povey, Jane F; O'Malley, Christopher J; Root, Tracy; Martin, Elaine B; Montague, Gary A; Feary, Marc; Trim, Carol; Lang, Dietmar A; Alldread, Richard; Racher, Andrew J; Smales, C Mark

2014-08-20

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements. Copyright © 2014 Elsevier B.V. All rights reserved.

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

PubMed

DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

2017-06-01

Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa

PubMed Central

DeGuzman, Marisa; Shott, Megan E.; Yang, Tony T.; Riederer, Justin; Frank, Guido K.W.

2017-01-01

Objective Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Method Female adolescents with anorexia nervosa (N=21; mean age, 15.2 years [SD=2.4]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 16.4 years [SD=1.9]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Results Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Conclusions Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs. PMID:28231717

Two recessive mutations in FGF5 are associated with the long-hair phenotype in donkeys.

PubMed

Legrand, Romain; Tiret, Laurent; Abitbol, Marie

2014-09-25

Seven donkey breeds are recognized by the French studbook. Individuals from the Pyrenean, Provence, Berry Black, Normand, Cotentin and Bourbonnais breeds are characterized by a short coat, while those from the Poitou breed (Baudet du Poitou) are characterized by a long-hair phenotype. We hypothesized that loss-of-function mutations in the FGF5 (fibroblast growth factor 5) gene, which are associated with a long-hair phenotype in several mammalian species, may account for the special coat feature of Poitou donkeys. To the best of our knowledge, mutations in FGF5 have never been described in Equidae. We sequenced the FGF5 gene from 35 long-haired Poitou donkeys, as well as from a panel of 67 short-haired donkeys from the six other French breeds and 131 short-haired ponies and horses. We identified a recessive c.433_434delAT frameshift deletion in FGF5, present in Poitou and three other donkey breeds and a recessive nonsense c.245G > A substitution, present in Poitou and four other donkey breeds. The frameshift deletion was associated with the long-hair phenotype in Poitou donkeys when present in two copies (n = 31) or combined with the nonsense mutation (n = 4). The frameshift deletion led to a stop codon at position 159 whereas the nonsense mutation led to a stop codon at position 82 in the FGF5 protein. In silico, the two truncated FGF5 proteins were predicted to lack the critical β strands involved in the interaction between FGF5 and its receptor, a mandatory step to inhibit hair growth. Our results highlight the allelic heterogeneity of the long-hair phenotype in donkeys and enlarge the panel of recessive FGF5 loss-of-function alleles described in mammals. Thanks to the DNA test developed in this study, breeders of non-Poitou breeds will have the opportunity to identify long-hair carriers in their breeding stocks.

Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers.

PubMed

Loehr, John; O'Hara, Robert B

2013-08-23

We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939-1940). We measured facial width-to-height ratio-a trait known to predict aggressive behaviour in males-and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank.

X-linked CHARGE-like Abruzzo-Erickson syndrome and classic cleft palate with ankyloglossia result from TBX22 splicing mutations.

PubMed

Pauws, E; Peskett, E; Boissin, C; Hoshino, A; Mengrelis, K; Carta, E; Abruzzo, M A; Lees, M; Moore, G E; Erickson, R P; Stanier, P

2013-04-01

X-linked cleft palate (CPX) is caused by mutations in the gene encoding the TBX22 transcription factor and is known to exhibit phenotypic variability, usually involving either a complete, partial or submucous cleft palate, with or without ankyloglossia. This study hypothesized a possible involvement of TBX22 in a family with X-linked, CHARGE-like Abruzzo-Erickson syndrome, of unknown etiology. The phenotype extends to additional features including sensorineural deafness and coloboma, which are suggested by the Tbx22 developmental expression pattern but not previously associated in CPX patients. A novel TBX22 splice acceptor mutation (c.593-5T>A) was identified that tracked with the phenotype in this family. A novel splice donor variant (c.767+5G>A) and a known canonical splice donor mutation (c.767+1G>A) affecting the same exon were identified in patients with classic CPX phenotypes and were comparatively analyzed using both in silico and in vitro splicing studies. All three variants were predicted to abolish normal mRNA splicing and an in vitro assay indicated that use of alternative splice sites was a likely outcome. Collectively, the data showed the functional effect of several novel intronic splice site variants but most importantly confirms that TBX22 is the gene underlying Abruzzo-Erickson syndrome, expanding the phenotypic spectrum of TBX22 mutations. © 2012 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

PubMed

Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

2014-12-01

Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p < 0.0001), and respiratory cause mortality (HR 21.5, p < 0.0001) than those in the other four groups. Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

Comparative systems biology across an evolutionary gradient within the Shewanella genus.

PubMed

Konstantinidis, Konstantinos T; Serres, Margrethe H; Romine, Margaret F; Rodrigues, Jorge L M; Auchtung, Jennifer; McCue, Lee-Ann; Lipton, Mary S; Obraztsova, Anna; Giometti, Carol S; Nealson, Kenneth H; Fredrickson, James K; Tiedje, James M

2009-09-15

To what extent genotypic differences translate to phenotypic variation remains a poorly understood issue of paramount importance for several cornerstone concepts of microbiology including the species definition. Here, we take advantage of the completed genomic sequences, expressed proteomic profiles, and physiological studies of 10 closely related Shewanella strains and species to provide quantitative insights into this issue. Our analyses revealed that, despite extensive horizontal gene transfer within these genomes, the genotypic and phenotypic similarities among the organisms were generally predictable from their evolutionary relatedness. The power of the predictions depended on the degree of ecological specialization of the organisms evaluated. Using the gradient of evolutionary relatedness formed by these genomes, we were able to partly isolate the effect of ecology from that of evolutionary divergence and to rank the different cellular functions in terms of their rates of evolution. Our ranking also revealed that whole-cell protein expression differences among these organisms, when the organisms were grown under identical conditions, were relatively larger than differences at the genome level, suggesting that similarity in gene regulation and expression should constitute another important parameter for (new) species description. Collectively, our results provide important new information toward beginning a systems-level understanding of bacterial species and genera.

Barriers to adaptive reasoning in community ecology.

PubMed

McLachlan, Athol J; Ladle, Richard J

2011-08-01

Recent high-profile calls for a more trait-focused approach to community ecology have the potential to open up novel research areas, generate new insights and to transform community ecology into a more predictive science. However, a renewed emphasis on function and phenotype also requires a fundamental shift in approach and research philosophy within community ecology to more fully embrace evolutionary reasoning. Such a subject-wise transformation will be difficult due to at least four factors: (1) the historical development of the academic discipline of ecology and its roots as a descriptive science; (2) the dominating role of the ecosystem concept in the driving of contemporary ecological thought; (3) the practical difficulties associated with defining and identifying (phenotypic) adaptations, and; (4) scaling effects in ecology; the difficulty of teasing apart the overlapping and shifting hierarchical processes that generate the observed environment-trait correlations in nature. We argue that the ability to predict future ecological conditions through a sufficient understanding of ecological processes will not be achieved without the placement of the concept of adaptation at the centre of ecology, with influence radiating outwards through all the related (and rapidly specializing) sub-disciplines. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.

A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence.

PubMed

de Souza, Camila Ferreira; Sabedot, Thais S; Malta, Tathiane M; Stetson, Lindsay; Morozova, Olena; Sokolov, Artem; Laird, Peter W; Wiznerowicz, Maciej; Iavarone, Antonio; Snyder, James; deCarvalho, Ana; Sanborn, Zachary; McDonald, Kerrie L; Friedman, William A; Tirapelli, Daniela; Poisson, Laila; Mikkelsen, Tom; Carlotti, Carlos G; Kalkanis, Steven; Zenklusen, Jean; Salama, Sofie R; Barnholtz-Sloan, Jill S; Noushmehr, Houtan

2018-04-10

Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease. G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell-like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change.

PubMed

Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O

2018-04-24

As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.

A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

PubMed Central

2012-01-01

Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

Identification and individualized prediction of clinical phenotypes in bipolar disorders using neurocognitive data, neuroimaging scans and machine learning.

PubMed

Wu, Mon-Ju; Mwangi, Benson; Bauer, Isabelle E; Passos, Ives C; Sanches, Marsal; Zunta-Soares, Giovana B; Meyer, Thomas D; Hasan, Khader M; Soares, Jair C

2017-01-15

Diagnosis, clinical management and research of psychiatric disorders remain subjective - largely guided by historically developed categories which may not effectively capture underlying pathophysiological mechanisms of dysfunction. Here, we report a novel approach of identifying and validating distinct and biologically meaningful clinical phenotypes of bipolar disorders using both unsupervised and supervised machine learning techniques. First, neurocognitive data were analyzed using an unsupervised machine learning approach and two distinct clinical phenotypes identified namely; phenotype I and phenotype II. Second, diffusion weighted imaging scans were pre-processed using the tract-based spatial statistics (TBSS) method and 'skeletonized' white matter fractional anisotropy (FA) and mean diffusivity (MD) maps extracted. The 'skeletonized' white matter FA and MD maps were entered into the Elastic Net machine learning algorithm to distinguish individual subjects' phenotypic labels (e.g. phenotype I vs. phenotype II). This calculation was performed to ascertain whether the identified clinical phenotypes were biologically distinct. Original neurocognitive measurements distinguished individual subjects' phenotypic labels with 94% accuracy (sensitivity=92%, specificity=97%). TBSS derived FA and MD measurements predicted individual subjects' phenotypic labels with 76% and 65% accuracy respectively. In addition, individual subjects belonging to phenotypes I and II were distinguished from healthy controls with 57% and 92% accuracy respectively. Neurocognitive task variables identified as most relevant in distinguishing phenotypic labels included; Affective Go/No-Go (AGN), Cambridge Gambling Task (CGT) coupled with inferior fronto-occipital fasciculus and callosal white matter pathways. These results suggest that there may exist two biologically distinct clinical phenotypes in bipolar disorders which can be identified from healthy controls with high accuracy and at an individual subject level. We suggest a strong clinical utility of the proposed approach in defining and validating biologically meaningful and less heterogeneous clinical sub-phenotypes of major psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

Mutations in PIGY: expanding the phenotype of inherited glycosylphosphatidylinositol deficiencies

PubMed Central

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.

2015-01-01

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. PMID:26293662

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

PubMed Central

Bartlett, Madelaine E.; Whipple, Clinton J.

2013-01-01

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; altered protein–protein interactions; altered domain content; altered activity as an activator or repressor; altered protein stability; and hypomorphic and hypermorphic alleles. There was also variability 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. PMID:24124420

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

PubMed

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.

Phenylalanine hydroxylase deficiency in Mexico: genotype-phenotype correlations, BH4 responsiveness and evidence of a founder effect.

PubMed

Vela-Amieva, M; Abreu-González, M; González-del Angel, A; Ibarra-González, I; Fernández-Lainez, C; Barrientos-Ríos, R; Monroy-Santoyo, S; Guillén-López, S; Alcántara-Ortigoza, M A

2015-07-01

The mutational spectrum of the phenylalanine hydroxylase gene (PAH) in Mexico is unknown, although it has been suggested that PKU variants could have a differential geographical distribution. Genotype-phenotype correlations and genotype-based predictions of responsiveness to tetrahydrobiopterin (BH4 ) have never been performed. We sequenced the PAH gene and determined the geographic origin of each allele, mini-haplotype associated, genotype-phenotype correlations and genotype-based prediction of BH4 responsiveness in 48 Mexican patients. The mutational spectrum included 34 variants with c.60+5G>T being the most frequent (20.8%) and linked to haplotype 4.3 possibly because of a founder effect and/or genetic drift. Two new variants were found c.1A>T and c.969+6T>C. The genotype-phenotype correlation was concordant in 70.8%. The genotype-based prediction to BH4 -responsiveness was 41.7%, this information could be useful for the rational selection of candidates for BH4 testing and therapy. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Functional characterisation of osteosarcoma cell lines and identification of mRNAs and miRNAs associated with aggressive cancer phenotypes

PubMed Central

Lauvrak, S U; Munthe, E; Kresse, S H; Stratford, E W; Namløs, H M; Meza-Zepeda, L A; Myklebost, O

2013-01-01

Background: Osteosarcoma is the most common primary malignant bone tumour, predominantly affecting children and adolescents. Cancer cell line models are required to understand the underlying mechanisms of tumour progression and for preclinical investigations. Methods: To identify cell lines that are well suited for studies of critical cancer-related phenotypes, such as tumour initiation, growth and metastasis, we have evaluated 22 osteosarcoma cell lines for in vivo tumorigenicity, in vitro colony-forming ability, invasive/migratory potential and proliferation capacity. Importantly, we have also identified mRNA and microRNA (miRNA) gene expression patterns associated with these phenotypes by expression profiling. Results: The cell lines exhibited a wide range of cancer-related phenotypes, from rather indolent to very aggressive. Several mRNAs were differentially expressed in highly aggressive osteosarcoma cell lines compared with non-aggressive cell lines, including RUNX2, several S100 genes, collagen genes and genes encoding proteins involved in growth factor binding, cell adhesion and extracellular matrix remodelling. Most notably, four genes—COL1A2, KYNU, ACTG2 and NPPB—were differentially expressed in high and non-aggressive cell lines for all the cancer-related phenotypes investigated, suggesting that they might have important roles in the process of osteosarcoma tumorigenesis. At the miRNA level, miR-199b-5p and mir-100-3p were downregulated in the highly aggressive cell lines, whereas miR-155-5p, miR-135b-5p and miR-146a-5p were upregulated. miR-135b-5p and miR-146a-5p were further predicted to be linked to the metastatic capacity of the disease. Interpretation: The detailed characterisation of cell line phenotypes will support the selection of models to use for specific preclinical investigations. The differentially expressed mRNAs and miRNAs identified in this study may represent good candidates for future therapeutic targets. To our knowledge, this is the first time that expression profiles are associated with functional characteristics of osteosarcoma cell lines. PMID:24064976

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

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

PubMed Central

Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra

2015-01-01

Objectives 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. Methods 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. Results 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. Conclusions 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. PMID:25764521

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.

PubMed

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.

Disease Modeling via Large-Scale Network Analysis

DTIC Science & Technology

2015-05-20

SECURITY CLASSIFICATION OF: A central goal of genetics is to learn how the genotype of an organism determines its phenotype. We address the implicit...guarantees for the methods. In the past, we have developed predictive methods general enough to apply to potentially any genetic trait, varying from... genetics is to learn how the genotype of an organism determines its phenotype. We address the implicit problem of predicting the association of genes with

Antimicrobial resistance prediction in PATRIC and RAST

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, James J.; Boisvert, Sebastien; Brettin, Thomas

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned bymore » their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.« less

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

PubMed

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E; Kayser, Manfred

2017-02-27

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour

PubMed Central

Wollstein, Andreas; Walsh, Susan; Liu, Fan; Chakravarthy, Usha; Rahu, Mati; Seland, Johan H.; Soubrane, Gisèle; Tomazzoli, Laura; Topouzis, Fotis; Vingerling, Johannes R.; Vioque, Jesus; Böhringer, Stefan; Fletcher, Astrid E.; Kayser, Manfred

2017-01-01

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing. PMID:28240252

Antimicrobial resistance prediction in PATRIC and RAST

DOE PAGES

Davis, James J.; Boisvert, Sebastien; Brettin, Thomas; ...

2016-06-14

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned bymore » their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii, methicillin resistance in Staphylococcus aureus, and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis, achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.« less

Brief Report: IQ Split Predicts Social Symptoms and Communication Abilities in High-Functioning Children with Autism Spectrum Disorders

PubMed Central

Wallace, Gregory L.; Sokoloff, Jennifer L.; Kenworthy, Lauren

2011-01-01

We investigated the relationship of discrepancies between VIQ and NVIQ (IQ split) to autism symptoms and adaptive behavior in a sample of high-functioning (mean FSIQ = 98.5) school-age children with autism spectrum disorders divided into three groups: discrepantly high VIQ (n = 18); discrepantly high NVIQ (n = 24); and equivalent VIQ and NVIQ (n = 36). Discrepantly high VIQ and NVIQ were associated with autism social symptoms but not communication symptoms or repetitive behaviors. Higher VIQ and NVIQ were associated with better adaptive communication but not socialization or Daily Living Skills. IQ discrepancy may be an important phenotypic marker in autism. Although better verbal abilities are associated with better functional outcomes in autism, discrepantly high VIQ in high-functioning children may also be associated with social difficulties. PMID:19572193

Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.

PubMed

Cuthbertson, Carmen C; Kucharska-Newton, Anna; Faurot, Keturah R; Stürmer, Til; Jonsson Funk, Michele; Palta, Priya; Windham, B Gwen; Thai, Sydney; Lund, Jennifer L

2018-07-01

Frailty is a geriatric syndrome characterized by weakness and weight loss and is associated with adverse health outcomes. It is often an unmeasured confounder in pharmacoepidemiologic and comparative effectiveness studies using administrative claims data. Among the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 participants (2011-2013; n = 3,146), we conducted a validation study to compare a Medicare claims-based algorithm of dependency in activities of daily living (or dependency) developed as a proxy for frailty with a reference standard measure of phenotypic frailty. We applied the algorithm to the ARIC participants' claims data to generate a predicted probability of dependency. Using the claims-based algorithm, we estimated the C-statistic for predicting phenotypic frailty. We further categorized participants by their predicted probability of dependency (<5%, 5% to <20%, and ≥20%) and estimated associations with difficulties in physical abilities, falls, and mortality. The claims-based algorithm showed good discrimination of phenotypic frailty (C-statistic = 0.71; 95% confidence interval [CI] = 0.67, 0.74). Participants classified with a high predicted probability of dependency (≥20%) had higher prevalence of falls and difficulty in physical ability, and a greater risk of 1-year all-cause mortality (hazard ratio = 5.7 [95% CI = 2.5, 13]) than participants classified with a low predicted probability (<5%). Sensitivity and specificity varied across predicted probability of dependency thresholds. The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses.

PubMed

Amuzu-Aweh, E N; Bijma, P; Kinghorn, B P; Vereijken, A; Visscher, J; van Arendonk, J Am; Bovenhuis, H

2013-12-01

Prediction of heterosis has a long history with mixed success, partly due to low numbers of genetic markers and/or small data sets. We investigated the prediction of heterosis for egg number, egg weight and survival days in domestic white Leghorns, using ∼400 000 individuals from 47 crosses and allele frequencies on ∼53 000 genome-wide single nucleotide polymorphisms (SNPs). When heterosis is due to dominance, and dominance effects are independent of allele frequencies, heterosis is proportional to the squared difference in allele frequency (SDAF) between parental pure lines (not necessarily homozygous). Under these assumptions, a linear model including regression on SDAF partitions crossbred phenotypes into pure-line values and heterosis, even without pure-line phenotypes. We therefore used models where phenotypes of crossbreds were regressed on the SDAF between parental lines. Accuracy of prediction was determined using leave-one-out cross-validation. SDAF predicted heterosis for egg number and weight with an accuracy of ∼0.5, but did not predict heterosis for survival days. Heterosis predictions allowed preselection of pure lines before field-testing, saving ∼50% of field-testing cost with only 4% loss in heterosis. Accuracies from cross-validation were lower than from the model-fit, suggesting that accuracies previously reported in literature are overestimated. Cross-validation also indicated that dominance cannot fully explain heterosis. Nevertheless, the dominance model had considerable accuracy, clearly greater than that of a general/specific combining ability model. This work also showed that heterosis can be modelled even when pure-line phenotypes are unavailable. We concluded that SDAF is a useful predictor of heterosis in commercial layer breeding.

Nmf9 Encodes a Highly Conserved Protein Important to Neurological Function in Mice and Flies.

PubMed

Zhang, Shuxiao; Ross, Kevin D; Seidner, Glen A; Gorman, Michael R; Poon, Tiffany H; Wang, Xiaobo; Keithley, Elizabeth M; Lee, Patricia N; Martindale, Mark Q; Joiner, William J; Hamilton, Bruce A

2015-07-01

Many protein-coding genes identified by genome sequencing remain without functional annotation or biological context. Here we define a novel protein-coding gene, Nmf9, based on a forward genetic screen for neurological function. ENU-induced and genome-edited null mutations in mice produce deficits in vestibular function, fear learning and circadian behavior, which correlated with Nmf9 expression in inner ear, amygdala, and suprachiasmatic nuclei. Homologous genes from unicellular organisms and invertebrate animals predict interactions with small GTPases, but the corresponding domains are absent in mammalian Nmf9. Intriguingly, homozygotes for null mutations in the Drosophila homolog, CG45058, show profound locomotor defects and premature death, while heterozygotes show striking effects on sleep and activity phenotypes. These results link a novel gene orthology group to discrete neurological functions, and show conserved requirement across wide phylogenetic distance and domain level structural changes.

THE EVOLUTION OF CANALIZATION AND THE BREAKING OF VON BAER'S LAWS: MODELING THE EVOLUTION OF DEVELOPMENT WITH EPISTASIS.

PubMed

Rice, Sean H

1998-06-01

Evolution can change the developmental processes underlying a character without changing the average expression of the character itself. This sort of change must occur in both the evolution of canalization, in which a character becomes increasingly buffered against genetic or developmental variation, and in the phenomenon of closely related species that show similar adult phenotypes but different underlying developmental patterns. To study such phenomena, I develop a model that follows evolution on a surface representing adult phenotype as a function of underlying developmental characters. A contour on such a "phenotype landscape" is a set of states of developmental characters that produce the same adult phenotype. Epistasis induces curvature of this surface, and degree of canalization is represented by the slope along a contour. I first discuss the geometric properties of phenotype landscapes, relating epistasis to canalization. I then impose a fitness function on the phenotype and model evolution of developmental characters as a function of the fitness function and the local geometry of the surface. This model shows how canalization evolves as a population approaches an optimum phenotype. It further shows that under some circumstances, "decanalization" can occur, in which the expression of adult phenotype becomes increasingly sensitive to developmental variation. This process can cause very similar populations to diverge from one another developmentally even when their adult phenotypes experience identical selection regimes. © 1998 The Society for the Study of Evolution.

Robustness, evolvability, and the logic of genetic regulation.

PubMed

Payne, Joshua L; Moore, Jason H; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene's cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: For the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield identical gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, so that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype.

Robustness, Evolvability, and the Logic of Genetic Regulation

PubMed Central

Moore, Jason H.; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene’s cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: for the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield idential gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, such that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype. PMID:23373974

Female orgasm rates are largely independent of other traits: implications for "female orgasmic disorder" and evolutionary theories of orgasm.

PubMed

Zietsch, Brendan P; Miller, Geoffrey F; Bailey, J Michael; Martin, Nicholas G

2011-08-01

The criteria for "female orgasmic disorder" (FOD) assume that low rates of orgasm are dysfunctional, implying that high rates are functional. Evolutionary theories about the function of female orgasm predict correlations of orgasm rates with sexual attitudes and behavior and other fitness-related traits. To test hypothesized evolutionary functions of the female orgasm. We examined such correlations in a community sample of 2,914 adult female Australian twins who reported their orgasm rates during masturbation, intercourse, and other sexual activities, and who completed demographic, personality, and sexuality questionnaires. Orgasm rates during intercourse, other sex, and masturbation. Although orgasm rates showed high variance across women and substantial heritability, they were largely phenotypically and genetically independent of other important traits. We found zero to weak phenotypic correlations between all three orgasm rates and all other 19 traits examined, including occupational status, social class, educational attainment, extraversion, neuroticism, psychoticism, impulsiveness, childhood illness, maternal pregnancy stress, marital status, political liberalism, restrictive attitudes toward sex, libido, lifetime number of sex partners, risky sexual behavior, masculinity, orientation toward uncommitted sex, age of first intercourse, and sexual fantasy. Furthermore, none of the correlations had significant genetic components. These findings cast doubt on most current evolutionary theories about female orgasm's adaptive functions, and on the validity of FOD as a psychiatric construct. © 2011 International Society for Sexual Medicine.

The Metabolic Phenotype in Obesity: Fat Mass, Body Fat Distribution, and Adipose Tissue Function.

PubMed

Goossens, Gijs H

2017-01-01

The current obesity epidemic poses a major public health issue since obesity predisposes towards several chronic diseases. BMI and total adiposity are positively correlated with cardiometabolic disease risk at the population level. However, body fat distribution and an impaired adipose tissue function, rather than total fat mass, better predict insulin resistance and related complications at the individual level. Adipose tissue dysfunction is determined by an impaired adipose tissue expandability, adipocyte hypertrophy, altered lipid metabolism, and local inflammation. Recent human studies suggest that adipose tissue oxygenation may be a key factor herein. A subgroup of obese individuals - the 'metabolically healthy obese' (MHO) - have a better adipose tissue function, less ectopic fat storage, and are more insulin sensitive than obese metabolically unhealthy persons, emphasizing the central role of adipose tissue function in metabolic health. However, controversy has surrounded the idea that metabolically healthy obesity may be considered really healthy since MHO individuals are at increased (cardio)metabolic disease risk and may have a lower quality of life than normal weight subjects due to other comorbidities. Detailed metabolic phenotyping of obese persons will be invaluable in understanding the pathophysiology of metabolic disturbances, and is needed to identify high-risk individuals or subgroups, thereby paving the way for optimization of prevention and treatment strategies to combat cardiometabolic diseases. © 2017 The Author(s) Published by S. Karger GmbH, Freiburg.

Organs-on-chips at the frontiers of drug discovery

PubMed Central

Esch, Eric W.; Bahinski, Anthony; Huh, Dongeun

2016-01-01

Improving the effectiveness of preclinical predictions of human drug responses is critical to reducing costly failures in clinical trials. Recent advances in cell biology, microfabrication and microfluidics have enabled the development of microengineered models of the functional units of human organs — known as organs-on-chips — that could provide the basis for preclinical assays with greater predictive power. Here, we examine the new opportunities for the application of organ-on-chip technologies in a range of areas in preclinical drug discovery, such as target identification and validation, target-based screening, and phenotypic screening. We also discuss emerging drug discovery opportunities enabled by organs-on-chips, as well as important challenges in realizing the full potential of this technology. PMID:25792263

Targeting Metabolic Plasticity in Breast Cancer Cells via Mitochondrial Complex I Modulation

PubMed Central

Xu, Qijin; Biener-Ramanujan, Eva; Yang, Wei; Ramanujan, V Krishnan

2016-01-01

Purpose Heterogeneity commonly observed in clinical tumors stems both from the genetic diversity as well as from the differential metabolic adaptation of multiple cancer types during their struggle to maintain uncontrolled proliferation and invasion in vivo. This study aims to identify a potential metabolic window of such adaptation in aggressive human breast cancer cell lines. Methods With a multidisciplinary approach using high resolution imaging, cell metabolism assays, proteomic profiling and animal models of human tumor xenografts and via clinically-relevant, pharmacological approach for modulating mitochondrial complex I function in human breast cancer cell lines, we report a novel route to target metabolic plasticity in human breast cancer cells. Results By a systematic modulation of mitochondrial function and by mitigating metabolic switch phenotype in aggressive human breast cancer cells, we demonstrate that the resulting metabolic adaptation signatures can predictably decrease tumorigenic potential in vivo. Proteomic profiling of the metabolic adaptation in these cells further revealed novel protein-pathway interactograms highlighting the importance of antioxidant machinery in the observed metabolic adaptation. Conclusions Improved metabolic adaptation potential in aggressive human breast cancer cells contribute to improving mitochondrial function and reducing metabolic switch phenotype –which may be vital for targeting primary tumor growth in vivo. PMID:25677747

Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers.

PubMed

Lu, H-J; Bernardo, R; Ohm, H W

2003-02-01

Popping expansion volume is the most important quality trait in popcorn ( Zea mays L.), but its genetics is not well understood. The objectives of this study were to map quantitative trait loci (QTLs) responsible for popping expansion volume in a popcorn x dent corn cross, and to compare the predicted efficiencies of phenotypic selection, marker-based selection, and marker-assisted selection for popping expansion volume. Of 259 simple sequence repeat (SSR) primer pairs screened, 83 pairs were polymorphic between the H123 (dent corn) and AG19 (popcorn) parental inbreds. Popping test data were obtained for 160 S(1) families developed from the [AG19(H123 x AG19)] BC(1) population. The heritability ( h(2)) for popping expansion volume on an S(1) family mean basis was 0.73. The presence of the gametophyte factor Ga1(s) in popcorn complicates the analysis of popcorn x dent corn crosses. But, from a practical perspective, the linkage between a favorable QTL allele and Ga1(s) in popcorn will lead to selection for the favorable QTL allele. Four QTLs, on chromosomes 1S, 3S, 5S and 5L, jointly explained 45% of the phenotypic variation. Marker-based selection for popping expansion volume would require less time and work than phenotypic selection. But due to the high h(2) of popping expansion volume, marker-based selection was predicted to be only 92% as efficient as phenotypic selection. Marker-assisted selection, which comprises index selection on phenotypic and marker scores, was predicted to be 106% as efficient as phenotypic selection. Overall, our results suggest that phenotypic selection will remain the preferred method for selection in popcorn x dent corn crosses.

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

PubMed Central

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

2017-01-01

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. PMID:28272456

Pseudomonas fluorescens transportome is linked to strain-specific plant growth promotion in Aspen seedlings under nutrient stress

DOE PAGES

Shinde, Shalaka; Cumming, Jonathan R.; Collart, Frank R.; ...

2017-03-21

Diverse communities of bacteria colonize plant roots and the rhizosphere. Many of these rhizobacteria are symbionts and provide plant growth promotion (PGP) services, protecting the plant from biotic and abiotic stresses and increasing plant productivity by providing access to nutrients that would otherwise be unavailable to roots. In return, these symbiotic bacteria receive photosynthetically-derived carbon (C), in the form of sugars and organic acids, from plant root exudates. PGP activities have been characterized for a variety of forest tree species and are important in C cycling and sequestration in terrestrial ecosystems. The molecular mechanisms of these PGP activities, however, aremore » less well-known. In a previous analysis of Pseudomonas genomes, we found that the bacterial transportome, the aggregate activity of a bacteria's transmembrane transporters, was most predictive for the ecological niche of Pseudomonads in the rhizosphere. Here, we used Populus tremuloides Michx. (trembling aspen) seedlings inoculated with one of three Pseudomonas fluorescens strains (Pf0-1, SBW25, and WH6) and one Pseudomonas protegens (Pf-5) as a laboratory model to further investigate the relationships between the predicted transportomic capacity of a bacterial strain and its observed PGP effects in laboratory cultures. Conditions of low nitrogen (N) or low phosphorus (P) availability and the corresponding replete media conditions were investigated. We measured phenotypic and biochemical parameters of P. tremuloides seedlings and correlated P fluorescens strain-specific transportomic capacities with P. tremuloides seedling phenotype to predict the strain and nutrient environment-specific transporter functions that lead to experimentally observed, strain, and media-specific PGP activities and the capacity to protect plants against nutrient stress. These predicted transportomic functions fall in three groups: (i) transport of compounds that modulate aspen seedling root architecture, (ii) transport of compounds that help to mobilize nutrients for aspen roots, and (iii) transporters that enable bacterial acquisition of C sources from seedling root exudates. Lastly, these predictions point to specific molecular mechanisms of PGP activities that can be directly tested through future, hypothesis-driven biological experiments.« less

Pseudomonas fluorescens transportome is linked to strain-specific plant growth promotion in Aspen seedlings under nutrient stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shinde, Shalaka; Cumming, Jonathan R.; Collart, Frank R.

Diverse communities of bacteria colonize plant roots and the rhizosphere. Many of these rhizobacteria are symbionts and provide plant growth promotion (PGP) services, protecting the plant from biotic and abiotic stresses and increasing plant productivity by providing access to nutrients that would otherwise be unavailable to roots. In return, these symbiotic bacteria receive photosynthetically-derived carbon (C), in the form of sugars and organic acids, from plant root exudates. PGP activities have been characterized for a variety of forest tree species and are important in C cycling and sequestration in terrestrial ecosystems. The molecular mechanisms of these PGP activities, however, aremore » less well-known. In a previous analysis of Pseudomonas genomes, we found that the bacterial transportome, the aggregate activity of a bacteria's transmembrane transporters, was most predictive for the ecological niche of Pseudomonads in the rhizosphere. Here, we used Populus tremuloides Michx. (trembling aspen) seedlings inoculated with one of three Pseudomonas fluorescens strains (Pf0-1, SBW25, and WH6) and one Pseudomonas protegens (Pf-5) as a laboratory model to further investigate the relationships between the predicted transportomic capacity of a bacterial strain and its observed PGP effects in laboratory cultures. Conditions of low nitrogen (N) or low phosphorus (P) availability and the corresponding replete media conditions were investigated. We measured phenotypic and biochemical parameters of P. tremuloides seedlings and correlated P fluorescens strain-specific transportomic capacities with P. tremuloides seedling phenotype to predict the strain and nutrient environment-specific transporter functions that lead to experimentally observed, strain, and media-specific PGP activities and the capacity to protect plants against nutrient stress. These predicted transportomic functions fall in three groups: (i) transport of compounds that modulate aspen seedling root architecture, (ii) transport of compounds that help to mobilize nutrients for aspen roots, and (iii) transporters that enable bacterial acquisition of C sources from seedling root exudates. Lastly, these predictions point to specific molecular mechanisms of PGP activities that can be directly tested through future, hypothesis-driven biological experiments.« less

Phenotypic and genetic heterogeneity among subjects with mild airflow obstruction in COPDGene.

PubMed

Lee, Jin Hwa; Cho, Michael H; McDonald, Merry-Lynn N; Hersh, Craig P; Castaldi, Peter J; Crapo, James D; Wan, Emily S; Dy, Jennifer G; Chang, Yale; Regan, Elizabeth A; Hardin, Megan; DeMeo, Dawn L; Silverman, Edwin K

2014-10-01

Chronic obstructive pulmonary disease (COPD) is characterized by marked phenotypic heterogeneity. Most previous studies have focused on COPD subjects with FEV1 < 80% predicted. We investigated the clinical and genetic heterogeneity in subjects with mild airflow limitation in spirometry grade 1 defined by the Global Initiative for chronic Obstructive Lung Disease (GOLD 1). Data from current and former smokers participating in the COPDGene Study (NCT00608764) were analyzed. K-means clustering was performed to explore subtypes within 794 GOLD 1 subjects. For all subjects with GOLD 1 and with each cluster, a genome-wide association study and candidate gene testing were performed using smokers with normal lung function as a control group. Combinations of COPD genome-wide significant single nucleotide polymorphisms (SNPs) were tested for association with FEV1 (% predicted) in GOLD 1 and in a combined group of GOLD 1 and smoking control subjects. K-means clustering of GOLD 1 subjects identified putative "near-normal", "airway-predominant", "emphysema-predominant" and "lowest FEV1% predicted" subtypes. In non-Hispanic whites, the only SNP nominally associated with GOLD 1 status relative to smoking controls was rs7671167 (FAM13A) in logistic regression models with adjustment for age, sex, pack-years of smoking, and genetic ancestry. The emphysema-predominant GOLD 1 cluster was nominally associated with rs7671167 (FAM13A) and rs161976 (BICD1). The lowest FEV1% predicted cluster was nominally associated with rs1980057 (HHIP) and rs1051730 (CHRNA3). Combinations of COPD genome-wide significant SNPs were associated with FEV1 (% predicted) in a combined group of GOLD 1 and smoking control subjects. Our results indicate that GOLD 1 subjects show substantial clinical heterogeneity, which is at least partially related to genetic heterogeneity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Retrospective study of long-term outcomes of enzyme replacement therapy in Fabry disease: Analysis of prognostic factors

PubMed Central

Biegstraaten, Marieke; Hughes, Derralynn A.; Mehta, Atul; Elliott, Perry M.; Oder, Daniel; Watkinson, Oliver T.; Vaz, Frédéric M.; van Kuilenburg, André B. P.; Wanner, Christoph; Hollak, Carla E. M.

2017-01-01

Despite enzyme replacement therapy, disease progression is observed in patients with Fabry disease. Identification of factors that predict disease progression is needed to refine guidelines on initiation and cessation of enzyme replacement therapy. To study the association of potential biochemical and clinical prognostic factors with the disease course (clinical events, progression of cardiac and renal disease) we retrospectively evaluated 293 treated patients from three international centers of excellence. As expected, age, sex and phenotype were important predictors of event rate. Clinical events before enzyme replacement therapy, cardiac mass and eGFR at baseline predicted an increased event rate. eGFR was the most important predictor: hazard ratios increased from 2 at eGFR <90 ml/min/1.73m2 to 4 at eGFR <30, compared to patients with an eGFR >90. In addition, men with classical disease and a baseline eGFR <60 ml/min/1.73m2 had a faster yearly decline (-2.0 ml/min/1.73m2) than those with a baseline eGFR of >60. Proteinuria was a further independent risk factor for decline in eGFR. Increased cardiac mass at baseline was associated with the most robust decrease in cardiac mass during treatment, while presence of cardiac fibrosis predicted a stronger increase in cardiac mass (3.36 gram/m2/year). Of other cardiovascular risk factors, hypertension significantly predicted the risk for clinical events. In conclusion, besides increasing age, male sex and classical phenotype, faster disease progression while on enzyme replacement therapy is predicted by renal function, proteinuria and to a lesser extent cardiac fibrosis and hypertension. PMID:28763515

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Plastic Responses of a Sessile Prey to Multiple Predators: A Field and Experimental Study

PubMed Central

Hirsch, Philipp Emanuel; Cayon, David; Svanbäck, Richard

2014-01-01

Background Theory predicts that prey facing a combination of predators with different feeding modes have two options: to express a response against the feeding mode of the most dangerous predator, or to express an intermediate response. Intermediate phenotypes protect equally well against several feeding modes, rather than providing specific protection against a single predator. Anti-predator traits that protect against a common feeding mode displayed by all predators should be expressed regardless of predator combination, as there is no need for trade-offs. Principal Findings We studied phenotypic anti-predator responses of zebra mussels to predation threat from a handling-time-limited (crayfish) and a gape-size-limited (roach) predator. Both predators dislodge mussels from the substrate but diverge in their further feeding modes. Mussels increased expression of a non-specific defense trait (attachment strength) against all combinations of predators relative to a control. In response to roach alone, mussels showed a tendency to develop a weaker and more elongated shell. In response to crayfish, mussels developed a harder and rounder shell. When exposed to either a combination of predators or no predator, mussels developed an intermediate phenotype. Mussel growth rate was positively correlated with an elongated weaker shell and negatively correlated with a round strong shell, indicating a trade-off between anti-predator responses. Field observations of prey phenotypes revealed the presence of both anti-predator phenotypes and the trade-off with growth, but intra-specific population density and bottom substrate had a greater influence than predator density. Conclusions Our results show that two different predators can exert both functionally equivalent and inverse selection pressures on a single prey. Our field study suggests that abiotic factors and prey population density should be considered when attempting to explain phenotypic diversity in the wild. PMID:25517986

Volatile organic compounds as non-invasive markers for plant phenotyping.

PubMed

Niederbacher, B; Winkler, J B; Schnitzler, J P

2015-09-01

Plants emit a great variety of volatile organic compounds (VOCs) that can actively participate in plant growth and protection against biotic and abiotic stresses. VOC emissions are strongly dependent on environmental conditions; the greatest ambiguity is whether or not the predicted change in climate will influence and modify plant-pest interactions that are mediated by VOCs. The constitutive and induced emission patterns between plant genotypes, species, and taxa are highly variable and can be used as pheno(chemo)typic markers to distinguish between different origins and provenances. In recent years significant progress has been made in molecular and genetic plant breeding. However, there is actually a lack of knowledge in functionally linking genotypes and phenotypes, particularly in analyses of plant-environment interactions. Plant phenotyping, the assessment of complex plant traits such as growth, development, tolerance, resistance, etc., has become a major bottleneck, and quantitative information on genotype-environment relationships is the key to addressing major future challenges. With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to measure accurately increasingly large numbers of plants and plant traits. In this review article, we focus on the promising outlook of VOC phenotyping as a fast and non-invasive measure of phenotypic dynamics. The basic principle is to define plant phenotypes according to their disease resistance and stress tolerance, which in turn will help in improving the performance and yield of economically relevant plants. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Predicting network modules of cell cycle regulators using relative protein abundance statistics.

PubMed

Oguz, Cihan; Watson, Layne T; Baumann, William T; Tyson, John J

2017-02-28

Parameter estimation in systems biology is typically done by enforcing experimental observations through an objective function as the parameter space of a model is explored by numerical simulations. Past studies have shown that one usually finds a set of "feasible" parameter vectors that fit the available experimental data equally well, and that these alternative vectors can make different predictions under novel experimental conditions. In this study, we characterize the feasible region of a complex model of the budding yeast cell cycle under a large set of discrete experimental constraints in order to test whether the statistical features of relative protein abundance predictions are influenced by the topology of the cell cycle regulatory network. Using differential evolution, we generate an ensemble of feasible parameter vectors that reproduce the phenotypes (viable or inviable) of wild-type yeast cells and 110 mutant strains. We use this ensemble to predict the phenotypes of 129 mutant strains for which experimental data is not available. We identify 86 novel mutants that are predicted to be viable and then rank the cell cycle proteins in terms of their contributions to cumulative variability of relative protein abundance predictions. Proteins involved in "regulation of cell size" and "regulation of G1/S transition" contribute most to predictive variability, whereas proteins involved in "positive regulation of transcription involved in exit from mitosis," "mitotic spindle assembly checkpoint" and "negative regulation of cyclin-dependent protein kinase by cyclin degradation" contribute the least. These results suggest that the statistics of these predictions may be generating patterns specific to individual network modules (START, S/G2/M, and EXIT). To test this hypothesis, we develop random forest models for predicting the network modules of cell cycle regulators using relative abundance statistics as model inputs. Predictive performance is assessed by the areas under receiver operating characteristics curves (AUC). Our models generate an AUC range of 0.83-0.87 as opposed to randomized models with AUC values around 0.50. By using differential evolution and random forest modeling, we show that the model prediction statistics generate distinct network module-specific patterns within the cell cycle network.

RARGE II: an integrated phenotype database of Arabidopsis mutant traits using a controlled vocabulary.

PubMed

Akiyama, Kenji; Kurotani, Atsushi; Iida, Kei; Kuromori, Takashi; Shinozaki, Kazuo; Sakurai, Tetsuya

2014-01-01

Arabidopsis thaliana is one of the most popular experimental plants. However, only 40% of its genes have at least one experimental Gene Ontology (GO) annotation assigned. Systematic observation of mutant phenotypes is an important technique for elucidating gene functions. Indeed, several large-scale phenotypic analyses have been performed and have generated phenotypic data sets from many Arabidopsis mutant lines and overexpressing lines, which are freely available online. Since each Arabidopsis mutant line database uses individual phenotype expression, the differences in the structured term sets used by each database make it difficult to compare data sets and make it impossible to search across databases. Therefore, we obtained publicly available information for a total of 66,209 Arabidopsis mutant lines, including loss-of-function (RATM and TARAPPER) and gain-of-function (AtFOX and OsFOX) lines, and integrated the phenotype data by mapping the descriptions onto Plant Ontology (PO) and Phenotypic Quality Ontology (PATO) terms. This approach made it possible to manage the four different phenotype databases as one large data set. Here, we report a publicly accessible web-based database, the RIKEN Arabidopsis Genome Encyclopedia II (RARGE II; http://rarge-v2.psc.riken.jp/), in which all of the data described in this study are included. Using the database, we demonstrated consistency (in terms of protein function) with a previous study and identified the presumed function of an unknown gene. We provide examples of AT1G21600, which is a subunit in the plastid-encoded RNA polymerase complex, and AT5G56980, which is related to the jasmonic acid signaling pathway.

Genome-environment associations in sorghum landraces predict adaptive traits

PubMed Central

Lasky, Jesse R.; Upadhyaya, Hari D.; Ramu, Punna; Deshpande, Santosh; Hash, C. Tom; Bonnette, Jason; Juenger, Thomas E.; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E.; Buckler, Edward S.; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P.

2015-01-01

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

Aging and autism spectrum disorder: Evidence from the broad autism phenotype.

PubMed

Wallace, Gregory L; Budgett, Jessica; Charlton, Rebecca A

2016-12-01

This study investigated for the first time the broad autism phenotype (BAP) in the context of older adulthood and its associations with real-world executive function, social support, and both depression and anxiety symptomatology. Based on self-ratings of autistic traits, 66 older adults (60+ years old, range = 61-88) were split into BAP (n = 20) and control (n = 46) groups. Individuals in the BAP group, even after controlling for age, education level, sex, and health problems, exhibited more real-world executive function problems in multiple domains, reported lower levels of social support, and self-rated increased depression and anxiety symptomatology compared to the control group. Regression analysis revealed that level of social support was the strongest predictor of BAP traits across both groups, although real-world executive function problems and depression symptomatology were also significant predictors. Moreover, when predicting anxiety and depression symptomatology, BAP traits were the strongest predictors above and beyond the effects of demographic factors, real-world executive function problems, and social support levels. These findings suggest that the BAP in older adulthood imparts additional risks to areas of functioning that are known to be crucial to aging-related outcomes in the context of typical development. These results might in turn inform aging in autism spectrum disorder, which has been largely unexplored to date. Autism Res 2016, 9: 1294-1303. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

GenomeRNAi: a database for cell-based RNAi phenotypes.

PubMed

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.

GenomeRNAi: a database for cell-based RNAi phenotypes

PubMed Central

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 PMID:17135194

Chaos and unpredictability in evolution.

PubMed

Doebeli, Michael; Ispolatov, Iaroslav

2014-05-01

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long-term evolutionary chaos is rarely considered. The concept of "survival of the fittest" is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency-independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency-dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency-dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long-term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long-term evolution. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

A second component of the SltA-dependent cation tolerance pathway in Aspergillus nidulans.

PubMed

Mellado, Laura; Calcagno-Pizarelli, Ana Maria; Lockington, Robin A; Cortese, Marc S; Kelly, Joan M; Arst, Herbert N; Espeso, Eduardo A

2015-09-01

The transcriptional response to alkali metal cation stress is mediated by the zinc finger transcription factor SltA in Aspergillus nidulans and probably in other fungi of the pezizomycotina subphylum. A second component of this pathway has been identified and characterized. SltB is a 1272 amino acid protein with at least two putative functional domains, a pseudo-kinase and a serine-endoprotease, involved in signaling to the transcription factor SltA. Absence of SltB activity results in nearly identical phenotypes to those observed for a null sltA mutant. Hypersensitivity to a variety of monovalent and divalent cations, and to medium alkalinization are among the phenotypes exhibited by a null sltB mutant. Calcium homeostasis is an exception and this cation improves growth of sltΔ mutants. Moreover, loss of kinase HalA in conjunction with loss-of-function sltA or sltB mutations leads to pronounced calcium auxotrophy. sltA sltB double null mutants display a cation stress sensitive phenotype indistinguishable from that of single slt mutants showing the close functional relationship between these two proteins. This functional relationship is reinforced by the fact that numerous mutations in both slt loci can be isolated as suppressors of poor colonial growth resulting from certain null vps (vacuolar protein sorting) mutations. In addition to allowing identification of sltB, our sltB missense mutations enabled prediction of functional regions in the SltB protein. Although the relationship between the Slt and Vps pathways remains enigmatic, absence of SltB, like that of SltA, leads to vacuolar hypertrophy. Importantly, the phenotypes of selected sltA and sltB mutations demonstrate that suppression of null vps mutations is not dependent on the inability to tolerate cation stress. Thus a specific role for both SltA and SltB in the VPS pathway seems likely. Finally, it is noteworthy that SltA and SltB have a similar, limited phylogenetic distribution, being restricted to the pezizomycotina subphylum. The relevance of the Slt regulatory pathway to cell structure, intracellular trafficking and cation homeostasis and its restricted phylogenetic distribution makes this pathway of general interest for future investigation and as a source of targets for antifungal drugs. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults

PubMed Central

Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K.; Thomas, Venetta; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J.; Cheng, Iona; Chu, Lisa; Deming, Sandra L.; Driver, W. Ryan; Goodman, Phyllis; Hayes, Richard B.; Hennis, Anselm J. M.; Hsing, Ann W.; Hu, Jennifer J.; Ingles, Sue A.; John, Esther M.; Kittles, Rick A.; Kolb, Suzanne; Leske, M. Cristina; Monroe, Kristine R.; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F.; Rodriguez-Gil, Jorge L.; Rybicki, Ben A.; Schumacher, Fredrick; Stanford, Janet L.; Signorello, Lisa B.; Strom, Sara S.; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S.; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G.; Stram, Alexander H.; Kolonel, Laurence N.; Marchand, Loïc Le; Henderson, Brian E.; Haiman, Christopher A.; Stram, Daniel O.

2015-01-01

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious. PMID:26125186

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults.

PubMed

Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K; Thomas, Venetta; Ambrosone, Christine B; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J; Cheng, Iona; Chu, Lisa; Deming, Sandra L; Driver, W Ryan; Goodman, Phyllis; Hayes, Richard B; Hennis, Anselm J M; Hsing, Ann W; Hu, Jennifer J; Ingles, Sue A; John, Esther M; Kittles, Rick A; Kolb, Suzanne; Leske, M Cristina; Millikan, Robert C; Monroe, Kristine R; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Ben A; Schumacher, Fredrick; Stanford, Janet L; Signorello, Lisa B; Strom, Sara S; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G; Stram, Alexander H; Kolonel, Laurence N; Le Marchand, Loïc; Henderson, Brian E; Haiman, Christopher A; Stram, Daniel O

2015-01-01

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.

Comparative functional pan-genome analyses to build connections between genomic dynamics and phenotypic evolution in polycyclic aromatic hydrocarbon metabolism in the genus Mycobacterium.

PubMed

Kweon, Ohgew; Kim, Seong-Jae; Blom, Jochen; Kim, Sung-Kwan; Kim, Bong-Soo; Baek, Dong-Heon; Park, Su Inn; Sutherland, John B; Cerniglia, Carl E

2015-02-14

The bacterial genus Mycobacterium is of great interest in the medical and biotechnological fields. Despite a flood of genome sequencing and functional genomics data, significant gaps in knowledge between genome and phenome seriously hinder efforts toward the treatment of mycobacterial diseases and practical biotechnological applications. In this study, we propose the use of systematic, comparative functional pan-genomic analysis to build connections between genomic dynamics and phenotypic evolution in polycyclic aromatic hydrocarbon (PAH) metabolism in the genus Mycobacterium. Phylogenetic, phenotypic, and genomic information for 27 completely genome-sequenced mycobacteria was systematically integrated to reconstruct a mycobacterial phenotype network (MPN) with a pan-genomic concept at a network level. In the MPN, mycobacterial phenotypes show typical scale-free relationships. PAH degradation is an isolated phenotype with the lowest connection degree, consistent with phylogenetic and environmental isolation of PAH degraders. A series of functional pan-genomic analyses provide conserved and unique types of genomic evidence for strong epistatic and pleiotropic impacts on evolutionary trajectories of the PAH-degrading phenotype. Under strong natural selection, the detailed gene gain/loss patterns from horizontal gene transfer (HGT)/deletion events hypothesize a plausible evolutionary path, an epistasis-based birth and pleiotropy-dependent death, for PAH metabolism in the genus Mycobacterium. This study generated a practical mycobacterial compendium of phenotypic and genomic changes, focusing on the PAH-degrading phenotype, with a pan-genomic perspective of the evolutionary events and the environmental challenges. Our findings suggest that when selection acts on PAH metabolism, only a small fraction of possible trajectories is likely to be observed, owing mainly to a combination of the ambiguous phenotypic effects of PAHs and the corresponding pleiotropy- and epistasis-dependent evolutionary adaptation. Evolutionary constraints on the selection of trajectories, like those seen in PAH-degrading phenotypes, are likely to apply to the evolution of other phenotypes in the genus Mycobacterium.

Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

PubMed

Uhl, Elizabeth W; Warner, Natalie J

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

PREDICT-CP: study protocol of implementation of comprehensive surveillance to predict outcomes for school-aged children with cerebral palsy.

PubMed

Boyd, Roslyn N; Davies, Peter Sw; Ziviani, Jenny; Trost, Stewart; Barber, Lee; Ware, Robert; Rose, Stephen; Whittingham, Koa; Sakzewski, Leanne; Bell, Kristie; Carty, Christopher; Obst, Steven; Benfer, Katherine; Reedman, Sarah; Edwards, Priya; Kentish, Megan; Copeland, Lisa; Weir, Kelly; Davenport, Camilla; Brooks, Denise; Coulthard, Alan; Pelekanos, Rebecca; Guzzetta, Andrea; Fiori, Simona; Wynter, Meredith; Finn, Christine; Burgess, Andrea; Morris, Kym; Walsh, John; Lloyd, Owen; Whitty, Jennifer A; Scuffham, Paul A

2017-07-12

Cerebral palsy (CP) remains the world's most common childhood physical disability with total annual costs of care and lost well-being of $A3.87b. The PREDICT-CP (NHMRC 1077257 Partnership Project: Comprehensive surveillance to PREDICT outcomes for school age children with CP) study will investigate the influence of brain structure, body composition, dietary intake, oropharyngeal function, habitual physical activity, musculoskeletal development (hip status, bone health) and muscle performance on motor attainment, cognition, executive function, communication, participation, quality of life and related health resource use costs. The PREDICT-CP cohort provides further follow-up at 8-12 years of two overlapping preschool-age cohorts examined from 1.5 to 5 years (NHMRC 465128 motor and brain development; NHMRC 569605 growth, nutrition and physical activity). This population-based cohort study undertakes state-wide surveillance of 245 children with CP born in Queensland (birth years 2006-2009). Children will be classified for Gross Motor Function Classification System; Manual Ability Classification System, Communication Function Classification System and Eating and Drinking Ability Classification System. Outcomes include gross motor function, musculoskeletal development (hip displacement, spasticity, muscle contracture), upper limb function, communication difficulties, oropharyngeal dysphagia, dietary intake and body composition, participation, parent-reported and child-reported quality of life and medical and allied health resource use. These detailed phenotypical data will be compared with brain macrostructure and microstructure using 3 Tesla MRI (3T MRI). Relationships between brain lesion severity and outcomes will be analysed using multilevel mixed-effects models. The PREDICT-CP protocol is a prospectively registered and ethically accepted study protocol. The study combines data at 1.5-5 then 8-12 years of direct clinical assessment to enable prediction of outcomes and healthcare needs essential for tailoring interventions (eg, rehabilitation, orthopaedic surgery and nutritional supplements) and the projected healthcare utilisation. ACTRN: 12616001488493. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Evolution of increased phenotypic diversity enhances population performance by reducing sexual harassment in damselflies.

PubMed

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.

Cytochrome P450 2D6 variants in a Caucasian population: Allele frequencies and phenotypic consequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sachse, C.; Brockmoeller, J.; Bauer, S.

Cytochrome P450 2D6 (CYP2D6) metabolizes many important drugs. CYP2D6 activity ranges from complete deficiency to ultrafast metabolism, depending on at least 16 different known alleles. Their frequencies were determined in 589 unrelated German volunteers and correlated with enzyme activity measured by phenotyping with dextromethorphan or debrisoquine. For genotyping, nested PCR-RFLP tests from a PCR amplificate of the entire CYP2D6 gene were developed. The frequency of the CYP2D6*1 allele coding for extensive metabolizer (EM) phenotype was .364. The alleles coding for slightly (CYP2D6*2) or moderately (*9 and *10) reduced activity (intermediate metabolizer phenotype [IM]) showed frequencies of .324, .018, and .015,more » respectively. By use of novel PCR tests for discrimination, CYP2D6 gene duplication alleles were found with frequencies of.005 (*1 x 2), .013 (* 2 x 2), and .001 (*4 x 2). Frequencies of alleles with complete deficiency (poor metabolizer phenotype [PM]) were .207 (*4), .020 (*3 and *5), .009 (*6), and .001 (*7, *15, and *16). The defective CYP2D6 alleles *8, *11, *12, *13, and *14 were not found. All 41 PMs (7.0%) in this sample were explained by five mutations detected by four PCR-RFLP tests, which may suffice, together with the gene duplication test, for clinical prediction of CYP2D6 capacity. Three novel variants of known CYP2D6 alleles were discovered: *1C (T{sub 1957}C), *2B (additional C{sub 2558}T), and *4E (additional C{sub 2938}T). Analysis of variance showed significant differences in enzymatic activity measured by the dextromethorphan metabolic ratio (MR) between carriers of EN/PM (mean MR = .006) and IM/PM (mean MR = .014) alleles and between carriers of one (mean MR = .009) and two (mean MR = .003) functional alleles. The results of this study provide a solid basis for prediction of CYP2D6 capacity, as required in drug research and routine drug treatment. 35 refs., 4 figs., 5 tabs.« less

Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism

PubMed Central

Chang, Roger L; Ghamsari, Lila; Manichaikul, Ani; Hom, Erik F Y; Balaji, Santhanam; Fu, Weiqi; Shen, Yun; Hao, Tong; Palsson, Bernhard Ø; Salehi-Ashtiani, Kourosh; Papin, Jason A

2011-01-01

Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. PMID:21811229

Predictors of facial attractiveness and health in humans.

PubMed

Foo, Yong Zhi; Simmons, Leigh W; Rhodes, Gillian

2017-02-03

Facial attractiveness has been suggested to provide signals of biological quality, particularly health, in humans. The attractive traits that have been implicated as signals of biological quality include sexual dimorphism, symmetry, averageness, adiposity, and carotenoid-based skin colour. In this study, we first provide a comprehensive examination of the traits that predict attractiveness. In men, attractiveness was predicted positively by masculinity, symmetry, averageness, and negatively by adiposity. In women, attractiveness was predicted positively by femininity and negatively by adiposity. Skin colour did not predict attractiveness in either sex, suggesting that, despite recent interest in the literature, colour may play limited role in determining attractiveness. Male perceived health was predicted positively by averageness, symmetry, and skin yellowness, and negatively by adiposity. Female perceived health was predicted by femininity. We then examined whether appearance predicted actual health using measures that have been theoretically linked to sexual selection, including immune function, oxidative stress, and semen quality. In women, there was little evidence that female appearance predicted health. In men, we found support for the phenotype-linked fertility hypothesis that male masculinity signalled semen quality. However, we also found a negative relationship between averageness and semen quality. Overall, these results indicate weak links between attractive facial traits and health.

Predictors of facial attractiveness and health in humans

PubMed Central

Foo, Yong Zhi; Simmons, Leigh W.; Rhodes, Gillian

2017-01-01

Facial attractiveness has been suggested to provide signals of biological quality, particularly health, in humans. The attractive traits that have been implicated as signals of biological quality include sexual dimorphism, symmetry, averageness, adiposity, and carotenoid-based skin colour. In this study, we first provide a comprehensive examination of the traits that predict attractiveness. In men, attractiveness was predicted positively by masculinity, symmetry, averageness, and negatively by adiposity. In women, attractiveness was predicted positively by femininity and negatively by adiposity. Skin colour did not predict attractiveness in either sex, suggesting that, despite recent interest in the literature, colour may play limited role in determining attractiveness. Male perceived health was predicted positively by averageness, symmetry, and skin yellowness, and negatively by adiposity. Female perceived health was predicted by femininity. We then examined whether appearance predicted actual health using measures that have been theoretically linked to sexual selection, including immune function, oxidative stress, and semen quality. In women, there was little evidence that female appearance predicted health. In men, we found support for the phenotype-linked fertility hypothesis that male masculinity signalled semen quality. However, we also found a negative relationship between averageness and semen quality. Overall, these results indicate weak links between attractive facial traits and health. PMID:28155897

Oncogenes induce the cancer-associated fibroblast phenotype

PubMed Central

Lisanti, Michael P; Martinez-Outschoorn, Ubaldo E; Sotgia, Federica

2013-01-01

Metabolic coupling, between mitochondria in cancer cells and catabolism in stromal fibroblasts, promotes tumor growth, recurrence, metastasis, and predicts anticancer drug resistance. Catabolic fibroblasts donate the necessary fuels (such as L-lactate, ketones, glutamine, other amino acids, and fatty acids) to anabolic cancer cells, to metabolize via their TCA cycle and oxidative phosphorylation (OXPHOS). This provides a simple mechanism by which metabolic energy and biomass are transferred from the host microenvironment to cancer cells. Recently, we showed that catabolic metabolism and “glycolytic reprogramming” in the tumor microenvironment are orchestrated by oncogene activation and inflammation, which originates in epithelial cancer cells. Oncogenes drive the onset of the cancer-associated fibroblast phenotype in adjacent normal fibroblasts via paracrine oxidative stress. This oncogene-induced transition to malignancy is “mirrored” by a loss of caveolin-1 (Cav-1) and an increase in MCT4 in adjacent stromal fibroblasts, functionally reflecting catabolic metabolism in the tumor microenvironment. Virtually identical findings were obtained using BRCA1-deficient breast and ovarian cancer cells. Thus, oncogene activation (RAS, NFkB, TGF-β) and/or tumor suppressor loss (BRCA1) have similar functional effects on adjacent stromal fibroblasts, initiating “metabolic symbiosis” and the cancer-associated fibroblast phenotype. New therapeutic strategies that metabolically uncouple oxidative cancer cells from their glycolytic stroma or modulate oxidative stress could be used to target this lethal subtype of cancers. Targeting “fibroblast addiction” in primary and metastatic tumor cells may expose a critical Achilles’ heel, leading to disease regression in both sporadic and familial cancers. PMID:23860382

Pathogenic variants in E3 ubiquitin ligase RLIM/RNF12 lead to a syndromic X-linked intellectual disability and behavior disorder.

PubMed

Frints, Suzanna G M; Ozanturk, Aysegul; Rodríguez Criado, Germán; Grasshoff, Ute; de Hoon, Bas; Field, Michael; Manouvrier-Hanu, Sylvie; E Hickey, Scott; Kammoun, Molka; Gripp, Karen W; Bauer, Claudia; Schroeder, Christopher; Toutain, Annick; Mihalic Mosher, Theresa; Kelly, Benjamin J; White, Peter; Dufke, Andreas; Rentmeester, Eveline; Moon, Sungjin; Koboldt, Daniel C; van Roozendaal, Kees E P; Hu, Hao; Haas, Stefan A; Ropers, Hans-Hilger; Murray, Lucinda; Haan, Eric; Shaw, Marie; Carroll, Renee; Friend, Kathryn; Liebelt, Jan; Hobson, Lynne; De Rademaeker, Marjan; Geraedts, Joep; Fryns, Jean-Pierre; Vermeesch, Joris; Raynaud, Martine; Riess, Olaf; Gribnau, Joost; Katsanis, Nicholas; Devriendt, Koen; Bauer, Peter; Gecz, Jozef; Golzio, Christelle; Gontan, Cristina; Kalscheuer, Vera M

2018-05-04

RLIM, also known as RNF12, is an X-linked E3 ubiquitin ligase acting as a negative regulator of LIM-domain containing transcription factors and participates in X-chromosome inactivation (XCI) in mice. We report the genetic and clinical findings of 84 individuals from nine unrelated families, eight of whom who have pathogenic variants in RLIM (RING finger LIM domain-interacting protein). A total of 40 affected males have X-linked intellectual disability (XLID) and variable behavioral anomalies with or without congenital malformations. In contrast, 44 heterozygous female carriers have normal cognition and behavior, but eight showed mild physical features. All RLIM variants identified are missense changes co-segregating with the phenotype and predicted to affect protein function. Eight of the nine altered amino acids are conserved and lie either within a domain essential for binding interacting proteins or in the C-terminal RING finger catalytic domain. In vitro experiments revealed that these amino acid changes in the RLIM RING finger impaired RLIM ubiquitin ligase activity. In vivo experiments in rlim mutant zebrafish showed that wild type RLIM rescued the zebrafish rlim phenotype, whereas the patient-specific missense RLIM variants failed to rescue the phenotype and thus represent likely severe loss-of-function mutations. In summary, we identified a spectrum of RLIM missense variants causing syndromic XLID and affecting the ubiquitin ligase activity of RLIM, suggesting that enzymatic activity of RLIM is required for normal development, cognition and behavior.

Chromatin organization as an indicator of glucocorticoid induced natural killer cell dysfunction.

PubMed

Misale, Michael S; Witek Janusek, Linda; Tell, Dina; Mathews, Herbert L

2018-01-01

It is well-established that psychological distress reduces natural killer cell immune function and that this reduction can be due to the stress-induced release of glucocorticoids. Glucocorticoids are known to alter epigenetic marks associated with immune effector loci, and are also known to influence chromatin organization. The purpose of this investigation was to assess the effect of glucocorticoids on natural killer cell chromatin organization and to determine the relationship of chromatin organization to natural killer cell effector function, e.g. interferon gamma production. Interferon gamma production is the prototypic cytokine produced by natural killer cells and is known to modulate both innate and adaptive immunity. Glucocorticoid treatment of human peripheral blood mononuclear cells resulted in a significant reduction in interferon gamma production. Glucocorticoid treatment also resulted in a demonstrable natural killer cell nuclear phenotype. This phenotype was localization of the histone, post-translational epigenetic mark, H3K27me3, to the nuclear periphery. Peripheral nuclear localization of H3K27me3 was directly related to cellular levels of interferon gamma. This nuclear phenotype was determined by direct visual inspection and by use of an automated, high through-put technology, the Amnis ImageStream. This technology combines the per-cell information content provided by standard microscopy with the statistical significance afforded by large sample sizes common to standard flow cytometry. Most importantly, this technology provides for a direct assessment of the localization of signal intensity within individual cells. The results demonstrate glucocorticoids to dysregulate natural killer cell function at least in part through altered H3K27me3 nuclear organization and demonstrate H3K27me3 chromatin organization to be a predictive indicator of glucocorticoid induced immune dysregulation of natural killer cells. Copyright © 2017 Elsevier Inc. All rights reserved.

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

PubMed Central

SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

2016-01-01

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

Functional relationships between plasmids and their significance for metabolism and symbiotic performance of Rhizobium leguminosarum bv. trifolii.

PubMed

Stasiak, Grażyna; Mazur, Andrzej; Wielbo, Jerzy; Marczak, Małgorzata; Zebracki, Kamil; Koper, Piotr; Skorupska, Anna

2014-11-01

Rhizobium leguminosarum bv. trifolii TA1 (RtTA1) is a soil bacterium establishing a highly specific symbiotic relationship with clover, which is based on the exchange of molecular signals between the host plant and the microsymbiont. The RtTA1 genome is large and multipartite, composed of a chromosome and four plasmids, which comprise approximately 65 % and 35 % of the total genome, respectively. Extrachromosomal replicons were previously shown to confer significant metabolic versatility to bacteria, which is important for their adaptation in the soil and nodulation competitiveness. To investigate the contribution of individual RtTA1 plasmids to the overall cell phenotype, metabolic properties and symbiotic performance, a transposon-based elimination strategy was employed. RtTA1 derivatives cured of pRleTA1b or pRleTA1d and deleted in pRleTA1a were obtained. In contrast to the in silico predictions of pRleTA1b and pRleTA1d, which were described as chromid-like replicons, both appeared to be completely curable. On the other hand, for pRleTA1a (symbiotic plasmid) and pRleTA1c, which were proposed to be unessential for RtTA1 viability, it was not possible to eliminate them at all (pRleTA1c) or entirely (pRleTA1a). Analyses of the phenotypic traits of the RtTA1 derivatives obtained revealed the functional significance of individual plasmids and their indispensability for growth, certain metabolic pathways, production of surface polysaccharides, autoaggregation, biofilm formation, motility and symbiotic performance. Moreover, the results allow us to suggest broad functional cooperation among the plasmids in shaping the phenotypic properties and symbiotic capabilities of rhizobia.

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

PubMed

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.

Morphological change and phenotypic plasticity in native and non-native pumpkinseed sunfish in response to competition.

PubMed

Yavno, Stan; Rooke, Anna C; Fox, Michael G

2014-06-01

Non-indigenous species are oftentimes exposed to ecosystems with unfamiliar species, and organisms that exhibit a high degree of phenotypic plasticity may be better able to contend with the novel competitors that they may encounter during range expansion. In this study, differences in morphological plasticity were investigated using young-of-year pumpkinseed sunfish (Lepomis gibbosus) from native North American and non-native European populations. Two Canadian populations, isolated from bluegill sunfish (L. macrochirus) since the last glaciation, and two Spanish populations, isolated from bluegill since their introduction in Europe, were reared in a common environment using artificial enclosures. Fish were subjected to allopatric (without bluegill) or sympatric (with bluegill) conditions, and differences in plasticity were tested through a MANOVA of discriminant function scores. All pumpkinseed populations exhibited dietary shifts towards more benthivorous prey when held with bluegill. Differences between North American and European populations were observed in body dimensions, gill raker length and pelvic fin position. Sympatric treatments induced an increase in body width and a decrease in caudal peduncle length in native fish; non-native fish exhibited longer caudal peduncle lengths when held in sympatry with bluegill. Overall, phenotypic plasticity influenced morphological divergence less than genetic factors, regardless of population. Contrary to predictions, pumpkinseeds from Europe exhibited lower levels of phenotypic plasticity than Canadian populations, suggesting that European pumpkinseeds are more canalized than their North American counterparts.

Morphological change and phenotypic plasticity in native and non-native pumpkinseed sunfish in response to competition

NASA Astrophysics Data System (ADS)

Yavno, Stan; Rooke, Anna C.; Fox, Michael G.

2014-06-01

Non-indigenous species are oftentimes exposed to ecosystems with unfamiliar species, and organisms that exhibit a high degree of phenotypic plasticity may be better able to contend with the novel competitors that they may encounter during range expansion. In this study, differences in morphological plasticity were investigated using young-of-year pumpkinseed sunfish ( Lepomis gibbosus) from native North American and non-native European populations. Two Canadian populations, isolated from bluegill sunfish ( L. macrochirus) since the last glaciation, and two Spanish populations, isolated from bluegill since their introduction in Europe, were reared in a common environment using artificial enclosures. Fish were subjected to allopatric (without bluegill) or sympatric (with bluegill) conditions, and differences in plasticity were tested through a MANOVA of discriminant function scores. All pumpkinseed populations exhibited dietary shifts towards more benthivorous prey when held with bluegill. Differences between North American and European populations were observed in body dimensions, gill raker length and pelvic fin position. Sympatric treatments induced an increase in body width and a decrease in caudal peduncle length in native fish; non-native fish exhibited longer caudal peduncle lengths when held in sympatry with bluegill. Overall, phenotypic plasticity influenced morphological divergence less than genetic factors, regardless of population. Contrary to predictions, pumpkinseeds from Europe exhibited lower levels of phenotypic plasticity than Canadian populations, suggesting that European pumpkinseeds are more canalized than their North American counterparts.

Experimental validation of a predicted feedback loop in the multi-oscillator clock of Arabidopsis thaliana

PubMed Central

Locke, James C W; Kozma-Bognár, László; Gould, Peter D; Fehér, Balázs; Kevei, Éva; Nagy, Ferenc; Turner, Matthew S; Hall, Anthony; Millar, Andrew J

2006-01-01

Our computational model of the circadian clock comprised the feedback loop between LATE ELONGATED HYPOCOTYL (LHY), CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and TIMING OF CAB EXPRESSION 1 (TOC1), and a predicted, interlocking feedback loop involving TOC1 and a hypothetical component Y. Experiments based on model predictions suggested GIGANTEA (GI) as a candidate for Y. We now extend the model to include a recently demonstrated feedback loop between the TOC1 homologues PSEUDO-RESPONSE REGULATOR 7 (PRR7), PRR9 and LHY and CCA1. This three-loop network explains the rhythmic phenotype of toc1 mutant alleles. Model predictions fit closely to new data on the gi;lhy;cca1 mutant, which confirm that GI is a major contributor to Y function. Analysis of the three-loop network suggests that the plant clock consists of morning and evening oscillators, coupled intracellularly, which may be analogous to coupled, morning and evening clock cells in Drosophila and the mouse. PMID:17102804

A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN).

PubMed

Afshar, Majid; Press, Valerie G; Robison, Rachel G; Kho, Abel N; Bandi, Sindhura; Biswas, Ashvini; Avila, Pedro C; Kumar, Harsha Vardhan Madan; Yu, Byung; Naureckas, Edward T; Nyenhuis, Sharmilee M; Codispoti, Christopher D

2017-10-13

Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93-0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

Metabolomic analysis of insulin resistance across different mouse strains and diets.

PubMed

Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

2017-11-24

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

Platform for combined analysis of functional and biomolecular phenotypes of the same cell.

PubMed

Kelbauskas, L; Ashili, S; Zeng, J; Rezaie, A; Lee, K; Derkach, D; Ueberroth, B; Gao, W; Paulson, T; Wang, H; Tian, Y; Smith, D; Reid, B; Meldrum, Deirdre R

2017-03-16

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.

Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

PubMed

Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

2016-01-01

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology.

Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Breast Cancer Pathologic Stage

PubMed Central

Burnside, Elizabeth S.; Drukker, Karen; Li, Hui; Bonaccio, Ermelinda; Zuley, Margarita; Ganott, Marie; Net, Jose M.; Sutton, Elizabeth; Brandt, Kathleen R.; Whitman, Gary; Conzen, Suzanne; Lan, Li; Ji, Yuan; Zhu, Yitan; Jaffe, Carl; Huang, Erich; Freymann, John; Kirby, Justin; Morris, Elizabeth; Giger, Maryellen

2015-01-01

Background To demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on MRI can accurately predict pathologic stage. Methods We used a dataset of de-identified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. We analyzed 91 biopsy-proven breast cancer cases with pathologic stage (stage I = 22; stage II = 58; stage III = 11) and surgically proven nodal status (negative nodes = 46, ≥ 1 positive node = 44, no nodes examined = 1). We characterized tumors by (a) radiologist measured size, and (b) CEIP. We built models combining two CEIPs to predict tumor pathologic stage and lymph node involvement, evaluated them in leave-one-out cross-validation with area under the ROC curve (AUC) as figure of merit. Results Tumor size was the most powerful predictor of pathologic stage but CEIPs capturing biologic behavior also emerged as predictive (e.g. stage I+II vs. III demonstrated AUC = 0.83). No size measure was successful in the prediction of positive lymph nodes but adding a CEIP describing tumor “homogeneity,” significantly improved this discrimination (AUC = 0.62, p=.003) over chance. Conclusions Our results indicate that MRI phenotypes show promise for predicting breast cancer pathologic stage and lymph node status. PMID:26619259

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Point mutation in the MITF gene causing Waardenburg syndrome type II in a three-generation Indian family.

PubMed

Lalwani, A K; Attaie, A; Randolph, F T; Deshmukh, D; Wang, C; Mhatre, A; Wilcox, E

1998-12-04

Waardenburg syndrome (WS) is an autosomal-dominant neural crest cell disorder phenotypically characterized by hearing impairment and disturbance of pigmentation. A presence of dystopia canthorum is indicative of WS type 1, caused by loss of function mutation in the PAX3 gene. In contrast, type 2 WS (WS2) is characterized by normally placed medial canthi and is genetically heterogeneous; mutations in MITF (microphthalmia associated transcription factor) associated with WS2 have been identified in some but not all affected families. Here, we report on a three-generation Indian family with a point mutation in the MITF gene causing WS2. This mutation, initially reported in a Northern European family, creates a stop codon in exon 7 and is predicted to result in a truncated protein lacking the HLH-Zip or Zip structure necessary for normal interaction with its target DNA motif. Comparison of the phenotype between the two families demonstrates a significant difference in pigmentary disturbance of the eye. This family, with the first documented case of two unrelated WS2 families harboring identical mutations, provides additional evidence for the importance of genetic background on the clinical phenotype.

Identification of a basic helix-loop-helix-type transcription regulator gene in Aspergillus oryzae by systematically deleting large chromosomal segments.

PubMed

Jin, Feng Jie; Takahashi, Tadashi; Machida, Masayuki; Koyama, Yasuji

2009-09-01

We previously developed two methods (loop-out and replacement-type recombination) for generating large-scale chromosomal deletions that can be applied to more effective chromosomal engineering in Aspergillus oryzae. In this study, the replacement-type method is used to systematically delete large chromosomal DNA segments to identify essential and nonessential regions in chromosome 7 (2.93 Mb), which is the smallest A. oryzae chromosome and contains a large number of nonsyntenic blocks. We constructed 12 mutants harboring deletions that spanned 16- to 150-kb segments of chromosome 7 and scored phenotypic changes in the resulting mutants. Among the deletion mutants, strains designated Delta5 and Delta7 displayed clear phenotypic changes involving growth and conidiation. In particular, the Delta5 mutant exhibited vigorous growth and conidiation, potentially beneficial characteristics for certain industrial applications. Further deletion analysis allowed identification of the AO090011000215 gene as the gene responsible for the Delta5 mutant phenotype. The AO090011000215 gene was predicted to encode a helix-loop-helix binding protein belonging to the bHLH family of transcription factors. These results illustrate the potential of the approach for identifying novel functional genes.

Involvement of the VEP1 gene in vascular strand development in Arabidopsis thaliana.

PubMed

Jun, Ji Hyung; Ha, Chan Man; Nam, Hong Gil

2002-03-01

A dominant mutant line characterized by abnormal leaf venation pattern was isolated from a transgenic Arabidopsis plant pool that was generated with Agrobacterium culture harboring an Arabidopsis antisense cDNA library. In the mutant line, the phenotype was due to antisense suppression of a gene we named VEP1 (Vein Patterning). The predicted amino acid sequence of the gene contained a motif related to the mammalian death domain that is found in the apoptotic machinery. Reduced expression of the VEP1 gene resulted in the reduced complexity of the venation pattern of the cotyledons and foliar leaves, which was mainly due to the reduced number of the minor veins and their incomplete connection. The analysis of mutant embryos indicated that the phenotype was originated, at least in part, from a defect in the procambium patterning. In the mutant, the stem and root were thinner than those in wild type. This phenotype was associated with reduced vascular development. The promoter activity of the VEP1 gene was detected preferentially in the vascular regions. We propose that the death domain-containing protein VEP1 functions as a positive element required for vascular strand development in Arabidopsis thaliana.

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

PubMed

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 correlated with behavioral problems and prosocial behaviors in typically developing (TD) siblings of children with ASDs. Siblings of children with ASDs, due to genetic liability, are at a greater risk of psychological maladjustment. Furthermore, environmental factors like parenting styles and family function also have a significant effect on psychological maladjustment.

Breeding nursery tissue collection for possible genomic analysis

USDA-ARS?s Scientific Manuscript database

Phenotyping is considered a major bottleneck in breeding programs. With new genomic technologies, high throughput genotype schemes are constantly being developed. However, every genomic technology requires phenotypic data to inform prediction models generated from the technology. Forage breeders con...

Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study.

PubMed

At, Jotheeswaran; Bryce, Renata; Prina, Matthew; Acosta, Daisy; Ferri, Cleusa P; Guerra, Mariella; Huang, Yueqin; Rodriguez, Juan J Llibre; Salas, Aquiles; Sosa, Ana Luisa; Williams, Joseph D; Dewey, Michael E; Acosta, Isaac; Liu, Zhaorui; Beard, John; Prince, Martin

2015-06-10

In countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China. Population-based cohort studies were conducted in catchment area sites in Cuba, Dominican Republic, Venezuela, Mexico, Peru, India, and China. Seven frailty indicators, namely gait speed, self-reported exhaustion, weight loss, low energy expenditure, undernutrition, cognitive, and sensory impairment were assessed to estimate frailty phenotypes. Mortality and onset of dependence were ascertained after a median of 3.9 years. Overall, 13,924 older people were assessed at baseline, with 47,438 person-years follow-up for mortality and 30,689 for dependence. Both frailty phenotypes predicted the onset of dependence and mortality, even adjusting for chronic diseases and disability, with little heterogeneity of effect among sites. However, population attributable fractions (PAF) summarising etiologic force were highest for the aggregate effect of the individual indicators, as opposed to either the number of indicators or the dichotomised frailty phenotypes. The aggregate of all seven indicators provided the best overall prediction (weighted mean PAF 41.8 % for dependence and 38.3 % for mortality). While weight loss, underactivity, slow walking speed, and cognitive impairment predicted both outcomes, whereas undernutrition predicted only mortality and sensory impairment only dependence. Exhaustion predicted neither outcome. Simply assessed frailty indicators identify older people at risk of dependence and mortality, beyond information provided by chronic disease diagnoses and disability. Frailty is likely to be multidimensional. A better understanding of the construct and pathways to adverse outcomes could inform multidimensional assessment and intervention to prevent or manage dependence in frail older people, with potential to add life to years, and years to life.

Construction and Screening of a Lentiviral Secretome Library.

PubMed

Liu, Tao; Jia, Panpan; Ma, Huailei; Reed, Sean A; Luo, Xiaozhou; Larman, H Benjamin; Schultz, Peter G

2017-06-22

Over 2,000 human proteins are predicted to be secreted, but the biological function of the many of these proteins is still unknown. Moreover, a number of these proteins may act as new therapeutic agents or be targets for the development of therapeutic antibodies. To further explore the extracellular proteome, we have developed a secretome-enriched open reading frame (ORF) library that can be readily screened for autocrine activity in cell-based phenotypic or reporter assays. Next-generation sequencing (NGS) and database analysis predict that the library contains approximately 900 ORFs encoding known secreted proteins (accounting for 77.8% of the library), as well as genes encoding potentially unknown secreted proteins. In a proof-of-principle study, human TF-1 cells were screened for proliferative factors, and the known cytokine GMCSF was identified as a dominant hit. This library offers a relatively low-cost and straightforward approach for functional autocrine screens of secreted proteins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Linking the Human Gut Microbiome to Inflammatory Cytokine Production Capacity.

PubMed

Schirmer, Melanie; Smeekens, Sanne P; Vlamakis, Hera; Jaeger, Martin; Oosting, Marije; Franzosa, Eric A; Ter Horst, Rob; Jansen, Trees; Jacobs, Liesbeth; Bonder, Marc Jan; Kurilshikov, Alexander; Fu, Jingyuan; Joosten, Leo A B; Zhernakova, Alexandra; Huttenhower, Curtis; Wijmenga, Cisca; Netea, Mihai G; Xavier, Ramnik J

2016-11-03

Gut microbial dysbioses are linked to aberrant immune responses, which are often accompanied by abnormal production of inflammatory cytokines. As part of the Human Functional Genomics Project (HFGP), we investigate how differences in composition and function of gut microbial communities may contribute to inter-individual variation in cytokine responses to microbial stimulations in healthy humans. We observe microbiome-cytokine interaction patterns that are stimulus specific, cytokine specific, and cytokine and stimulus specific. Validation of two predicted host-microbial interactions reveal that TNFα and IFNγ production are associated with specific microbial metabolic pathways: palmitoleic acid metabolism and tryptophan degradation to tryptophol. Besides providing a resource of predicted microbially derived mediators that influence immune phenotypes in response to common microorganisms, these data can help to define principles for understanding disease susceptibility. The three HFGP studies presented in this issue lay the groundwork for further studies aimed at understanding the interplay between microbial, genetic, and environmental factors in the regulation of the immune response in humans. PAPERCLIP. Copyright © 2016 Elsevier Inc. All rights reserved.

The cancer glycocalyx mechanically primes integrin-mediated growth and survival

PubMed Central

Paszek, Matthew J.; DuFort, Christopher C.; Rossier, Olivier; Bainer, Russell; Mouw, Janna K.; Godula, Kamil; Hudak, Jason E.; Lakins, Jonathon N.; Wijekoon, Amanda C.; Cassereau, Luke; Rubashkin, Matthew G.; Magbanua, Mark J.; Thorn, Kurt S.; Davidson, Michael W.; Rugo, Hope S.; Park, John W.; Hammer, Daniel A.; Giannone, Grégory; Bertozzi, Carolyn R.; Weaver, Valerie M.

2015-01-01

Malignancy is associated with altered expression of glycans and glycoproteins that contribute to the cellular glycocalyx. We constructed a glycoprotein expression signature, which revealed that metastatic tumours upregulate expression of bulky glycoproteins. A computational model predicted that these glycoproteins would influence transmembrane receptor spatial organization and function. We tested this prediction by investigating whether bulky glycoproteins in the glycocalyx promote a tumour phenotype in human cells by increasing integrin adhesion and signalling. Our data revealed that a bulky glycocalyx facilitates integrin clustering by funnelling active integrins into adhesions and altering integrin state by applying tension to matrix-bound integrins, independent of actomyosin contractility. Expression of large tumour-associated glycoproteins in non-transformed mammary cells promoted focal adhesion assembly and facilitated integrin-dependent growth factor signalling to support cell growth and survival. Clinical studies revealed that large glycoproteins are abundantly expressed on circulating tumour cells from patients with advanced disease. Thus, a bulky glycocalyx is a feature of tumour cells that could foster metastasis by mechanically enhancing cell-surface receptor function. PMID:25030168

Replaying the tape of life in the twenty-first century.

PubMed

Orgogozo, Virginie

2015-12-06

Should the tape of life be replayed, would it produce similar living beings? A classical answer has long been 'no', but accumulating data are now challenging this view. Repeatability in experimental evolution, in phenotypic evolution of diverse species and in the genes underlying phenotypic evolution indicates that despite unpredictability at the level of basic evolutionary processes (such as apparition of mutations), a certain kind of predictability can emerge at higher levels over long time periods. For instance, a survey of the alleles described in the literature that cause non-deleterious phenotypic differences among animals, plants and yeasts indicates that similar phenotypes have often evolved in distinct taxa through independent mutations in the same genes. Does this mean that the range of possibilities for evolution is limited? Does this mean that we can predict the outcomes of a replayed tape of life? Imagining other possible paths for evolution runs into four important issues: (i) resolving the influence of contingency, (ii) imagining living organisms that are different from the ones we know, (iii) finding the relevant concepts for predicting evolution, and (iv) estimating the probability of occurrence for complex evolutionary events that occurred only once during the evolution of life on earth.

Six-Minute Walk Distance Predictors, Including CT Scan Measures, in the COPDGene Cohort

PubMed Central

Rambod, Mehdi; Porszasz, Janos; Make, Barry J.; Crapo, James D.

2012-01-01

Background: Exercise tolerance in COPD is only moderately well predicted by airflow obstruction assessed by FEV1. We determined whether other phenotypic characteristics, including CT scan measures, are independent predictors of 6-min walk distance (6MWD) in the COPDGene cohort. Methods: COPDGene recruits non-Hispanic Caucasian and African American current and ex-smokers. Phenotyping measures include postbronchodilator FEV1 % predicted and inspiratory and expiratory CT lung scans. We defined % emphysema as the percentage of lung voxels < −950 Hounsfield units on the inspiratory scan and % gas trapping as the percentage of lung voxels < −856 Hounsfield units on the expiratory scan. Results: Data of the first 2,500 participants of the COPDGene cohort were analyzed. Participant age was 61 ± 9 years; 51% were men; 76% were non-Hispanic Caucasians, and 24% were African Americans. Fifty-six percent had spirometrically defined COPD, with 9.3%, 23.4%, 15.0%, and 8.3% in GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I to IV, respectively. Higher % emphysema and % gas trapping predicted lower 6MWD (P < .001). However, in a given spirometric group, after adjustment for age, sex, race, and BMI, neither % emphysema nor % gas trapping, or their interactions with FEV1 % predicted, remained a significant 6MWD predictor. In a given spirometric group, only 16% to 27% of the variance in 6MWD could be explained by age, male sex, Caucasian race, and lower BMI as significant predictors of higher 6MWD. Conclusions: In this large cohort of smokers in a given spirometric stage, phenotypic characteristics were only modestly predictive of 6MWD. CT scan measures of emphysema and gas trapping were not predictive of 6MWD after adjustment for other phenotypic characteristics. PMID:21960696

Six-minute walk distance predictors, including CT scan measures, in the COPDGene cohort.

PubMed

Rambod, Mehdi; Porszasz, Janos; Make, Barry J; Crapo, James D; Casaburi, Richard

2012-04-01

Exercise tolerance in COPD is only moderately well predicted by airflow obstruction assessed by FEV(1). We determined whether other phenotypic characteristics, including CT scan measures, are independent predictors of 6-min walk distance (6MWD) in the COPDGene cohort. COPDGene recruits non-Hispanic Caucasian and African American current and ex-smokers. Phenotyping measures include postbronchodilator FEV(1) % predicted and inspiratory and expiratory CT lung scans. We defined % emphysema as the percentage of lung voxels < -950 Hounsfield units on the inspiratory scan and % gas trapping as the percentage of lung voxels < -856 Hounsfield units on the expiratory scan. Data of the first 2,500 participants of the COPDGene cohort were analyzed. Participant age was 61 ± 9 years; 51% were men; 76% were non-Hispanic Caucasians, and 24% were African Americans. Fifty-six percent had spirometrically defined COPD, with 9.3%, 23.4%, 15.0%, and 8.3% in GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I to IV, respectively. Higher % emphysema and % gas trapping predicted lower 6MWD (P < .001). However, in a given spirometric group, after adjustment for age, sex, race, and BMI, neither % emphysema nor % gas trapping, or their interactions with FEV(1) % predicted, remained a significant 6MWD predictor. In a given spirometric group, only 16% to 27% of the variance in 6MWD could be explained by age, male sex, Caucasian race, and lower BMI as significant predictors of higher 6MWD. In this large cohort of smokers in a given spirometric stage, phenotypic characteristics were only modestly predictive of 6MWD. CT scan measures of emphysema and gas trapping were not predictive of 6MWD after adjustment for other phenotypic characteristics.

PPARα siRNA–Treated Expression Profiles Uncover the Causal Sufficiency Network for Compound-Induced Liver Hypertrophy

PubMed Central

Dai, Xudong; Souza, Angus T. De; Dai, Hongyue; Lewis, David L; Lee, Chang-kyu; Spencer, Andy G; Herweijer, Hans; Hagstrom, Jim E; Linsley, Peter S; Bassett, Douglas E; Ulrich, Roger G; He, Yudong D

2007-01-01

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor α (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARα-induced liver hypertrophy is supported by their ability to predict non-PPARα–induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events. PMID:17335344

Pharmacokinetics and pharmacodynamics following maintenance doses of prasugrel and clopidogrel in Chinese carriers of CYP2C19 variants

PubMed Central

Kelly, Ronan P; Close, Sandra L; Farid, Nagy A; Winters, Kenneth J; Shen, Lei; Natanegara, Fanni; Jakubowski, Joseph A; Ho, Mary; Walker, Joseph R; Small, David S

2012-01-01

AIMS This open-label, two-period, randomized, crossover study was designed to determine the effect of CYP2C19 reduced function variants on exposure to active metabolites of, and platelet response to, prasugrel and clopidogrel. METHODS Ninety healthy Chinese subjects, stratified by CYP2C19 phenotype, were randomly assigned to treatment with prasugrel 10 mg or clopidogrel 75 mg for 10 days followed by 14 day washout and 10 day treatment with the other drug. Eighty-three subjects completed both treatment periods. Blood samples were collected at specified time points for measurement of each drug's active metabolite (Pras-AM and Clop-AM) concentrations and determination of inhibition of platelet aggregation (IPA) by light transmittance aggregometry. CYP2C19 genotypes were classified into three predicted phenotype groups: rapid metabolizers [RMs (*1/*1)], heterozygous or intermediate metabolizers [IMs (*1/*2, *1/*3)] and poor metabolizers [PMs (*2/*2, *2/*3)]. RESULTS Pras-AM exposure was similar in IMs and RMs (90% CI 0.85, 1.03) and slightly lower in PMs than IMs (90% CI 0.74, 0.99), whereas Clop-AM exposure was significantly lower in IMs compared with RMs (90% CI 0.62, 0.83), and in PMs compared with IMs (90% CI 0.53, 0.82). IPA was more consistent among RMs, IMs and PMs in prasugrel treated subjects (80.2%, 84.2% and 80.2%, respectively) than in clopidogrel treated subjects (59.7%, 56.2% and 36.8%, respectively; P < 0.001). CONCLUSIONS Prasugrel demonstrated higher active metabolite exposure and more consistent pharmacodynamic response across all three predicted phenotype groups compared with clopidogrel, confirming observations from previous research that CYP2C19 phenotype plays an important role in variability of response to clopidogrel, but has no impact on response to prasugrel. PMID:21689142

Dynamical predictors of an imminent phenotypic switch in bacteria

NASA Astrophysics Data System (ADS)

Wang, Huijing; Ray, J. Christian J.

2017-08-01

Single cells can stochastically switch across thresholds imposed by regulatory networks. Such thresholds can act as a tipping point, drastically changing global phenotypic states. In ecology and economics, imminent transitions across such tipping points can be predicted using dynamical early warning indicators. A typical example is ‘flickering’ of a fast variable, predicting a longer-lasting switch from a low to a high state or vice versa. Considering the different timescales between metabolite and protein fluctuations in bacteria, we hypothesized that metabolic early warning indicators predict imminent transitions across a network threshold caused by enzyme saturation. We used stochastic simulations to determine if flickering predicts phenotypic transitions, accounting for a variety of molecular physiological parameters, including enzyme affinity, burstiness of enzyme gene expression, homeostatic feedback, and rates of metabolic precursor influx. In most cases, we found that metabolic flickering rates are robustly peaked near the enzyme saturation threshold. The degree of fluctuation was amplified by product inhibition of the enzyme. We conclude that sensitivity to flickering in fast variables may be a possible natural or synthetic strategy to prepare physiological states for an imminent transition.

Clustering patterns of LOD scores for asthma-related phenotypes revealed by a genome-wide screen in 295 French EGEA families.

PubMed

Bouzigon, Emmanuelle; Dizier, Marie-Hélène; Krähenbühl, Christine; Lemainque, Arnaud; Annesi-Maesano, Isabella; Betard, Christine; Bousquet, Jean; Charpin, Denis; Gormand, Frédéric; Guilloud-Bataille, Michel; Just, Jocelyne; Le Moual, Nicole; Maccario, Jean; Matran, Régis; Neukirch, Françoise; Oryszczyn, Marie-Pierre; Paty, Evelyne; Pin, Isabelle; Rosenberg-Bourgin, Myriam; Vervloet, Daniel; Kauffmann, Francine; Lathrop, Mark; Demenais, Florence

2004-12-15

A genome-wide scan for asthma phenotypes was conducted in the whole sample of 295 EGEA families selected through at least one asthmatic subject. In addition to asthma, seven phenotypes involved in the main asthma physiopathological pathways were considered: SPT (positive skin prick test response to at least one of 11 allergens), SPTQ score being the number of positive skin test responses to 11 allergens, Phadiatop (positive specific IgE response to a mixture of allergens), total IgE levels, eosinophils, bronchial responsiveness (BR) to methacholine challenge and %predicted FEV(1). Four regions showed evidence for linkage (P

Experimental elevation of testosterone lowers fitness in female dark-eyed juncos.

PubMed

Gerlach, Nicole M; Ketterson, Ellen D

2013-05-01

Testosterone (T) is often referred to as the "male hormone," but it can influence aggression, parental behavior, and immune function in both males and females. By experimentally relating hormone-induced changes in phenotype to fitness, it is possible to ask whether existing phenotypes perform better or worse than alternative phenotypes, and hence to predict how selection might act on a novel or rare phenotype. In a songbird, the dark-eyed junco (Junco hyemalis), we have examined the effects of experimentally elevated T in females on fitness-related behaviors such as parental care. In this study, we implanted female juncos with exogenous T and examined its effect on fitness (survival, reproduction, and extra-pair mating) to assess whether T-altered phenotypes would prove to be adaptive or deleterious for females. Experimental elevation of T decreased the likelihood that a female would breed successfully, and T-implanted females had lower total reproductive success at every stage of the reproductive cycle. They did not, however, differ from control females in fledgling quality, extra-pair offspring production, survival, or reproduction in the following year. Previous work in this system has shown that experimental elevation of T in males alters behavior and physiology and decreases survival but increases the production of extra-pair offspring, leading to higher net fitness relative to control animals. Our results suggest that increased T has divergent effects on male and female fitness in this species, and that prevailing levels in females may be adaptive for them. These findings are consistent with sexual conflict. Copyright © 2013 Elsevier Inc. All rights reserved.

Autism beyond diagnostic categories: characterization of autistic phenotypes in schizophrenia.

PubMed

Kästner, Anne; Begemann, Martin; Michel, Tanja Maria; Everts, Sarah; Stepniak, Beata; Bach, Christiane; Poustka, Luise; Becker, Joachim; Banaschewski, Tobias; Dose, Matthias; Ehrenreich, Hannelore

2015-05-13

Behavioral phenotypical continua from health to disease suggest common underlying mechanisms with quantitative rather than qualitative differences. Until recently, autism spectrum disorders and schizophrenia were considered distinct nosologic entities. However, emerging evidence contributes to the blurring of symptomatic and genetic boundaries between these conditions. The present study aimed at quantifying behavioral phenotypes shared by autism spectrum disorders and schizophrenia to prepare the ground for biological pathway analyses. Specific items of the Positive and Negative Syndrome Scale were employed and summed up to form a dimensional autism severity score (PAUSS). The score was created in a schizophrenia sample (N = 1156) and validated in adult high-functioning autism spectrum disorder (ASD) patients (N = 165). To this end, the Autism Diagnostic Observation Schedule (ADOS), the Autism (AQ) and Empathy Quotient (EQ) self-rating questionnaires were applied back to back with the newly developed PAUSS. PAUSS differentiated between ASD, schizophrenia and a disease-control sample and substantially correlated with the Autism Diagnostic Observation Schedule. Patients with ADOS scores ≥12 obtained highest, those with scores <7 lowest PAUSS values. AQ and EQ were not found to vary dependent on ADOS diagnosis. ROC curves for ADOS and PAUSS resulted in AuC values of 0.9 and 0.8, whereas AQ and EQ performed at chance level in the prediction of ASD. This work underscores the convergence of schizophrenia negative symptoms and autistic phenotypes. PAUSS evolved as a measure capturing the continuous nature of autistic behaviors. The definition of extreme-groups based on the dimensional PAUSS may permit future investigations of genetic constellations modulating autistic phenotypes.

Genome-Wide Architecture of Disease Resistance Genes in Lettuce

PubMed Central

Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K.; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W.

2015-01-01

Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. PMID:26449254

SNPnexus: assessing the functional relevance of genetic variation to facilitate the promise of precision medicine.

PubMed

Dayem Ullah, Abu Z; Oscanoa, Jorge; Wang, Jun; Nagano, Ai; Lemoine, Nicholas R; Chelala, Claude

2018-05-11

Broader functional annotation of genetic variation is a valuable means for prioritising phenotypically-important variants in further disease studies and large-scale genotyping projects. We developed SNPnexus to meet this need by assessing the potential significance of known and novel SNPs on the major transcriptome, proteome, regulatory and structural variation models. Since its previous release in 2012, we have made significant improvements to the annotation categories and updated the query and data viewing systems. The most notable changes include broader functional annotation of noncoding variants and expanding annotations to the most recent human genome assembly GRCh38/hg38. SNPnexus has now integrated rich resources from ENCODE and Roadmap Epigenomics Consortium to map and annotate the noncoding variants onto different classes of regulatory regions and noncoding RNAs as well as providing their predicted functional impact from eight popular non-coding variant scoring algorithms and computational methods. A novel functionality offered now is the support for neo-epitope predictions from leading tools to facilitate its use in immunotherapeutic applications. These updates to SNPnexus are in preparation for its future expansion towards a fully comprehensive computational workflow for disease-associated variant prioritization from sequencing data, placing its users at the forefront of translational research. SNPnexus is freely available at http://www.snp-nexus.org.

Variant Interpretation: Functional Assays to the Rescue.

PubMed

Starita, Lea M; Ahituv, Nadav; Dunham, Maitreya J; Kitzman, Jacob O; Roth, Frederick P; Seelig, Georg; Shendure, Jay; Fowler, Douglas M

2017-09-07

Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Histone H2A is required for normal centromere function in Saccharomyces cerevisiae

PubMed Central

Pinto, Inés; Winston, Fred

2000-01-01

Histones are structural and functional components of the eukaryotic chromosome, and their function is essential for normal cell cycle progression. In this work, we describe the characterization of two Saccharomyces cerevisiae cold-sensitive histone H2A mutants. Both mutants contain single amino acid replacements of residues predicted to be on the surface of the nucleosome and in close contact with DNA. We show that these H2A mutations cause an increase-in-ploidy phenotype, an increased rate of chromosome loss, and a defect in traversing the G2–M phase of the cell cycle. Moreover, these H2A mutations show genetic interactions with mutations in genes encoding kinetochore components. Finally, chromatin analysis of these H2A mutants has revealed an altered centromeric chromatin structure. Taken together, these results strongly suggest that histone H2A is required for proper centromere–kinetochore function during chromosome segregation. PMID:10747028

Fine mapping and identification of candidate genes for the sy-2 locus in a temperature-sensitive chili pepper (Capsicum chinense).

PubMed

Liu, Li; Venkatesh, Jelli; Jo, Yeong Deuk; Koeda, Sota; Hosokawa, Munetaka; Kang, Jin-Ho; Goritschnig, Sandra; Kang, Byoung-Cheorl

2016-08-01

The sy - 2 temperature-sensitive gene from Capsicum chinense was fine mapped to a 138.8-kb region at the distal portion of pepper chromosome 1. Based on expression analyses, two putative F-box genes were identified as sy - 2 candidate genes. Seychelles-2 ('sy-2') is a temperature-sensitive natural mutant of Capsicum chinense, which exhibits an abnormal leaf phenotype when grown at temperatures below 24 °C. We previously showed that the sy-2 phenotype is controlled by a single recessive gene, sy-2, located on pepper chromosome 1. In this study, a high-resolution genetic and physical map for the sy-2 locus was constructed using two individual F2 mapping populations derived from a cross between C. chinense mutant 'sy-2' and wild-type 'No. 3341'. The sy-2 gene was fine mapped to a 138.8-kb region between markers SNP 5-5 and SNP 3-8 at the distal portion of chromosome 1, based on comparative genomic analysis and genomic information from pepper. The sy-2 target region was predicted to contain 27 genes. Expression analysis of these predicted genes showed a differential expression pattern for ORF10 and ORF20 between mutant and wild-type plants; with both having significantly lower expression in 'sy-2' than in wild-type plants. In addition, the coding sequences of both ORF10 and ORF20 contained single nucleotide polymorphisms (SNPs) causing amino acid changes, which may have important functional consequences. ORF10 and ORF20 are predicted to encode F-box proteins, which are components of the SCF complex. Based on the differential expression pattern and the presence of nonsynonymous SNPs, we suggest that these two putative F-box genes are most likely responsible for the temperature-sensitive phenotypes in pepper. Further investigation of these genes may enable a better understanding of the molecular mechanisms of low temperature sensitivity in plants.

Redox theory of aging: implications for health and disease

PubMed Central

Go, Young-Mi; Jones, Dean P.

2017-01-01

Genetics ultimately defines an individual, yet the phenotype of an adult is extensively determined by the sequence of lifelong exposures, termed the exposome. The redox theory of aging recognizes that animals evolved within an oxygen-rich environment, which created a critical redox interface between an organism and its environment. Advances in redox biology show that redox elements are present throughout metabolic and structural systems and operate as functional networks to support the genome in adaptation to environmental resources and challenges during lifespan. These principles emphasize that physical and functional phenotypes of an adult are determined by gene–environment interactions from early life onward. The principles highlight the critical nature of cumulative exposure memories in defining changes in resilience progressively during life. Both plasma glutathione and cysteine systems become oxidized with aging, and the recent finding that cystine to glutathione ratio in human plasma predicts death in coronary artery disease (CAD) patients suggests this could provide a way to measure resilience of redox networks in aging and disease. The emerging concepts of cumulative gene–environment interactions warrant focused efforts to elucidate central mechanisms by which exposure memory governs health and etiology, onset and progression of disease. PMID:28667066

Cuticle Integrity and Biogenic Amine Synthesis in Caenorhabditis elegans Require the Cofactor Tetrahydrobiopterin (BH4)

PubMed Central

Loer, Curtis M.; Calvo, Ana C.; Watschinger, Katrin; Werner-Felmayer, Gabriele; O’Rourke, Delia; Stroud, Dave; Tong, Amy; Gotenstein, Jennifer R.; Chisholm, Andrew D.; Hodgkin, Jonathan; Werner, Ernst R.; Martinez, Aurora

2015-01-01

Tetrahydrobiopterin (BH4) is the natural cofactor of several enzymes widely distributed among eukaryotes, including aromatic amino acid hydroxylases (AAAHs), nitric oxide synthases (NOSs), and alkylglycerol monooxygenase (AGMO). We show here that the nematode Caenorhabditis elegans, which has three AAAH genes and one AGMO gene, contains BH4 and has genes that function in BH4 synthesis and regeneration. Knockout mutants for putative BH4 synthetic enzyme genes lack the predicted enzymatic activities, synthesize no BH4, and have indistinguishable behavioral and neurotransmitter phenotypes, including serotonin and dopamine deficiency. The BH4 regeneration enzymes are not required for steady-state levels of biogenic amines, but become rate limiting in conditions of reduced BH4 synthesis. BH4-deficient mutants also have a fragile cuticle and are generally hypersensitive to exogenous agents, a phenotype that is not due to AAAH deficiency, but rather to dysfunction in the lipid metabolic enzyme AGMO, which is expressed in the epidermis. Loss of AGMO or BH4 synthesis also specifically alters the sensitivity of C. elegans to bacterial pathogens, revealing a cuticular function for AGMO-dependent lipid metabolism in host–pathogen interactions. PMID:25808955

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

PubMed

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.

An Effective Model of the Retinoic Acid Induced HL-60 Differentiation Program.

PubMed

Tasseff, Ryan; Jensen, Holly A; Congleton, Johanna; Dai, David; Rogers, Katharine V; Sagar, Adithya; Bunaciu, Rodica P; Yen, Andrew; Varner, Jeffrey D

2017-10-30

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPARg were critical to the ATRAinduced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

Genomic selection using beef commercial carcass phenotypes.

PubMed

Todd, D L; Roughsedge, T; Woolliams, J A

2014-03-01

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype-environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρX). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρX. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρX of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρX; however, the effect of varying ρX was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρX=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes in genomic evaluations.

[Phenotypic heterogeneity of chronic obstructive pulmonary disease].

PubMed

Garcia-Aymerich, Judith; Agustí, Alvar; Barberà, Joan A; Belda, José; Farrero, Eva; Ferrer, Antoni; Ferrer, Jaume; Gáldiz, Juan B; Gea, Joaquim; Gómez, Federico P; Monsó, Eduard; Morera, Josep; Roca, Josep; Sauleda, Jaume; Antó, Josep M

2009-03-01

A functional definition of chronic obstructive pulmonary disease (COPD) based on airflow limitation has largely dominated the field. However, a view has emerged that COPD involves a complex array of cellular, organic, functional, and clinical events, with a growing interest in disentangling the phenotypic heterogeneity of COPD. The present review is based on the opinion of the authors, who have extensive research experience in several aspects of COPD. The starting assumption of the review is that current knowledge on the pathophysiology and clinical features of COPD allows us to classify phenotypic information in terms of the following dimensions: respiratory symptoms and health status, acute exacerbations, lung function, structural changes, local and systemic inflammation, and systemic effects. Twenty-six phenotypic traits were identified and assigned to one of the 6 dimensions. For each dimension, a summary is provided of the best evidence on the relationships among phenotypic traits, in particular among those corresponding to different dimensions, and on the relationship between these traits and relevant events in the natural history of COPD. The information has been organized graphically into a phenotypic matrix where each cell representing a pair of phenotypic traits is linked to relevant references. The information provided has the potential to increase our understanding of the heterogeneity of COPD phenotypes and help us plan future studies on aspects that are as yet unexplored.

Platform for combined analysis of functional and biomolecular phenotypes of the same cell

PubMed Central

Kelbauskas, L.; Ashili, S.; Zeng, J.; Rezaie, A.; Lee, K.; Derkach, D.; Ueberroth, B.; Gao, W.; Paulson, T.; Wang, H.; Tian, Y.; Smith, D.; Reid, B.; Meldrum, Deirdre R.

2017-01-01

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression. PMID:28300162

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

PubMed

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.

Accounting for the Down syndrome advantage?

PubMed

Esbensen, Anna J; Seltzer, Marsha Mailick

2011-01-01

The authors examined factors that could explain the higher levels of psychosocial well being observed in past research in mothers of individuals with Down syndrome compared with mothers of individuals with other types of intellectual disabilities. The authors studied 155 mothers of adults with Down syndrome, contrasting factors that might validly account for the ?Down syndrome advantage? (behavioral phenotype) with those that have been portrayed in past research as artifactual (maternal age, social supports). The behavioral phenotype predicted less pessimism, more life satisfaction, and a better quality of the mother?child relationship. However, younger maternal age and fewer social supports, as well as the behavioral phenotype, predicted higher levels of caregiving burden. Implications for future research on families of individuals with Down syndrome are discussed.

The value of cows in reference populations for genomic selection of new functional traits.

PubMed

Buch, L H; Kargo, M; Berg, P; Lassen, J; Sørensen, A C

2012-06-01

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic prediction model to test the hypothesis that the value of cows in reference populations depends on the availability of phenotypic records. To test the hypothesis, we investigated different strategies of building a reference population for a new functional trait over a 10-year period. The trait was either recorded on a large scale (30 000 cows per year) or on a small scale (2000 cows per year). For large-scale recording, we compared four scenarios where the reference population consisted of 30 sires; 30 sires and 170 test bulls; 30 sires and 2000 cows; or 30 sires, 2000 cows and 170 test bulls in the first year with measurements of the new functional trait. In addition to varying the make-up of the reference population, we also varied the heritability of the trait (h2 = 0.05 v. 0.15). The results showed that a reference population of test bulls, cows and sires results in the highest accuracy of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new functional trait. The results showed that a reference population of cows results in the highest accuracy of the DGV whether the heritability is 0.05 or 0.15, because variation is lost when phenotypic data on cows are summarized in EBV of their sires. The main conclusions from this study are: (i) the fewer phenotypic records, the larger effect of including cows in the reference population; (ii) for small-scale recording, the accuracy of the DGV will continue to increase for several years, whereas the increases in the accuracy of the DGV quickly decrease with large-scale recording; (iii) it is possible to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls.

Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen

PubMed Central

Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer

2014-01-01

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318

Characterization of Novel StAR (Steroidogenic Acute Regulatory Protein) Mutations Causing Non-Classic Lipoid Adrenal Hyperplasia

PubMed Central

Flück, Christa E.; Pandey, Amit V.; Dick, Bernhard; Camats, Núria; Fernández-Cancio, Mónica; Clemente, María; Gussinyé, Miquel; Carrascosa, Antonio; Mullis, Primus E.; Audi, Laura

2011-01-01

Context Steroidogenic acute regulatory protein (StAR) is crucial for transport of cholesterol to mitochondria where biosynthesis of steroids is initiated. Loss of StAR function causes lipoid congenital adrenal hyperplasia (LCAH). Objective StAR gene mutations causing partial loss of function manifest atypical and may be mistaken as familial glucocorticoid deficiency. Only a few mutations have been reported. Design To report clinical, biochemical, genetic, protein structure and functional data on two novel StAR mutations, and to compare them with published literature. Setting Collaboration between the University Children's Hospital Bern, Switzerland, and the CIBERER, Hospital Vall d'Hebron, Autonomous University, Barcelona, Spain. Patients Two subjects of a non-consanguineous Caucasian family were studied. The 46,XX phenotypic normal female was diagnosed with adrenal insufficiency at the age of 10 months, had normal pubertal development and still has no signs of hypergonodatropic hypogonadism at 32 years of age. Her 46,XY brother was born with normal male external genitalia and was diagnosed with adrenal insufficiency at 14 months. Puberty was normal and no signs of hypergonadotropic hypogonadism are present at 29 years of age. Results StAR gene analysis revealed two novel compound heterozygote mutations T44HfsX3 and G221S. T44HfsX3 is a loss-of-function StAR mutation. G221S retains partial activity (∼30%) and is therefore responsible for a milder, non-classic phenotype. G221S is located in the cholesterol binding pocket and seems to alter binding/release of cholesterol. Conclusions StAR mutations located in the cholesterol binding pocket (V187M, R188C, R192C, G221D/S) seem to cause non-classic lipoid CAH. Accuracy of genotype-phenotype prediction by in vitro testing may vary with the assays employed. PMID:21647419

Social Frailty and Functional Disability: Findings From the Singapore Longitudinal Ageing Studies.

PubMed

Teo, Nigel; Gao, Qi; Nyunt, Ma Shwe Zin; Wee, Shiou Liang; Ng, Tze-Pin

2017-07-01

To examine the association between the social frailty (SF) phenotype and functional disability, independently of the physical frailty (PF) phenotype, and compare the abilities of the PF, SF, and combined social and physical (PSF) indexes for predicting functional disability. Cross-sectional and longitudinal analyses of a population-based cohort (Singapore Longitudinal Ageing Study, SLAS-1) of 2406 community-dwelling older adults with 3 years of follow-up (N = 1254 and N = 1557 for instrumental activity of daily living (IADL) disability and severe disability (≥3 basic ADL) respectively). Seven-item social frailty index (living arrangements, education, socioeconomic status, and social network and support, 0 = nil SF, 1 = low, 2-7 = high), PF phenotype (Fried criteria), and instrumental activities of daily living (IADLs) disability and severe disability (≥3 basic ADLs). Compared to nil SF, low and high SF were significantly associated with 1.3 to 2.4 fold increased prevalence and incidence of IADL disability, and 6.3 fold increase in severe disability. Frail individuals with and without SF stood out with 5-11 fold increased prevalence and incidence of IADL disability and 21-25 fold increased prevalence and incidence of severe disability, compared to robust individuals without SF. A combined PSF index more accurately identified individuals with increased risk of functional disability (ROC = 64%) and severe disability (ROC = 81%) than either the SF or the PF indexes alone (55% to 68%). The SF index alone or in combination with the PF index has clinical relevance and utility for identifying and stratifying older people at risk of disability. The mental frailty construct is closely related to SF and should be further investigated in future studies. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Characterizing the roles of changing population size and selection on the evolution of flux control in metabolic pathways.

PubMed

Orlenko, Alena; Chi, Peter B; Liberles, David A

2017-05-25

Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance. The evolutionary stability of rate limiting steps and the patterns of inter-molecular co-evolution were evaluated in a simulated pathway with a system out of equilibrium due to fluctuating selection, population size, or positive directional selection, to contrast with those under stabilizing selection. Depending upon the underlying population genetic regime, fluctuating population size was found to increase the evolutionary stability of rate limiting steps in some scenarios. This result was linked to patterns of local adaptation of the population. Further, during positive directional selection, as with more complex mutational scenarios, an increase in the observation of inter-molecular co-evolution was observed. Differences in patterns of evolution when systems are in and out of equilibrium, including during positive directional selection may lead to predictable differences in observed patterns for divergent evolutionary scenarios. In particular, this result might be harnessed to detect differences between compensatory processes and directional processes at the pathway level based upon evolutionary observations in individual proteins. Detecting functional shifts in pathways reflects an important milestone in predicting when changes in genotypes result in changes in phenotypes.