Explaining the disease phenotype of intergenic SNP through predicted long range regulation.

PubMed

Chen, Jingqi; Tian, Weidong

2016-10-14

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

PubMed

Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

Integrating Multiple Correlated Phenotypes for Genetic Association Analysis by Maximizing Heritability

PubMed Central

Zhou, Jin J.; Cho, Michael H.; Lange, Christoph; Lutz, Sharon; Silverman, Edwin K.; Laird, Nan M.

2015-01-01

Many correlated disease variables are analyzed jointly in genetic studies in the hope of increasing power to detect causal genetic variants. One approach involves assessing the relationship between each phenotype and each single nucleotide polymorphism (SNP) individually and using a Bonferroni correction for the effective number of tests conducted. Alternatively, one can apply a multivariate regression or a dimension reduction technique, such as principal component analysis (PCA), and test for the association with the principal components (PC) of the phenotypes rather than the individual phenotypes. Inspired by the previous approaches of combining phenotypes to maximize heritability at individual SNPs, in this paper, we propose to construct a maximally heritable phenotype (MaxH) by taking advantage of the estimated total heritability and co-heritability. The heritability and co-heritability only need to be estimated once, therefore our method is applicable to genome-wide scans. MaxH phenotype is a linear combination of the individual phenotypes with increased heritability and power over the phenotypes being combined. Simulations show that the heritability and power achieved agree well with the theory for large samples and two phenotypes. We compare our approach with commonly used methods and assess both the heritability and the power of the MaxH phenotype. Moreover we provide suggestions for how to choose the phenotypes for combination. An application of our approach to a COPD genome-wide association study shows the practical relevance. PMID:26111731

Computerized image analysis for quantitative neuronal phenotyping in zebrafish.

PubMed

Liu, Tianming; Lu, Jianfeng; Wang, Ye; Campbell, William A; Huang, Ling; Zhu, Jinmin; Xia, Weiming; Wong, Stephen T C

2006-06-15

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.

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.

Molecular Phenotyping Combines Molecular Information, Biological Relevance, and Patient Data to Improve Productivity of Early Drug Discovery.

PubMed

Drawnel, Faye Marie; Zhang, Jitao David; Küng, Erich; Aoyama, Natsuyo; Benmansour, Fethallah; Araujo Del Rosario, Andrea; Jensen Zoffmann, Sannah; Delobel, Frédéric; Prummer, Michael; Weibel, Franziska; Carlson, Coby; Anson, Blake; Iacone, Roberto; Certa, Ulrich; Singer, Thomas; Ebeling, Martin; Prunotto, Marco

2017-05-18

Today, novel therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping was applicable to compounds with a range of binding specificities and triaged false positives derived from high-content screening assays. The technique identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. Our results advocate for application of molecular phenotyping in early drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2014-01-01

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

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

PubMed

Rozman, Jan; Rathkolb, Birgit; Oestereicher, Manuela A; Schütt, Christine; Ravindranath, Aakash Chavan; Leuchtenberger, Stefanie; Sharma, Sapna; Kistler, Martin; Willershäuser, Monja; Brommage, Robert; Meehan, Terrence F; Mason, Jeremy; Haselimashhadi, Hamed; Hough, Tertius; Mallon, Ann-Marie; Wells, Sara; Santos, Luis; Lelliott, Christopher J; White, Jacqueline K; Sorg, Tania; Champy, Marie-France; Bower, Lynette R; Reynolds, Corey L; Flenniken, Ann M; Murray, Stephen A; Nutter, Lauryl M J; Svenson, Karen L; West, David; Tocchini-Valentini, Glauco P; Beaudet, Arthur L; Bosch, Fatima; Braun, Robert B; Dobbie, Michael S; Gao, Xiang; Herault, Yann; Moshiri, Ala; Moore, Bret A; Kent Lloyd, K C; McKerlie, Colin; Masuya, Hiroshi; Tanaka, Nobuhiko; Flicek, Paul; Parkinson, Helen E; Sedlacek, Radislav; Seong, Je Kyung; Wang, Chi-Kuang Leo; Moore, Mark; Brown, Steve D; Tschöp, Matthias H; Wurst, Wolfgang; Klingenspor, Martin; Wolf, Eckhard; Beckers, Johannes; Machicao, Fausto; Peter, Andreas; Staiger, Harald; Häring, Hans-Ulrich; Grallert, Harald; Campillos, Monica; Maier, Holger; Fuchs, Helmut; Gailus-Durner, Valerie; Werner, Thomas; Hrabe de Angelis, Martin

2018-01-18

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

Dissecting the Phenotypic Components of Crop Plant Growth and Drought Responses Based on High-Throughput Image Analysis[W][OPEN

PubMed Central

Chen, Dijun; Neumann, Kerstin; Friedel, Swetlana; Kilian, Benjamin; Chen, Ming; Altmann, Thomas; Klukas, Christian

2014-01-01

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues. PMID:25501589

Java implementation of Class Association Rule algorithms

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

Tamura, Makio

2007-08-30

Java implementation of three Class Association Rule mining algorithms, NETCAR, CARapriori, and clustering based rule mining. NETCAR algorithm is a novel algorithm developed by Makio Tamura. The algorithm is discussed in a paper: UCRL-JRNL-232466-DRAFT, and would be published in a peer review scientific journal. The software is used to extract combinations of genes relevant with a phenotype from a phylogenetic profile and a phenotype profile. The phylogenetic profiles is represented by a binary matrix and a phenotype profile is represented by a binary vector. The present application of this software will be in genome analysis, however, it could be appliedmore » more generally.« less

An omnibus test for family-based association studies with multiple SNPs and multiple phenotypes.

PubMed

Lasky-Su, Jessica; Murphy, Amy; McQueen, Matthew B; Weiss, Scott; Lange, Christoph

2010-06-01

We propose an omnibus family-based association test (MFBAT) that can be applied to multiple markers and multiple phenotypes and that has only one degree of freedom. The proposed test statistic extends current FBAT methodology to incorporate multiple markers as well as multiple phenotypes. Using simulation studies, power estimates for the proposed methodology are compared with the standard methodologies. On the basis of these simulations, we find that MFBAT substantially outperforms other methods, including haplotypic approaches and doing multiple tests with single single-nucleotide polymorphisms (SNPs) and single phenotypes. The practical relevance of the approach is illustrated by an application to asthma in which SNP/phenotype combinations are identified and reach overall significance that would not have been identified using other approaches. This methodology is directly applicable to cases in which there are multiple SNPs, such as candidate gene studies, cases in which there are multiple phenotypes, such as expression data, and cases in which there are multiple phenotypes and genotypes, such as genome-wide association studies that incorporate expression profiles as phenotypes. This program is available in the PBAT analysis package.

Use of natural variation to identify loci associated with relevant agronomic phenotypic traits

USDA-ARS?s Scientific Manuscript database

Analysis of natural allelic variation is a useful discovery tool to identify novel alleles in genes and pathways that are consistent with agronomic productivity and environmental stability. Switchgrass, a native perennial North American prairie grass and emerging biofuel feedstock species, is divide...

shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations.

PubMed

Dwivedi, Bhakti; Kowalski, Jeanne

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/.

shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations

PubMed Central

Dwivedi, Bhakti

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/. PMID:29415010

Mouse Phenome Database

PubMed Central

Grubb, Stephen C.; Bult, Carol J.; Bogue, Molly A.

2014-01-01

The Mouse Phenome Database (MPD; phenome.jax.org) was launched in 2001 as the data coordination center for the international Mouse Phenome Project. MPD integrates quantitative phenotype, gene expression and genotype data into a common annotated framework to facilitate query and analysis. MPD contains >3500 phenotype measurements or traits relevant to human health, including cancer, aging, cardiovascular disorders, obesity, infectious disease susceptibility, blood disorders, neurosensory disorders, drug addiction and toxicity. Since our 2012 NAR report, we have added >70 new data sets, including data from Collaborative Cross lines and Diversity Outbred mice. During this time we have completely revamped our homepage, improved search and navigational aspects of the MPD application, developed several web-enabled data analysis and visualization tools, annotated phenotype data to public ontologies, developed an ontology browser and released new single nucleotide polymorphism query functionality with much higher density coverage than before. Here, we summarize recent data acquisitions and describe our latest improvements. PMID:24243846

Bioethanol strains of Saccharomyces cerevisiae characterised by microsatellite and stress resistance.

PubMed

Reis, Vanda Renata; Antonangelo, Ana Teresa Burlamaqui Faraco; Bassi, Ana Paula Guarnieri; Colombi, Débora; Ceccato-Antonini, Sandra Regina

Strains of Saccharomyces cerevisiae may display characteristics that are typical of rough-type colonies, made up of cells clustered in pseudohyphal structures and comprised of daughter buds that do not separate from the mother cell post-mitosis. These strains are known to occur frequently in fermentation tanks with significant lower ethanol yield when compared to fermentations carried out by smooth strains of S. cerevisiae that are composed of dispersed cells. In an attempt to delineate genetic and phenotypic differences underlying the two phenotypes, this study analysed 10 microsatellite loci of 22 S. cerevisiae strains as well as stress resistance towards high concentrations of ethanol and glucose, low pH and cell sedimentation rates. The results obtained from the phenotypic tests by Principal-Component Analysis revealed that unlike the smooth colonies, the rough colonies of S. cerevisiae exhibit an enhanced resistance to stressful conditions resulting from the presence of excessive glucose and ethanol and high sedimentation rate. The microsatellite analysis was not successful to distinguish between the colony phenotypes as phenotypic assays. The relevant industrial strain PE-2 was observed in close genetic proximity to rough-colony although it does not display this colony morphology. A unique genetic pattern specific to a particular phenotype remains elusive. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Deregulation of obesity-relevant genes is associated with progression in BMI and the amount of adipose tissue in pigs.

PubMed

Mentzel, Caroline M Junker; Cardoso, Tainã Figueiredo; Pipper, Christian Bressen; Jacobsen, Mette Juul; Jørgensen, Claus Bøttcher; Cirera, Susanna; Fredholm, Merete

2018-02-01

The aim of this study was to elucidate the relative impact of three phenotypes often used to characterize obesity on perturbation of molecular pathways involved in obesity. The three obesity-related phenotypes are (1) body mass index (BMI), (2) amount of subcutaneous adipose tissue (SATa), and (3) amount of retroperitoneal adipose tissue (RPATa). Although it is generally accepted that increasing amount of RPATa is 'unhealthy', a direct comparison of the relative impact of the three obesity-related phenotypes on gene expression has, to our knowledge, not been performed previously. We have used multiple linear models to analyze altered gene expression of selected obesity-related genes in tissues collected from 19 female pigs phenotypically characterized with respect to the obesity-related phenotypes. Gene expression was assessed by high-throughput qPCR in RNA from liver, skeletal muscle and abdominal adipose tissue. The stringent statistical approach used in the study has increased the power of the analysis compared to the classical approach of analysis in divergent groups of individuals. Our approach led to the identification of key components of cellular pathways that are modulated in the three tissues in association with changes in the three obesity-relevant phenotypes (BMI, SATa and RPATa). The deregulated pathways are involved in biosynthesis and transcript regulation in adipocytes, in lipid transport, lipolysis and metabolism, and in inflammatory responses. Deregulation seemed more comprehensive in liver (23 genes) compared to abdominal adipose tissue (10 genes) and muscle (3 genes). Notably, the study supports the notion that excess amount of intra-abdominal adipose tissue is associated with a greater metabolic disease risk. Our results provide molecular support for this notion by demonstrating that increasing amount of RPATa has a higher impact on perturbation of cellular pathways influencing obesity and obesity-related metabolic traits compared to increase in BMI and amount of SATa.

Genome-wide association mapping and agronomic impact of cowpea root architecture.

PubMed

Burridge, James D; Schneider, Hannah M; Huynh, Bao-Lam; Roberts, Philip A; Bucksch, Alexander; Lynch, Jonathan P

2017-02-01

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance. Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

Mouse Phenome Database

PubMed Central

Grubb, Stephen C.; Maddatu, Terry P.; Bult, Carol J.; Bogue, Molly A.

2009-01-01

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools). PMID:18987003

Mito-Nuclear Interactions Affecting Lifespan and Neurodegeneration in a Drosophila Model of Leigh Syndrome.

PubMed

Loewen, Carin A; Ganetzky, Barry

2018-04-01

Proper mitochondrial activity depends upon proteins encoded by genes in the nuclear and mitochondrial genomes that must interact functionally and physically in a precisely coordinated manner. Consequently, mito-nuclear allelic interactions are thought to be of crucial importance on an evolutionary scale, as well as for manifestation of essential biological phenotypes, including those directly relevant to human disease. Nonetheless, detailed molecular understanding of mito-nuclear interactions is still lacking, and definitive examples of such interactions in vivo are sparse. Here we describe the characterization of a mutation in Drosophila ND23 , a nuclear gene encoding a highly conserved subunit of mitochondrial complex 1. This characterization led to the discovery of a mito-nuclear interaction that affects the ND23 mutant phenotype. ND23 mutants exhibit reduced lifespan, neurodegeneration, abnormal mitochondrial morphology, and decreased ATP levels. These phenotypes are similar to those observed in patients with Leigh syndrome, which is caused by mutations in a number of nuclear genes that encode mitochondrial proteins, including the human ortholog of ND23 A key feature of Leigh syndrome, and other mitochondrial disorders, is unexpected and unexplained phenotypic variability. We discovered that the phenotypic severity of ND23 mutations varies depending on the maternally inherited mitochondrial background. Sequence analysis of the relevant mitochondrial genomes identified several variants that are likely candidates for the phenotypic interaction with mutant ND23 , including a variant affecting a mitochondrially encoded component of complex I. Thus, our work provides an in vivo demonstration of the phenotypic importance of mito-nuclear interactions in the context of mitochondrial disease. Copyright © 2018 by the Genetics Society of America.

Two distinct phenotypes of asthma in elite athletes identified by latent class analysis.

PubMed

Couto, Mariana; Stang, Julie; Horta, Luís; Stensrud, Trine; Severo, Milton; Mowinckel, Petter; Silva, Diana; Delgado, Luís; Moreira, André; Carlsen, Kai-Håkon

2015-01-01

Clusters of asthma in athletes have been insufficiently studied. Therefore, the present study aimed to characterize asthma phenotypes in elite athletes using latent class analysis (LCA) and to evaluate its association with the type of sport practiced. In the present cross-sectional study, an analysis of athletes' records was carried out in databases of the Portuguese National Anti-Doping Committee and the Norwegian School of Sport Sciences. Athletes with asthma, diagnosed according to criteria given by the International Olympic Committee, were included for LCA. Sports practiced were categorized into water, winter and other sports. Of 324 files screened, 150 files belonged to asthmatic athletes (91 Portuguese; 59 Norwegian). LCA retrieved two clusters: "atopic asthma" defined by allergic sensitization, rhinitis and allergic co-morbidities and increased exhaled nitric oxide levels; and "sports asthma", defined by exercise-induced respiratory symptoms and airway hyperesponsiveness without allergic features. The risk of developing the phenotype "sports asthma" was significantly increased in athletes practicing water (OR = 2.87; 95% CI [1.82-4.51]) and winter (OR = 8.65; 95% CI [2.67-28.03]) sports, when compared with other athletes. Two asthma phenotypes were identified in elite athletes: "atopic asthma" and "sports asthma". The type of sport practiced was associated with different phenotypes: water and winter sport athletes had three- and ninefold increased risk of "sports asthma". Recognizing different phenotypes is clinically relevant as it would lead to distinct targeted treatments.

Detection of Rare Antimicrobial Resistance Profiles by Active and Passive Surveillance Approaches

PubMed Central

Mather, Alison E.; Reeve, Richard; Mellor, Dominic J.; Matthews, Louise; Reid-Smith, Richard J.; Haydon, Daniel T.; Reid, Stuart W. J.

2016-01-01

Antimicrobial resistance (AMR) surveillance systems are generally not specifically designed to detect emerging resistances and usually focus primarily on resistance to individual drugs. Evaluating the diversity of resistance, using ecological metrics, allows the assessment of sampling protocols with regard to the detection of rare phenotypes, comprising combinations of resistances. Surveillance data of phenotypic AMR of Canadian poultry Salmonella Heidelberg and swine Salmonella Typhimurium var. 5- were used to contrast active (representative isolates derived from healthy animals) and passive (diagnostic isolates) surveillance and assess their suitability for detecting emerging resistance patterns. Although in both datasets the prevalences of resistance to individual antimicrobials were not significantly different between the two surveillance systems, analysis of the diversity of entire resistance phenotypes demonstrated that passive surveillance of diagnostic isolates detected more unique phenotypes. Whilst the most appropriate surveillance method will depend on the relevant objectives, under the conditions of this study, passive surveillance of diagnostic isolates was more effective for the detection of rare and therefore potentially emerging resistance phenotypes. PMID:27391966

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of Cerebrotendinous xanthomatosis.

PubMed

Taboada, María; Martínez, Diego; Pilo, Belén; Jiménez-Escrig, Adriano; Robinson, Peter N; Sobrido, María J

2012-07-31

Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies. A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption. This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research.

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

PubMed

Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

2010-04-01

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

EuroPhenome: a repository for high-throughput mouse phenotyping data

PubMed Central

Morgan, Hugh; Beck, Tim; Blake, Andrew; Gates, Hilary; Adams, Niels; Debouzy, Guillaume; Leblanc, Sophie; Lengger, Christoph; Maier, Holger; Melvin, David; Meziane, Hamid; Richardson, Dave; Wells, Sara; White, Jacqui; Wood, Joe; de Angelis, Martin Hrabé; Brown, Steve D. M.; Hancock, John M.; Mallon, Ann-Marie

2010-01-01

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies. PMID:19933761

Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast

PubMed Central

Oud, Bart; Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

2012-01-01

Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. PMID:22152095

Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast.

PubMed

Oud, Bart; van Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

2012-03-01

Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Development and evaluation of a Quadruplex Taq Man real-time PCR assay for simultaneous detection of clinical isolates of Enterococcus faecalis, Enterococcus faecium and their vanA and vanB genotypes.

PubMed

Naserpour Farivar, Taghi; Najafipour, Reza; Johari, Pouran; Aslanimehr, Masoumeh; Peymani, Amir; Jahani Hashemi, Hoasan; Mirzaui, Baman

2014-10-01

We developed and evaluated the utility of a quadruplex Taqman real-time PCR assay that allows simultaneous identification of vancomycin-resistant genotypes and clinically relevant enterococci. The specificity of the assay was tested using reference strains of vancomycin-resistant and susceptible enterococci. In total, 193 clinical isolates were identified and subsequently genotyped using a Quadruplex Taqman real-time PCR assay and melting curve analysis. Representative Quadruplex Taqman real-time PCR amplification curve were obtained for Enterococcus faecium, Enterococcus faecalis, vanA-containing E. faecium, vanB-containing E. faecalis. Phenotypic and genotypic analysis of the isolates gave same results for 82 enterococcal isolates, while in 5 isolates, they were inconsistent. We had three mixed strains, which were detected by the TaqMan real-time PCR assay and could not be identified correctly using phenotypic methods. Vancomycin resistant enterococci (VRE) genotyping and identification of clinically relevant enterococci were rapidly and correctly performed using TaqMan real-time multiplex real-time PCR assay.

Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes

PubMed Central

Bray, Mark-Anthony; Singh, Shantanu; Han, Han; Davis, Chadwick T.; Borgeson, Blake; Hartland, Cathy; Kost-Alimova, Maria; Gustafsdottir, Sigrun M.; Gibson, Christopher C.; Carpenter, Anne E.

2016-01-01

In morphological profiling, quantitative data are extracted from microscopy images of cells to identify biologically relevant similarities and differences among samples based on these profiles. This protocol describes the design and execution of experiments using Cell Painting, a morphological profiling assay multiplexing six fluorescent dyes imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multi-well plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Then, automated image analysis software identifies individual cells and measures ~1,500 morphological features (various measures of size, shape, texture, intensity, etc.) to produce a rich profile suitable for detecting subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. Cell culture and image acquisition takes two weeks; feature extraction and data analysis take an additional 1-2 weeks. PMID:27560178

Latent class analysis reveals clinically relevant atopy phenotypes in 2 birth cohorts.

PubMed

Hose, Alexander J; Depner, Martin; Illi, Sabina; Lau, Susanne; Keil, Thomas; Wahn, Ulrich; Fuchs, Oliver; Pfefferle, Petra Ina; Schmaußer-Hechfellner, Elisabeth; Genuneit, Jon; Lauener, Roger; Karvonen, Anne M; Roduit, Caroline; Dalphin, Jean-Charles; Riedler, Josef; Pekkanen, Juha; von Mutius, Erika; Ege, Markus J

2017-06-01

Phenotypes of childhood-onset asthma are characterized by distinct trajectories and functional features. For atopy, definition of phenotypes during childhood is less clear. We sought to define phenotypes of atopic sensitization over the first 6 years of life using a latent class analysis (LCA) integrating 3 dimensions of atopy: allergen specificity, time course, and levels of specific IgE (sIgE). Phenotypes were defined by means of LCA in 680 children of the Multizentrische Allergiestudie (MAS) and 766 children of the Protection against allergy: Study in Rural Environments (PASTURE) birth cohorts and compared with classical nondisjunctive definitions of seasonal, perennial, and food sensitization with respect to atopic diseases and lung function. Cytokine levels were measured in the PASTURE cohort. The LCA classified predominantly by type and multiplicity of sensitization (food vs inhalant), allergen combinations, and sIgE levels. Latent classes were related to atopic disease manifestations with higher sensitivity and specificity than the classical definitions. LCA detected consistently in both cohorts a distinct group of children with severe atopy characterized by high seasonal sIgE levels and a strong propensity for asthma; hay fever; eczema; and impaired lung function, also in children without an established asthma diagnosis. Severe atopy was associated with an increased IL-5/IFN-γ ratio. A path analysis among sensitized children revealed that among all features of severe atopy, only excessive sIgE production early in life affected asthma risk. LCA revealed a set of benign, symptomatic, and severe atopy phenotypes. The severe phenotype emerged as a latent condition with signs of a dysbalanced immune response. It determined high asthma risk through excessive sIgE production and directly affected impaired lung function. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Mothers' appreciation of chromosomal microarray analysis for autism spectrum disorder.

PubMed

Giarelli, Ellen; Reiff, Marian

2015-10-01

The aim of this study was to examine mothers' experiences with chromosomal microarray analysis (CMA) for a child with autism spectrum disorder (ASD). This is a descriptive qualitative study using thematic content analysis of in-depth interview with 48 mothers of children who had genetic testing for ASD. The principal theme, "something is missing," included missing knowledge about genetics, information on use of the results, explanations of the relevance to the diagnosis, and relevance to life-long care. Two subordinate themes were (a) disappreciation of the helpfulness of scientific information to explain the diagnosis, and (b) returning to personal experience for interpretation. The test "appreciated" in value when results could be linked to the phenotype. © 2015, Wiley Periodicals, Inc.

GEAR: genomic enrichment analysis of regional DNA copy number changes.

PubMed

Kim, Tae-Min; Jung, Yu-Chae; Rhyu, Mun-Gan; Jung, Myeong Ho; Chung, Yeun-Jun

2008-02-01

We developed an algorithm named GEAR (genomic enrichment analysis of regional DNA copy number changes) for functional interpretation of genome-wide DNA copy number changes identified by array-based comparative genomic hybridization. GEAR selects two types of chromosomal alterations with potential biological relevance, i.e. recurrent and phenotype-specific alterations. Then it performs functional enrichment analysis using a priori selected functional gene sets to identify primary and clinical genomic signatures. The genomic signatures identified by GEAR represent functionally coordinated genomic changes, which can provide clues on the underlying molecular mechanisms related to the phenotypes of interest. GEAR can help the identification of key molecular functions that are activated or repressed in the tumor genomes leading to the improved understanding on the tumor biology. GEAR software is available with online manual in the website, http://www.systemsbiology.co.kr/GEAR/.

A platform for high-throughput bioenergy production phenotype characterization in single cells

PubMed Central

Kelbauskas, Laimonas; Glenn, Honor; Anderson, Clifford; Messner, Jacob; Lee, Kristen B.; Song, Ganquan; Houkal, Jeff; Su, Fengyu; Zhang, Liqiang; Tian, Yanqing; Wang, Hong; Bussey, Kimberly; Johnson, Roger H.; Meldrum, Deirdre R.

2017-01-01

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers. PMID:28349963

Exome Sequencing in the Clinical Diagnosis of Sporadic or Familial Cerebellar Ataxia

PubMed Central

Fogel, Brent L.; Lee, Hane; Deignan, Joshua L.; Strom, Samuel P.; Kantarci, Sibel; Wang, Xizhe; Quintero-Rivera, Fabiola; Vilain, Eric; Grody, Wayne W.; Perlman, Susan; Geschwind, Daniel H.; Nelson, Stanley F.

2015-01-01

IMPORTANCE Cerebellar ataxias are a diverse collection of neurologic disorders with causes ranging from common acquired etiologies to rare genetic conditions. Numerous genetic disorders have been associated with chronic progressive ataxia and this consequently presents a diagnostic challenge for the clinician regarding how to approach and prioritize genetic testing in patients with such clinically heterogeneous phenotypes. Additionally, while the value of genetic testing in early-onset and/or familial cases seems clear, many patients with ataxia present sporadically with adult onset of symptoms and the contribution of genetic variation to the phenotype of these patients has not yet been established. OBJECTIVE To investigate the contribution of genetic disease in a population of patients with predominantly adult- and sporadic-onset cerebellar ataxia. DESIGN, SETTING, AND PARTICIPANTS We examined a consecutive series of 76 patients presenting to a tertiary referral center for evaluation of chronic progressive cerebellar ataxia. MAIN OUTCOMES AND MEASURES Next-generation exome sequencing coupled with comprehensive bioinformatic analysis, phenotypic analysis, and clinical correlation. RESULTS We identified clinically relevant genetic information in more than 60% of patients studied (n = 46), including diagnostic pathogenic gene variants in 21% (n = 16), a notable yield given the diverse genetics and clinical heterogeneity of the cerebellar ataxias. CONCLUSIONS AND RELEVANCE This study demonstrated that clinical exome sequencing in patients with adult-onset and sporadic presentations of ataxia is a high-yield test, providing a definitive diagnosis in more than one-fifth of patients and suggesting a potential diagnosis in more than one-third to guide additional phenotyping and diagnostic evaluation. Therefore, clinical exome sequencing is an appropriate consideration in the routine genetic evaluation of all patients presenting with chronic progressive cerebellar ataxia. PMID:25133958

Microbial genotype-phenotype mapping by class association rule mining.

PubMed

Tamura, Makio; D'haeseleer, Patrik

2008-07-01

Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11,969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. Supplementary data are available at Bioinformatics online.

Phenotypic and genotypic analysis of anti-tuberculosis drug resistance in Mycobacterium tuberculosis isolates in Myanmar.

PubMed

Aung, Wah Wah; Ei, Phyu Win; Nyunt, Wint Wint; Swe, Thyn Lei; Lwin, Thandar; Htwe, Mi Mi; Kim, Kyung Jun; Lee, Jong Seok; Kim, Chang Ki; Cho, Sang Nae; Song, Sun Dae; Chang, Chulhun L

2015-09-01

Tuberculosis (TB) is one of the most serious health problems in Myanmar. Because TB drug resistance is associated with genetic mutation(s) relevant to responses to each drug, genotypic methods for detecting these mutations have been proposed to overcome the limitations of classic phenotypic drug susceptibility testing (DST). We explored the current estimates of drug-resistant TB and evaluated the usefulness of genotypic DST in Myanmar. We determined the drug susceptibility of Mycobacterium tuberculosis isolated from sputum smear-positive patients with newly diagnosed pulmonary TB at two main TB centers in Myanmar during 2013 by using conventional phenotypic DST and the GenoType MTBDRplus assay (Hain Lifescience, Germany). Discrepant results were confirmed by sequencing the genes relevant to each type of resistance (rpoB for rifampicin; katG and inhA for isoniazid). Of 191 isolates, phenotypic DST showed that 27.7% (n=53) were resistant to at least one first-line drug and 20.9% (n=40) were resistant to two or more, including 18.3% (n=35) multidrug-resistant TB (MDR-TB) strains. Monoresistant strains accounted for 6.8% (n=13) of the samples. Genotypic assay of 189 isolates showed 17.5% (n=33) MDR-TB and 5.3% (n=10) isoniazid-monoresistant strains. Genotypic susceptibility results were 99.5% (n=188) concordant and agreed almost perfectly with phenotypic DST (kappa=0.99; 95% confidence interval 0.96-1.01). The results highlight the burden of TB drug resistance and prove the usefulness of the genotypic DST in Myanmar.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation

PubMed Central

Hawes, Norman L.; Trantow, Colleen M.; Chang, Bo; John, Simon W.M.

2010-01-01

Summary Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among sixteen mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease. PMID:18715234

Iris phenotypes and pigment dispersion caused by genes influencing pigmentation.

PubMed

Anderson, Michael G; Hawes, Norman L; Trantow, Colleen M; Chang, Bo; John, Simon W M

2008-10-01

Spontaneous mutations altering mouse coat colors have been a classic resource for discovery of numerous molecular pathways. Although often overlooked, the mouse iris is also densely pigmented and easily observed, thus representing a similarly powerful opportunity for studying pigment cell biology. Here, we present an analysis of iris phenotypes among 16 mouse strains with mutations influencing melanosomes. Many of these strains exhibit biologically and medically relevant phenotypes, including pigment dispersion, a common feature of several human ocular diseases. Pigment dispersion was identified in several strains with mutant alleles known to influence melanosomes, including beige, light, and vitiligo. Pigment dispersion was also detected in the recently arising spontaneous coat color variant, nm2798. We have identified the nm2798 mutation as a missense mutation in the Dct gene, an identical re-occurrence of the slaty light mutation. These results suggest that dysregulated events of melanosomes can be potent contributors to the pigment dispersion phenotype. Combined, these findings illustrate the utility of studying iris phenotypes as a means of discovering new pathways, and re-linking old ones, to processes of pigmented cells in health and disease.

Pancreatic Autoantibodies Against CUZD1 and GP2 Are Associated with Distinct Clinical Phenotypes of Crohn's Disease.

PubMed

Michaels, Maike Anna; Jendrek, Sebastian Torben; Korf, Tobias; Nitzsche, Thomas; Teegen, Bianca; Komorowski, Lars; Derer, Stefanie; Schröder, Torsten; Baer, Florian; Lehnert, Henrik; Büning, Jürgen; Fellerman, Klaus; Sina, Christian

2015-12-01

Inflammatory bowel disease (IBD) is characterized by a broad spectrum of clinical phenotypes with different outcomes. In the last decades, several IBD-associated autoantibodies have been identified and investigated for their diagnostic relevance. Autoantibodies against the pancreatic glycoproteins (PAB) CUB and zona pellucida-like domains-containing protein 1 (CUZD1), and glycoprotein 2 (GP2) have been demonstrated to possess high specificity for the diagnosis of IBD. Although several studies have shown significant interrelations of anti-GP2 positivity with disease phenotype, associations of clinical phenotypes with anti-CUZD1 are still unknown. The aim was to identify the association of clinical phenotypes with anti-CUZD1 and anti-GP2 in a well-defined German IBD cohort. Patients with IBD (224 patients with Crohn's disease and 136 patients with ulcerative colitis), who were tested for anti-GP2 and anti-CUZD1 immunoglobulin G and immunoglobulin A by indirect immunofluorescence on transfected cells between 2005 and 2013, were included. Serotype and specified phenotypic data were collected in retrospect and statistically analyzed. Both anti-GP2 (P < 0.001) and anti-CUZD1 (P < 0.001) were significantly more prevalent in patients with Crohn's disease than in ulcerative colitis. PAB positivity was associated with ileocolonic disease (P = 0.002), perianal disease (P = 0.011), immunosuppressive treatment (P = 0.036), and ASCA positivity (P = 0.036). Anti-CUZD1 positivity was associated with ileocolonic (P = 0.016) and perianal disease (P = 0.002), whereas anti-GP2 positivity was positively associated with stricturing behavior (P = 0.016). We found distinct clinical phenotypes to be associated with PAB positivity. Therefore, determination of PABs and their subgroup analysis might identify patients with complicated disease behavior. However, the clinical relevance of our findings should be further evaluated in prospective cohorts.

Novel clustering of items from the Autism Diagnostic Interview-Revised to define phenotypes within autism spectrum disorders

PubMed Central

Hu, Valerie W.; Steinberg, Mara E.

2009-01-01

Heterogeneity in phenotypic presentation of ASD has been cited as one explanation for the difficulty in pinpointing specific genes involved in autism. Recent studies have attempted to reduce the “noise” in genetic and other biological data by reducing the phenotypic heterogeneity of the sample population. The current study employs multiple clustering algorithms on 123 item scores from the Autism Diagnostic Interview-Revised (ADI-R) diagnostic instrument of nearly 2000 autistic individuals to identify subgroups of autistic probands with clinically relevant behavioral phenotypes in order to isolate more homogeneous groups of subjects for gene expression analyses. Our combined cluster analyses suggest optimal division of the autistic probands into 4 phenotypic clusters based on similarity of symptom severity across the 123 selected item scores. One cluster is characterized by severe language deficits, while another exhibits milder symptoms across the domains. A third group possesses a higher frequency of savant skills while the fourth group exhibited intermediate severity across all domains. Grouping autistic individuals by multivariate cluster analysis of ADI-R scores reveals meaningful phenotypes of subgroups within the autistic spectrum which we show, in a related (accompanying) study, to be associated with distinct gene expression profiles. PMID:19455643

Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of cerebrotendinous xanthomatosis

PubMed Central

2012-01-01

Background Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. Methods Due to the current availability of ontological and terminological resources that have already reached some consensus in biomedicine, a reuse-based ontology engineering approach was followed. The proposed approach uses the Ontology Web Language (OWL) to represent the phenotype ontology and the patient model, the Semantic Web Rule Language (SWRL) to bridge the gap between phenotype descriptions and clinical data, and the Semantic Query Web Rule Language (SQWRL) to query relevant phenotype-genotype bidirectional relationships. The work tests the use of semantic web technology in the biomedical research domain named cerebrotendinous xanthomatosis (CTX), using a real dataset and ontologies. Results A framework to query relevant phenotype-genotype bidirectional relationships is provided. Phenotype descriptions and patient data were harmonized by defining 28 Horn-like rules in terms of the OWL concepts. In total, 24 patterns of SWQRL queries were designed following the initial list of competency questions. As the approach is based on OWL, the semantic of the framework adapts the standard logical model of an open world assumption. Conclusions This work demonstrates how semantic web technologies can be used to support flexible representation and computational inference mechanisms required to query patient datasets at different levels of abstraction. The open world assumption is especially good for describing only partially known phenotype-genotype relationships, in a way that is easily extensible. In future, this type of approach could offer researchers a valuable resource to infer new data from patient data for statistical analysis in translational research. In conclusion, phenotype description formalization and mapping to clinical data are two key elements for interchanging knowledge between basic and clinical research. PMID:22849591

Open innovation for phenotypic drug discovery: The PD2 assay panel.

PubMed

Lee, Jonathan A; Chu, Shaoyou; Willard, Francis S; Cox, Karen L; Sells Galvin, Rachelle J; Peery, Robert B; Oliver, Sarah E; Oler, Jennifer; Meredith, Tamika D; Heidler, Steven A; Gough, Wendy H; Husain, Saba; Palkowitz, Alan D; Moxham, Christopher M

2011-07-01

Phenotypic lead generation strategies seek to identify compounds that modulate complex, physiologically relevant systems, an approach that is complementary to traditional, target-directed strategies. Unlike gene-specific assays, phenotypic assays interrogate multiple molecular targets and signaling pathways in a target "agnostic" fashion, which may reveal novel functions for well-studied proteins and discover new pathways of therapeutic value. Significantly, existing compound libraries may not have sufficient chemical diversity to fully leverage a phenotypic strategy. To address this issue, Eli Lilly and Company launched the Phenotypic Drug Discovery Initiative (PD(2)), a model of open innovation whereby external research groups can submit compounds for testing in a panel of Lilly phenotypic assays. This communication describes the statistical validation, operations, and initial screening results from the first PD(2) assay panel. Analysis of PD(2) submissions indicates that chemical diversity from open source collaborations complements internal sources. Screening results for the first 4691 compounds submitted to PD(2) have confirmed hit rates from 1.6% to 10%, with the majority of active compounds exhibiting acceptable potency and selectivity. Phenotypic lead generation strategies, in conjunction with novel chemical diversity obtained via open-source initiatives such as PD(2), may provide a means to identify compounds that modulate biology by novel mechanisms and expand the innovation potential of drug discovery.

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

PubMed

Antanaviciute, Agne; Watson, Christopher M; Harrison, Sally M; Lascelles, Carolina; Crinnion, Laura; Markham, Alexander F; Bonthron, David T; Carr, Ian M

2015-12-01

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. Supplementary data are available at Bioinformatics online. umaan@leeds.ac.uk. © The Author 2015. Published by Oxford University Press.

Genomic regions underlying susceptibility to bovine tuberculosis in Holstein-Friesian cattle.

PubMed

Raphaka, Kethusegile; Matika, Oswald; Sánchez-Molano, Enrique; Mrode, Raphael; Coffey, Mike Peter; Riggio, Valentina; Glass, Elizabeth Janet; Woolliams, John Arthur; Bishop, Stephen Christopher; Banos, Georgios

2017-03-23

The significant social and economic loss as a result of bovine tuberculosis (bTB) presents a continuous challenge to cattle industries in the UK and worldwide. However, host genetic variation in cattle susceptibility to bTB provides an opportunity to select for resistant animals and further understand the genetic mechanisms underlying disease dynamics. The present study identified genomic regions associated with susceptibility to bTB using genome-wide association (GWA), regional heritability mapping (RHM) and chromosome association approaches. Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires and pertained to three bTB indicator traits: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin tests with positive post-mortem examination results (phenotype 3). Genotypes based on the 50 K SNP DNA array were available and a total of 34,874 SNPs remained per animal after quality control. The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWA analysis identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB. Genomic regions and candidate genes identified in the present study provide an opportunity to further understand pathways critical to cattle susceptibility to bTB and enhance genetic improvement programmes aiming at controlling and eradicating the disease.

DNA methylation analysis of phenotype specific stratified Indian population.

PubMed

Rotti, Harish; Mallya, Sandeep; Kabekkodu, Shama Prasada; Chakrabarty, Sanjiban; Bhale, Sameer; Bharadwaj, Ramachandra; Bhat, Balakrishna K; Dedge, Amrish P; Dhumal, Vikram Ram; Gangadharan, G G; Gopinath, Puthiya M; Govindaraj, Periyasamy; Joshi, Kalpana S; Kondaiah, Paturu; Nair, Sreekumaran; Nair, S N Venugopalan; Nayak, Jayakrishna; Prasanna, B V; Shintre, Pooja; Sule, Mayura; Thangaraj, Kumarasamy; Patwardhan, Bhushan; Valiathan, Marthanda Varma Sankaran; Satyamoorthy, Kapaettu

2015-05-08

DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

Patterns of population structure and environmental associations to aridity across the range of loblolly pine (Pinus taeda L., Pinaceae).

PubMed

Eckert, Andrew J; van Heerwaarden, Joost; Wegrzyn, Jill L; Nelson, C Dana; Ross-Ibarra, Jeffrey; González-Martínez, Santíago C; Neale, David B

2010-07-01

Natural populations of forest trees exhibit striking phenotypic adaptations to diverse environmental gradients, thereby making them appealing subjects for the study of genes underlying ecologically relevant phenotypes. Here, we use a genome-wide data set of single nucleotide polymorphisms genotyped across 3059 functional genes to study patterns of population structure and identify loci associated with aridity across the natural range of loblolly pine (Pinus taeda L.). Overall patterns of population structure, as inferred using principal components and Bayesian cluster analyses, were consistent with three genetic clusters likely resulting from expansions out of Pleistocene refugia located in Mexico and Florida. A novel application of association analysis, which removes the confounding effects of shared ancestry on correlations between genetic and environmental variation, identified five loci correlated with aridity. These loci were primarily involved with abiotic stress response to temperature and drought. A unique set of 24 loci was identified as F(ST) outliers on the basis of the genetic clusters identified previously and after accounting for expansions out of Pleistocene refugia. These loci were involved with a diversity of physiological processes. Identification of nonoverlapping sets of loci highlights the fundamental differences implicit in the use of either method and suggests a pluralistic, yet complementary, approach to the identification of genes underlying ecologically relevant phenotypes.

Applying Quantitative Genetic Methods to Primate Social Behavior

PubMed Central

Brent, Lauren J. N.

2013-01-01

Increasingly, behavioral ecologists have applied quantitative genetic methods to investigate the evolution of behaviors in wild animal populations. The promise of quantitative genetics in unmanaged populations opens the door for simultaneous analysis of inheritance, phenotypic plasticity, and patterns of selection on behavioral phenotypes all within the same study. In this article, we describe how quantitative genetic techniques provide studies of the evolution of behavior with information that is unique and valuable. We outline technical obstacles for applying quantitative genetic techniques that are of particular relevance to studies of behavior in primates, especially those living in noncaptive populations, e.g., the need for pedigree information, non-Gaussian phenotypes, and demonstrate how many of these barriers are now surmountable. We illustrate this by applying recent quantitative genetic methods to spatial proximity data, a simple and widely collected primate social behavior, from adult rhesus macaques on Cayo Santiago. Our analysis shows that proximity measures are consistent across repeated measurements on individuals (repeatable) and that kin have similar mean measurements (heritable). Quantitative genetics may hold lessons of considerable importance for studies of primate behavior, even those without a specific genetic focus. PMID:24659839

Identifying drought adaptive traits in upland cotton using a proximal sensing cart for high-throughput phenotyping

USDA-ARS?s Scientific Manuscript database

Field-based high-throughput phenotyping is an emerging approach to characterize difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts have been developed as an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the fi...

Whole genome sequencing of one complex pedigree illustrates challenges with genomic medicine.

PubMed

Fang, Han; Wu, Yiyang; Yang, Hui; Yoon, Margaret; Jiménez-Barrón, Laura T; Mittelman, David; Robison, Reid; Wang, Kai; Lyon, Gholson J

2017-02-23

Human Phenotype Ontology (HPO) has risen as a useful tool for precision medicine by providing a standardized vocabulary of phenotypic abnormalities to describe presentations of human pathologies; however, there have been relatively few reports combining whole genome sequencing (WGS) and HPO, especially in the context of structural variants. We illustrate an integrative analysis of WGS and HPO using an extended pedigree, which involves Prader-Willi Syndrome (PWS), hereditary hemochromatosis (HH), and dysautonomia-like symptoms. A comprehensive WGS pipeline was used to ensure reliable detection of genomic variants. Beyond variant filtering, we pursued phenotypic prioritization of candidate genes using Phenolyzer. Regarding PWS, WGS confirmed a 5.5 Mb de novo deletion of the parental allele at 15q11.2 to 15q13.1. Phenolyzer successfully returned the diagnosis of PWS, and pinpointed clinically relevant genes in the deletion. Further, Phenolyzer revealed how each of the genes is linked with the phenotypes represented by HPO terms. For HH, WGS identified a known disease variant (p.C282Y) in HFE of an affected female. Analysis of HPO terms alone fails to provide a correct diagnosis, but Phenolyzer successfully revealed the phenotype-genotype relationship using a disease-centric approach. Finally, Phenolyzer also revealed the complexity behind dysautonomia-like symptoms, and seven variants that might be associated with the phenotypes were identified by manual filtering based on a dominant inheritance model. The integration of WGS and HPO can inform comprehensive molecular diagnosis for patients, eliminate false positives and reveal novel insights into undiagnosed diseases. Due to extreme heterogeneity and insufficient knowledge of human diseases, it is also important that phenotypic and genomic data are standardized and shared simultaneously.

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Comparative Proteome Analysis of the Tuberous Roots of Six Cassava (Manihot esculenta) Varieties Reveals Proteins Related to Phenotypic Traits.

PubMed

Schmitz, Gabriela Justamante Händel; de Magalhães Andrade, Jonathan; Valle, Teresa Losada; Labate, Carlos Alberto; do Nascimento, João Roberto Oliveira

2016-04-27

Cassava (Manihot esculenta Crantz) is a staple food and an important source of starch, and the attributes of its tuberous root largely depend on the variety. The proteome of cassava has been investigated; however, to date, no study has focused on varieties that reveal the molecular basis of phenotypical characteristics. Therefore, we aimed to compare the proteome of the tuberous roots of six cassava varieties that differed in carbohydrates, carotenoids, and resistance to diseases, among other attributes. Two-dimensional gels showed 146 differential spots between the varieties, and the functional roles of some differential proteins were correlated to phenotypic characteristics of the varieties, such as the amount of carbohydrates or carotenoids and the resistance to biotic or abiotic stresses. The results obtained here highlight elements that might help to direct the improvement of new cultivars of cassava, which is an economically and socially relevant crop worldwide.

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

PubMed

Abee, T; Koomen, J; Metselaar, K I; Zwietering, M H; den Besten, H M W

2016-01-01

This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

Recent advances in the evolutionary engineering of industrial biocatalysts.

PubMed

Winkler, James D; Kao, Katy C

2014-12-01

Evolutionary engineering has been used to improve key industrial strain traits, such as carbon source utilization, tolerance to adverse environmental conditions, and resistance to chemical inhibitors, for many decades due to its technical simplicity and effectiveness. The lack of need for prior genetic knowledge underlying the phenotypes of interest makes this a powerful approach for strain development for even species with minimal genotypic information. While the basic experimental procedure for laboratory adaptive evolution has remained broadly similar for many years, a range of recent advances show promise for improving the experimental workflows for evolutionary engineering by accelerating the pace of evolution, simplifying the analysis of evolved mutants, and providing new ways of linking desirable phenotypes to selectable characteristics. This review aims to highlight some of these recent advances and discuss how they may be used to improve industrially relevant microbial phenotypes. Copyright © 2014 Elsevier Inc. All rights reserved.

Exploring Genetic Attributions Underlying Radiotherapy-Induced Fatigue in Prostate Cancer Patients.

PubMed

Hashemi, Sepehr; Fernandez Martinez, Juan Luis; Saligan, Leorey; Sonis, Stephen

2017-09-01

Despite numerous proposed mechanisms, no definitive pathophysiology underlying radiotherapy-induced fatigue (RIF) has been established. However, the dysregulation of a set of 35 genes was recently validated to predict development of fatigue in prostate cancer patients receiving radiotherapy. To hypothesize novel pathways, and provide genetic targets for currently proposed pathways implicated in RIF development through analysis of the previously validated gene set. The gene set was analyzed for all phenotypic attributions implicated in the phenotype of fatigue. Initially, a "directed" approach was used by querying specific fatigue-related sub-phenotypes against all known phenotypic attributions of the gene set. Then, an "undirected" approach, reviewing the entirety of the literature referencing the 35 genes, was used to increase analysis sensitivity. The dysregulated genes attribute to neural, immunological, mitochondrial, muscular, and metabolic pathways. In addition, certain genes suggest phenotypes not previously emphasized in the context of RIF, such as ionizing radiation sensitivity, DNA damage, and altered DNA repair frequency. Several genes also associated with prostate cancer depression, possibly emphasizing variable radiosensitivity by RIF-prone patients, which may have palliative care implications. Despite the relevant findings, many of the 35 RIF-predictive genes are poorly characterized, warranting their investigation. The implications of herein presented RIF pathways are purely theoretical until specific end-point driven experiments are conducted in more congruent contexts. Nevertheless, the presented attributions are informative, directing future investigation to definitively elucidate RIF's pathoetiology. This study demonstrates an arguably comprehensive method of approaching known differential expression underlying a complex phenotype, to correlate feasible pathophysiology. Copyright © 2017 American Academy of Hospice and Palliative Medicine. All rights reserved.

Active Learning Strategies for Phenotypic Profiling of High-Content Screens.

PubMed

Smith, Kevin; Horvath, Peter

2014-06-01

High-content screening is a powerful method to discover new drugs and carry out basic biological research. Increasingly, high-content screens have come to rely on supervised machine learning (SML) to perform automatic phenotypic classification as an essential step of the analysis. However, this comes at a cost, namely, the labeled examples required to train the predictive model. Classification performance increases with the number of labeled examples, and because labeling examples demands time from an expert, the training process represents a significant time investment. Active learning strategies attempt to overcome this bottleneck by presenting the most relevant examples to the annotator, thereby achieving high accuracy while minimizing the cost of obtaining labeled data. In this article, we investigate the impact of active learning on single-cell-based phenotype recognition, using data from three large-scale RNA interference high-content screens representing diverse phenotypic profiling problems. We consider several combinations of active learning strategies and popular SML methods. Our results show that active learning significantly reduces the time cost and can be used to reveal the same phenotypic targets identified using SML. We also identify combinations of active learning strategies and SML methods which perform better than others on the phenotypic profiling problems we studied. © 2014 Society for Laboratory Automation and Screening.

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

[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.

Identification of clinically relevant phenotypes in patients with Ebstein anomaly.

PubMed

Cabrera, Rodrigo; Miranda-Fernández, Marta Catalina; Huertas-Quiñones, Victor Manuel; Carreño, Marisol; Pineda, Ivonne; Restrepo, Carlos M; Silva, Claudia Tamar; Quero, Rossi; Cano, Juan David; Manrique, Diana Carolina; Camacho, Camila; Tabares, Sebastián; García, Alberto; Sandoval, Néstor; Moreno Medina, Karen Julieth; Dennis Verano, Rodolfo José

2018-03-01

Ebstein anomaly (EA) is a heterogeneous congenital heart defect (CHD), frequently accompanied by diverse cardiac and extracardiac comorbidities, resulting in a wide range of clinical outcomes. Phenotypic characterization of EA patients has the potential to identify variables that influence prognosis and subgroups with distinct contributing factors. A comprehensive cross-sectional phenotypic characterization of 147 EA patients from one of the main referral institutions for CHD in Colombia was carried out. The most prevalent comorbidities and distinct subgroups within the patient cohort were identified through cluster analysis. The most prevalent cardiac comorbidities identified were atrial septal defect (61%), Wolff-Parkinson-White syndrome (WPW; 27%), and right ventricular outflow tract obstruction (25%). Cluster analysis showed that patients can be classified into 2 distinct subgroups with defined phenotypes that determine disease severity and survival. Patients in cluster 1 represented a particularly homogeneous subgroup with a milder spectrum of disease, including only patients with WPW and/or supraventricular tachycardia (SVT). Cluster 2 included patients with more diverse cardiovascular comorbidities. This study represents one of the largest phenotypic characterizations of EA patients reported. The data show that EA is a heterogeneous disease, very frequently associated with cardiovascular and noncardiovascular comorbidities. Patients with WPW and SVT represent a homogeneous subgroup that presents with a less severe spectrum of disease and better survival when adequately managed. This should be considered when searching for genetic causes of EA and in the clinical setting. © 2018 Wiley Periodicals, Inc.

The Cording Phenotype of Mycobacterium tuberculosis Induces the Formation of Extracellular Traps in Human Macrophages.

PubMed

Kalsum, Sadaf; Braian, Clara; Koeken, Valerie A C M; Raffetseder, Johanna; Lindroth, Margaretha; van Crevel, Reinout; Lerm, Maria

2017-01-01

The causative agent of tuberculosis, Mycobacterium tuberculosis , shares several characteristics with organisms that produce biofilms during infections. One of these is the ability to form tight bundles also known as cords. However, little is known of the physiological relevance of the cording phenotype. In this study, we investigated whether cord-forming M. tuberculosis induce the formation of macrophage extracellular traps (METs) in human monocyte-derived macrophages. Macrophages have previously been shown to produce extracellular traps in response to various stimuli. We optimized bacterial culturing conditions that favored the formation of the cord-forming phenotype as verified by scanning electron microscopy. Microscopy analysis of METs formation during experimental infection of macrophages with M. tuberculosis revealed that cord-forming M. tuberculosis induced significantly more METs compared to the non-cording phenotype. Deletion of early secreted antigenic target-6 which is an important virulence factor of M. tuberculosis , abrogated the ability of the bacteria to induce METs. The release of extracellular DNA from host cells during infection may represent a defense mechanism against pathogens that are difficult to internalize, including cord-forming M. tuberculosis .

Selection and phenotypic characterization of a core collection of Brachypodium distachyon inbred lines.

PubMed

Tyler, Ludmila; Fangel, Jonatan U; Fagerström, Alexandra Dotson; Steinwand, Michael A; Raab, Theodore K; Willats, William Gt; Vogel, John P

2014-01-14

The model grass Brachypodium distachyon is increasingly used to study various aspects of grass biology. A large and genotypically diverse collection of B. distachyon germplasm has been assembled by the research community. The natural variation in this collection can serve as a powerful experimental tool for many areas of inquiry, including investigating biomass traits. We surveyed the phenotypic diversity in a large collection of inbred lines and then selected a core collection of lines for more detailed analysis with an emphasis on traits relevant to the use of grasses as biofuel and grain crops. Phenotypic characters examined included plant height, growth habit, stem density, flowering time, and seed weight. We also surveyed differences in cell wall composition using near infrared spectroscopy (NIR) and comprehensive microarray polymer profiling (CoMPP). In all cases, we observed extensive natural variation including a two-fold variation in stem density, four-fold variation in ferulic acid bound to hemicellulose, and 1.7-fold variation in seed mass. These characterizations can provide the criteria for selecting diverse lines for future investigations of the genetic basis of the observed phenotypic variation.

The DRD4 exon 3 VNTR polymorphism and addiction-related phenotypes: a review

PubMed Central

McGeary, John

2009-01-01

In addition to the large literatures on associations of the DRD4 VNTR polymorphism with ADHD and personality traits, there is an emerging literature linking this variant to addiction and addiction-related phenotypes. When only diagnosis-based studies are considered, an inconsistent picture emerges raising doubts as to the relevance of this polymorphism to addiction. However the use of multiple levels of analysis in examining the importance of this polymorphism has raised the possibility of an urge-related “intermediate phenotype” that puts one at risk for developing addiction but may not be found in all persons with an addiction diagnosis. From cellular assays through neuroimaging and behavioral phenotypes, these studies highlight the power of the “intermediate phenotype” approach and suggest a possible explanation of the mixed findings when diagnosis is used as the phenotype. Strengths and weaknesses of alternative DRD4 VNTR genotype grouping strategies are discussed. In sum, converging evidence across multiple methodologies supports the possibility of a robust relationship between the DRD4 exon 3 VNTR polymorphism and urge for addictive substances. PMID:19336242

Evaluation of a Partial Genome Screening of Two Asthma Susceptibility Regions Using Bayesian Network Based Bayesian Multilevel Analysis of Relevance

PubMed Central

Antal, Péter; Kiszel, Petra Sz.; Gézsi, András; Hadadi, Éva; Virág, Viktor; Hajós, Gergely; Millinghoffer, András; Nagy, Adrienne; Kiss, András; Semsei, Ágnes F.; Temesi, Gergely; Melegh, Béla; Kisfali, Péter; Széll, Márta; Bikov, András; Gálffy, Gabriella; Tamási, Lilla; Falus, András; Szalai, Csaba

2012-01-01

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA). This method uses Bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the Bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated. With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2–1.8); p = 3×10−4). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics. In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance. PMID:22432035

Patterns of Population Structure and Environmental Associations to Aridity Across the Range of Loblolly Pine (Pinus taeda L., Pinaceae)

PubMed Central

Eckert, Andrew J.; van Heerwaarden, Joost; Wegrzyn, Jill L.; Nelson, C. Dana; Ross-Ibarra, Jeffrey; González-Martínez, Santíago C.; Neale, David. B.

2010-01-01

Natural populations of forest trees exhibit striking phenotypic adaptations to diverse environmental gradients, thereby making them appealing subjects for the study of genes underlying ecologically relevant phenotypes. Here, we use a genome-wide data set of single nucleotide polymorphisms genotyped across 3059 functional genes to study patterns of population structure and identify loci associated with aridity across the natural range of loblolly pine (Pinus taeda L.). Overall patterns of population structure, as inferred using principal components and Bayesian cluster analyses, were consistent with three genetic clusters likely resulting from expansions out of Pleistocene refugia located in Mexico and Florida. A novel application of association analysis, which removes the confounding effects of shared ancestry on correlations between genetic and environmental variation, identified five loci correlated with aridity. These loci were primarily involved with abiotic stress response to temperature and drought. A unique set of 24 loci was identified as FST outliers on the basis of the genetic clusters identified previously and after accounting for expansions out of Pleistocene refugia. These loci were involved with a diversity of physiological processes. Identification of nonoverlapping sets of loci highlights the fundamental differences implicit in the use of either method and suggests a pluralistic, yet complementary, approach to the identification of genes underlying ecologically relevant phenotypes. PMID:20439779

Identifying biologically relevant putative mechanisms in a given phenotype comparison

PubMed Central

Hanoudi, Samer; Donato, Michele; Draghici, Sorin

2017-01-01

A major challenge in life science research is understanding the mechanism involved in a given phenotype. The ability to identify the correct mechanisms is needed in order to understand fundamental and very important phenomena such as mechanisms of disease, immune systems responses to various challenges, and mechanisms of drug action. The current data analysis methods focus on the identification of the differentially expressed (DE) genes using their fold change and/or p-values. Major shortcomings of this approach are that: i) it does not consider the interactions between genes; ii) its results are sensitive to the selection of the threshold(s) used, and iii) the set of genes produced by this approach is not always conducive to formulating mechanistic hypotheses. Here we present a method that can construct networks of genes that can be considered putative mechanisms. The putative mechanisms constructed by this approach are not limited to the set of DE genes, but also considers all known and relevant gene-gene interactions. We analyzed three real datasets for which both the causes of the phenotype, as well as the true mechanisms were known. We show that the method identified the correct mechanisms when applied on microarray datasets from mouse. We compared the results of our method with the results of the classical approach, showing that our method produces more meaningful biological insights. PMID:28486531

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

Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

PubMed

Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

2018-02-21

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

PubMed

Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T; Wu, Joy T; Welt, Jonathan; Foote, John; Moseley, Edward T; Grant, David W; Tyler, Patrick D; Celi, Leo A

2018-01-01

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Phenotypic and Genotypic Analysis of In Vitro-Selected Artemisinin-Resistant Progeny of Plasmodium falciparum

PubMed Central

Tucker, Matthew S.; Mutka, Tina; Sparks, Kansas; Patel, Janus

2012-01-01

Emergence of artemisinin resistance in Cambodia highlights the importance of characterizing resistance to this class of drugs. Previously, intermediate levels of resistance in Plasmodium falciparum were generated in vitro for artelinic acid (AL) and artemisinin (QHS). Here we expanded on earlier selection efforts to produce levels of clinically relevant concentrations, and the resulting lines were characterized genotypically and phenotypically. Recrudescence assays determined the ability of resistant and parent lines to recover following exposure to clinically relevant levels of drugs. Interestingly, the parent clone (D6) tolerated up to 1,500 ng/ml QHS, but the resistant parasite, D6.QHS340×3, recovered following exposure to 2,400 ng/ml QHS. Resistant D6, W2, and TM91c235 parasites all exhibited elevated 50% inhibitory concentrations (IC50s) to multiple artemisinin drugs, with >3-fold resistance to QHS and AL; however, the degree of resistance obtained with standard methods was remarkably less than expected for parasite lines that recovered from 2,400-ng/ml drug pressure. A novel assay format with radiolabeled hypoxanthine demonstrated a greater degree of resistance in vitro than the standard SYBR green method. Analysis of merozoite number in resistant parasites found D6 and TM91c235 resistant progeny had significantly fewer merozoites than parent strains, whereas W2 resistant progeny had significantly more. Amplification of pfmdr1 increased proportionately to the increased drug levels tolerated by W2 and TM91c235, but not in resistant D6. In summary, we define the artemisinin resistance phenotype as a decrease in susceptibility to artemisinins along with the ability to recover from drug-induced dormancy following supraclinical concentrations of the drug. PMID:22083467

Rare Variant Association Test with Multiple Phenotypes

PubMed Central

Lee, Selyeong; Won, Sungho; Kim, Young Jin; Kim, Yongkang; Kim, Bong-Jo; Park, Taesung

2016-01-01

Although genome-wide association studies (GWAS) have now discovered thousands of genetic variants associated with common traits, such variants cannot explain the large degree of “missing heritability,” likely due to rare variants. The advent of next generation sequencing technology has allowed rare variant detection and association with common traits, often by investigating specific genomic regions for rare variant effects on a trait. Although multiply correlated phenotypes are often concurrently observed in GWAS, most studies analyze only single phenotypes, which may lessen statistical power. To increase power, multivariate analyses, which consider correlations between multiple phenotypes, can be used. However, few existing multi-variant analyses can identify rare variants for assessing multiple phenotypes. Here, we propose Multivariate Association Analysis using Score Statistics (MAAUSS), to identify rare variants associated with multiple phenotypes, based on the widely used Sequence Kernel Association Test (SKAT) for a single phenotype. We applied MAAUSS to Whole Exome Sequencing (WES) data from a Korean population of 1,058 subjects, to discover genes associated with multiple traits of liver function. We then assessed validation of those genes by a replication study, using an independent dataset of 3,445 individuals. Notably, we detected the gene ZNF620 among five significant genes. We then performed a simulation study to compare MAAUSS's performance with existing methods. Overall, MAAUSS successfully conserved type 1 error rates and in many cases, had a higher power than the existing methods. This study illustrates a feasible and straightforward approach for identifying rare variants correlated with multiple phenotypes, with likely relevance to missing heritability. PMID:28039885

Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2018-02-01

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

Systematic RH genotyping and variant identification in French donors of African origin

PubMed Central

Kappler-Gratias, Sandrine; Auxerre, Carine; Dubeaux, Isabelle; Beolet, Marylise; Ripaux, Maryline; Le Pennec, Pierre-Yves; Pham, Bach-Nga

2014-01-01

Background RH molecular analysis has enabled the documentation of numerous variants of RHD and RHCE alleles, especially in individuals of African origin. The aim of the present study was to determine the type and frequency of D and/or RhCE variants among blood donors of African origin in France, by performing a systematic RH molecular analysis, in order to evaluate the implications for blood transfusion of patients of African origin. Materials and methods Samples from 316 African blood donors, whose origin was established by their Fy(a−b−) phenotype, were first analysed using the RHD and RHCE BeadChips Kit (BioArray Solutions, Immucor, Warren, NJ, USA). Sequencing was performed when necessary. Results RHD molecular analysis showed that 26.2% of donors had a variant RHD allele. It allowed the prediction of a partial D in 11% of cases. RHCE molecular analysis showed that 14.2% of donors had a variant RHCE allele or RH [RN or (C)ces] haplotype. A rare Rh phenotype associated with the loss of a high-prevalence antigen or partial RhCE antigens were predicted from RHCE molecular analysis in 1 (0.3%) and 17 (5%) cases, respectively. Discussion Systematic RHD and RHCE molecular analysis performed in blood donors of African origin provides transfusion-relevant information for individuals of African origin because of the frequency of variant RH alleles. RH molecular analysis may improve transfusion therapy of patients by allowing better donor and recipient matching, based not only on phenotypically matched red blood cell units, but also on units that are genetically matched with regards to RhCE variants. PMID:23867180

Accelerated Evolution in Distinctive Species Reveals Candidate Elements for Clinically Relevant Traits, Including Mutation and Cancer Resistance.

PubMed

Ferris, Elliott; Abegglen, Lisa M; Schiffman, Joshua D; Gregg, Christopher

2018-03-06

The identity of most functional elements in the mammalian genome and the phenotypes they impact are unclear. Here, we perform a genome-wide comparative analysis of patterns of accelerated evolution in species with highly distinctive traits to discover candidate functional elements for clinically important phenotypes. We identify accelerated regions (ARs) in the elephant, hibernating bat, orca, dolphin, naked mole rat, and thirteen-lined ground squirrel lineages in mammalian conserved regions, uncovering ∼33,000 elements that bind hundreds of different regulatory proteins in humans and mice. ARs in the elephant, the largest land mammal, are uniquely enriched near elephant DNA damage response genes. The genomic hotspot for elephant ARs is the E3 ligase subunit of the Fanconi anemia complex, a master regulator of DNA repair. Additionally, ARs in the six species are associated with specific human clinical phenotypes that have apparent concordance with overt traits in each species. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

Meta-analysis of the relevance of the OPRM1 118A>G genetic variant for pain treatment.

PubMed

Walter, Carmen; Lötsch, Jörn

2009-12-01

Regard of functional pharmacogenetic polymorphisms may further the success of pain therapy by adopting individualized approaches. The mu-opioid receptor gene (OPRM1) 118A>G polymorphism is a promising candidate for both opioid effects and pain because of both biological reasonability and apparent experimental and clinical evidence. We analyzed its importance for pain therapy using a meta-analytic approach to studies relating it to opioid pain therapy. Data from suitable studies selected from hits of a PubMed search for "OPRM1" were independently extracted by two authors. The meta-analysis included phenotypes by OPRM1 genotype (opioid dosing, pain, and side effects), publication year, diagnostic status, proportion of male study participants, and whether genotype frequencies agreed with Hardy-Weinberg equilibrium. We found no consistent association between OPRM1 118A>G genotypes and most of the phenotypes in a heterogeneous set of eight clinical studies. Only weak evidence of an association with less nausea (effect size, Cohen's d=-0.21, p=0.037) and of increased opioid dosage requirements (d=0.56, p=0.018) in homozygous carriers of the G allele was obtained. This indicates that despite initially promising results, available evidence of the clinical relevance of the OPRM1 118A>G polymorphism does not withhold a meta-analysis. This discourages basing personalized therapeutic concepts of pain therapy on OPRM1 118A>G genotyping at the present state of evidence.

On the nosology and pathogenesis of Wolf-Hirschhorn syndrome: genotype-phenotype correlation analysis of 80 patients and literature review.

PubMed

Zollino, Marcella; Murdolo, Marina; Marangi, Giuseppe; Pecile, Vanna; Galasso, Cinzia; Mazzanti, Laura; Neri, Giovanni

2008-11-15

Based on genotype-phenotype correlation analysis of 80 Wolf-Hirschhorn syndrome (WHS) patients, as well as on review of relevant literature, we add further insights to the following aspects of WHS: (1) clinical delineation and phenotypic categories; (2) characterization of the basic genomic defect, mechanisms of origin and familiarity; (3) identification of prognostic factors for mental retardation; (4) chromosome mapping of the distinctive clinical signs, in an effort to identify pathogenic genes. Clinically, we consider that minimal diagnostic criteria for WHS, defining a "core" phenotype, are typical facial appearance, mental retardation, growth delay and seizures (or EEG anomalies). Three different categories of the WHS phenotype were defined, generally correlating with the extent of the 4p deletion. The first one comprises a small deletion not exceeding 3.5 Mb, that is usually associated with a mild phenotype, lacking major malformations. This category is likely under-diagnosed. The second and by far the more frequent category is identified by large deletions, averaging between 5 and 18 Mb, and causes the widely recognizable WHS phenotype. The third clinical category results from a very large deletion exceeding 22-25 Mb causing a severe phenotype, that can hardly be defined as typical WHS. Genetically, de novo chromosome abnormalities in WHS include pure deletions but also complex rearrangements, mainly unbalanced translocations. With the exception of t(4p;8p), WHS-associated chromosome abnormalities are neither mediated by segmental duplications, nor associated with a parental inversion polymorphism on 4p16.3. Factors involved in prediction of prognosis include the extent of the deletion, the occurrence of complex chromosome anomalies, and the severity of seizures. We found that the core phenotype maps within the terminal 1.9 Mb region of chromosome 4p. Therefore, WHSCR-2 should be considered the critical region for this condition. We also confirmed that the pathogenesis of WHS is multigenic. Specific and independent chromosome regions were characterized for growth delay and seizures, as well as for the additional clinical signs that characterize this condition. With the exception of parental balanced translocations, familial recurrence is uncommon.

Next generation phenotyping using narrative reports in a rare disease clinical data warehouse.

PubMed

Garcelon, Nicolas; Neuraz, Antoine; Salomon, Rémi; Bahi-Buisson, Nadia; Amiel, Jeanne; Picard, Capucine; Mahlaoui, Nizar; Benoit, Vincent; Burgun, Anita; Rance, Bastien

2018-05-31

Secondary use of data collected in Electronic Health Records opens perspectives for increasing our knowledge of rare diseases. The clinical data warehouse (named Dr. Warehouse) at the Necker-Enfants Malades Children's Hospital contains data collected during normal care for thousands of patients. Dr. Warehouse is oriented toward the exploration of clinical narratives. In this study, we present our method to find phenotypes associated with diseases of interest. We leveraged the frequency and TF-IDF to explore the association between clinical phenotypes and rare diseases. We applied our method in six use cases: phenotypes associated with the Rett, Lowe, Silver Russell, Bardet-Biedl syndromes, DOCK8 deficiency and Activated PI3-kinase Delta Syndrome (APDS). We asked domain experts to evaluate the relevance of the top-50 (for frequency and TF-IDF) phenotypes identified by Dr. Warehouse and computed the average precision and mean average precision. Experts concluded that between 16 and 39 phenotypes could be considered as relevant in the top-50 phenotypes ranked by descending frequency discovered by Dr. Warehouse (resp. between 11 and 41 for TF-IDF). Average precision ranges from 0.55 to 0.91 for frequency and 0.52 to 0.95 for TF-IDF. Mean average precision was 0.79. Our study suggests that phenotypes identified in clinical narratives stored in Electronic Health Record can provide rare disease specialists with candidate phenotypes that can be used in addition to the literature. Clinical Data Warehouses can be used to perform Next Generation Phenotyping, especially in the context of rare diseases. We have developed a method to detect phenotypes associated with a group of patients using medical concepts extracted from free-text clinical narratives.

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.

PubMed

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions.

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records

PubMed Central

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions. PMID:29899974

Genome-Wide Association Study for Traits Related to Plant and Grain Morphology, and Root Architecture in Temperate Rice Accessions.

PubMed

Biscarini, Filippo; Cozzi, Paolo; Casella, Laura; Riccardi, Paolo; Vattari, Alessandra; Orasen, Gabriele; Perrini, Rosaria; Tacconi, Gianni; Tondelli, Alessandro; Biselli, Chiara; Cattivelli, Luigi; Spindel, Jennifer; McCouch, Susan; Abbruscato, Pamela; Valé, Giampiero; Piffanelli, Pietro; Greco, Raffaella

2016-01-01

In this study we carried out a genome-wide association analysis for plant and grain morphology and root architecture in a unique panel of temperate rice accessions adapted to European pedo-climatic conditions. This is the first study to assess the association of selected phenotypic traits to specific genomic regions in the narrow genetic pool of temperate japonica. A set of 391 rice accessions were GBS-genotyped yielding-after data editing-57000 polymorphic and informative SNPS, among which 54% were in genic regions. In total, 42 significant genotype-phenotype associations were detected: 21 for plant morphology traits, 11 for grain quality traits, 10 for root architecture traits. The FDR of detected associations ranged from 3 · 10-7 to 0.92 (median: 0.25). In most cases, the significant detected associations co-localised with QTLs and candidate genes controlling the phenotypic variation of single or multiple traits. The most significant associations were those for flag leaf width on chromosome 4 (FDR = 3 · 10-7) and for plant height on chromosome 6 (FDR = 0.011). We demonstrate the effectiveness and resolution of the developed platform for high-throughput phenotyping, genotyping and GWAS in detecting major QTLs for relevant traits in rice. We identified strong associations that may be used for selection in temperate irrigated rice breeding: e.g. associations for flag leaf width, plant height, root volume and length, grain length, grain width and their ratio. Our findings pave the way to successfully exploit the narrow genetic pool of European temperate rice and to pinpoint the most relevant genetic components contributing to the adaptability and high yield of this germplasm. The generated data could be of direct use in genomic-assisted breeding strategies.

Mouse models of ageing and their relevance to disease.

PubMed

Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

2016-12-01

Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome.

PubMed

de Toro-Martín, Juan; Arsenault, Benoit J; Després, Jean-Pierre; Vohl, Marie-Claude

2017-08-22

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

PubMed Central

de Toro-Martín, Juan; Arsenault, Benoit J.; Després, Jean-Pierre

2017-01-01

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed. PMID:28829397

Fibroblast-matrix interplay: Nintedanib and pirfenidone modulate the effect of IPF fibroblast-conditioned matrix on normal fibroblast phenotype.

PubMed

Epstein Shochet, Gali; Wollin, Lutz; Shitrit, David

2018-03-12

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis. Activated fibroblasts are the key effector cells in fibrosis, producing excessive amounts of collagen and extracellular matrix (ECM) proteins. Whether the ECM conditioned by IPF fibroblasts determines the phenotype of naïve fibroblasts is difficult to explore. IPF-derived primary fibroblasts were cultured on Matrigel and then cleared using ammonium hydroxide, creating an IPF-conditioned matrix (CM). Normal fibroblast CM served as control. Normal fibroblasts were cultured on both types of CM, and cell count, cell distribution and markers of myofibroblast differentiation; transforming growth factor beta (TGFβ) signalling; and ECM expression were assessed. The effects of the anti-fibrotic drugs nintedanib and pirfenidone at physiologically relevant concentrations were also explored. Normal fibroblasts cultured on IPF-CM arranged in large aggregates as a result of increased proliferation and migration. Moreover, increased levels of pSmad3, pSTAT3 (phospho signal transducer and activator of transcription 3), alpha smooth muscle actin (αSMA) and Collagen1a were found, suggesting a differentiation towards a myofibroblast-like phenotype. SB505124 (10 μmol/L) partially reversed these alterations, suggesting a TGFβ contribution. Furthermore, nintedanib at 100 nmol/L and, to a lesser extent, pirfenidone at 100 μmol/L prevented the IPF-CM-induced fibroblast phenotype alterations, suggesting an attenuation of the ECM-fibroblast interplay. IPF fibroblasts alter the ECM, thus creating a CM that further propagates an IPF-like phenotype in normal fibroblasts. This assay demonstrated differences in drug activities for approved IPF drugs at clinically relevant concentrations. Thus, the matrix-fibroblast phenotype interplay might be a relevant assay to explore drug candidates for IPF treatment. © 2018 Asian Pacific Society of Respirology.

Developmental origins of novel gut morphology in frogs

PubMed Central

Bloom, Stephanie; Ledon-Rettig, Cris; Infante, Carlos; Everly, Anne; Hanken, James; Nascone-Yoder, Nanette

2013-01-01

SUMMARY Phenotypic variation is a prerequisite for evolution by natural selection, yet the processes that give rise to the novel morphologies upon which selection acts are poorly understood. We employed a chemical genetic screen to identify developmental changes capable of generating ecologically relevant morphological variation as observed among extant species. Specifically, we assayed for exogenously applied small molecules capable of transforming the ancestral larval foregut of the herbivorous Xenopus laevis to resemble the derived larval foregut of the carnivorous Lepidobatrachus laevis. Appropriately, the small molecules that demonstrate this capacity modulate conserved morphogenetic pathways involved in gut development, including downregulation of retinoic acid (RA) signaling. Identical manipulation of RA signaling in a species that is more closely related to Lepidobatrachus, Ceratophrys cranwelli, yielded even more similar transformations, corroborating the relevance of RA signaling variation in interspecific morphological change. Finally, we were able to recover the ancestral gut phenotype in Lepidobatrachus by performing a reverse chemical manipulation to upregulate RA signaling, providing strong evidence that modifications to this specific pathway promoted the emergence of a lineage-specific phenotypic novelty. Interestingly, our screen also revealed pathways that have not yet been implicated in early gut morphogenesis, such as thyroid hormone signaling. In general, the chemical genetic screen may be a valuable tool for identifying developmental mechanisms that underlie ecologically and evolutionarily relevant phenotypic variation. PMID:23607305

Developing Novel Automated Apparatus for Studying Battery of Social Behaviors in Mutant Mouse Models for Autism

DTIC Science & Technology

2013-06-01

Psychiatry, 2008. 13(1): p. 4-26. 2. McFarlane, H.G., et al., Autism -like behavioral phenotypes in BTBR T+tf/J mice. Genes Brain Behav, 2008. 7(2): p. 152...63. 3. Brodkin, E.S., BALB/c mice: low sociability and other phenotypes that may be relevant to autism . Behav Brain Res, 2007. 176(1): p. 53-65. 4...S.S., et al., Development of a mouse test for repetitive, restricted behaviors: relevance to autism . Behav Brain Res, 2008. 188(1): p. 178-94. 6

Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.

PubMed

Taguchi, Y-H

2018-05-08

Even though coexistence of multiple phenotypes sharing the same genomic background is interesting, it remains incompletely understood. Epigenomic profiles may represent key factors, with unknown contributions to the development of multiple phenotypes, and social-insect castes are a good model for elucidation of the underlying mechanisms. Nonetheless, previous studies have failed to identify genes associated with aberrant gene expression and methylation profiles because of the lack of suitable methodology that can address this problem properly. A recently proposed principal component analysis (PCA)-based and tensor decomposition (TD)-based unsupervised feature extraction (FE) can solve this problem because these two approaches can deal with gene expression and methylation profiles even when a small number of samples is available. PCA-based and TD-based unsupervised FE methods were applied to the analysis of gene expression and methylation profiles in the brains of two social insects, Polistes canadensis and Dinoponera quadriceps. Genes associated with differential expression and methylation between castes were identified, and analysis of enrichment of Gene Ontology terms confirmed reliability of the obtained sets of genes from the biological standpoint. Biologically relevant genes, shown to be associated with significant differential gene expression and methylation between castes, were identified here for the first time. The identification of these genes may help understand the mechanisms underlying epigenetic control of development of multiple phenotypes under the same genomic conditions.

Species composition and morphologic variation of Porites in the Gulf of California

NASA Astrophysics Data System (ADS)

López-Pérez, R. A.

2013-09-01

Morphometric analysis of corallite calices confirmed that from the late Miocene to the Recent, four species of Porites have inhabited the Gulf of California: the extinct Porites carrizensis, the locally extirpated Porites lobata and the extant Porites sverdrupi and Porites panamensis. Furthermore, large-scale spatial and temporal phenotypic plasticity was observed in the dominant species P. panamensis. Canonical discriminant analysis and ANOVA demonstrated that the calice structures of P. panamensis experienced size reduction between the late Pleistocene and Recent. Similarly, PERMANOVA, regression and correlation analyses demonstrated that across the 800 km north to south in the gulf, P. panamensis populations displayed a similar reduction in calice structures. Based on correlation analysis with environmental data, these large spatial changes are likely related to changes in nutrient concentration and sea surface temperature. As such, the large-scale spatial and temporal phenotypic variation recorded in populations of P. panamensis in the Gulf of California is likely related to optimization of corallite performance (energy acquisition) within various environmental scenarios. These findings may have relevance to modern conservation efforts within this ecological dominant genus.

Epigenetic regulation of EFEMP1 in prostate cancer: biological relevance and clinical potential

PubMed Central

Almeida, Mafalda; Costa, Vera L; Costa, Natália R; Ramalho-Carvalho, João; Baptista, Tiago; Ribeiro, Franclim R; Paulo, Paula; Teixeira, Manuel R; Oliveira, Jorge; Lothe, Ragnhild A; Lind, Guro E; Henrique, Rui; Jerónimo, Carmen

2014-01-01

Epigenetic alterations are common in prostate cancer (PCa) and seem to contribute decisively to its initiation and progression. Moreover, aberrant promoter methylation is a promising biomarker for non-invasive screening. Herein, we sought to characterize EFEMP1 as biomarker for PCa, unveiling its biological relevance in prostate carcinogenesis. Microarray analyses of treated PCa cell lines and primary tissues enabled the selection of differentially methylated genes, among which EFEMP1 was further validated by MSP and bisulfite sequencing. Assessment of biomarker performance was accomplished by qMSP. Expression analysis of EFEMP1 and characterization of histone marks were performed in tissue samples and cancer cell lines to determine the impact of epigenetic mechanisms on EFEMP1 transcriptional regulation. Phenotypic assays, using transfected cell lines, permitted the evaluation of EFEMP1’s role in PCa development. EFEMP1 methylation assay discriminated PCa from normal prostate tissue (NPT; P < 0.001, Kruskall–Wallis test) and renal and bladder cancers (96% sensitivity and 98% specificity). EFEMP1 transcription levels inversely correlated with promoter methylation and histone deacetylation, suggesting that both epigenetic mechanisms are involved in gene regulation. Phenotypic assays showed that EFEMP1 de novo expression reduces malignant phenotype of PCa cells. EFEMP1 promoter methylation is prevalent in PCa and accurately discriminates PCa from non-cancerous prostate tissues and other urological neoplasms. This epigenetic alteration occurs early in prostate carcinogenesis and, in association with histone deacetylation, progressively leads to gene down-regulation, fostering cell proliferation, invasion and evasion of apoptosis. PMID:25211630

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.

Systematic internal transcribed spacer sequence analysis for identification of clinical mold isolates in diagnostic mycology: a 5-year study.

PubMed

Ciardo, Diana E; Lucke, Katja; Imhof, Alex; Bloemberg, Guido V; Böttger, Erik C

2010-08-01

The implementation of internal transcribed spacer (ITS) sequencing for routine identification of molds in the diagnostic mycology laboratory was analyzed in a 5-year study. All mold isolates (n = 6,900) recovered in our laboratory from 2005 to 2009 were included in this study. According to a defined work flow, which in addition to troublesome phenotypic identification takes clinical relevance into account, 233 isolates were subjected to ITS sequence analysis. Sequencing resulted in successful identification for 78.6% of the analyzed isolates (57.1% at species level, 21.5% at genus level). In comparison, extended in-depth phenotypic characterization of the isolates subjected to sequencing achieved taxonomic assignment for 47.6% of these, with a mere 13.3% at species level. Optimization of DNA extraction further improved the efficacy of molecular identification. This study is the first of its kind to testify to the systematic implementation of sequence-based identification procedures in the routine workup of mold isolates in the diagnostic mycology laboratory.

Relevance and costs of RHD genotyping in women with a weak D phenotype.

PubMed

Laget, L; Izard, C; Durieux-Roussel, E; Gouvitsos, J; Dettori, I; Chiaroni, J; Ferrera-Tourenc, V

2018-06-01

For pregnant women, the serologic test results of D antigen will determine the frequency of RBC antibody detection as well as the indication for RhIG prophylaxis. RHD genotyping is the only method that may provide clear guidance on prophylaxis for women with a weak D phenotype. This analysis evaluated the economical implications of using RHD genotyping to guide RhIG prophylaxis among pregnant women with a serological weak D phenotype. We compared the costs of 2 strategies in a cohort of 273 women with weak D phenotype. In the first strategy, we did not perform genotyping and all women with weak D phenotypes were treated as if they were D-, thus considered to be a risk of RhD alloimmunization. These women all received the prophylactic follow up. In the second strategy, RHD genotyping was performed on all women with a serologic weak D phenotype. Then, the follow-up will be determined by phenotype deduced from genotype. On the studied cohort, the additional expense occurred by genotyping is 26,536 €. RHD Genotyping has highlighted 162 weak D Type 1, 2 3, that could safely be managed as D+ and 111 partial D to consider as D-. By comparing the 2 strategies, the savings generated by genotyping the patients of our cohort are € 12,046 for the follow up of one pregnancy. Knowing that in France, a woman has on average 2 pregnancies and that the genotyping is carried out only once, the savings generated for the following pregnancies would be € 38,581. Performing RHD genotyping for pregnant women with a weak D phenotype enables to clearly identify weak D type 1, 2 or 3 from the other variants at risk of alloimmunization. This analysis generates savings in terms of follow-up schedule of pregnant women and RhIG prophylaxis. It also allows saving of D- products for patient with a weak D type 1, 2 or 3 in case of a transfusion need. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Rationale and Design of the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) Study. Sarcoidosis Protocol.

PubMed

Moller, David R; Koth, Laura L; Maier, Lisa A; Morris, Alison; Drake, Wonder; Rossman, Milton; Leader, Joseph K; Collman, Ronald G; Hamzeh, Nabeel; Sweiss, Nadera J; Zhang, Yingze; O'Neal, Scott; Senior, Robert M; Becich, Michael; Hochheiser, Harry S; Kaminski, Naftali; Wisniewski, Stephen R; Gibson, Kevin F

2015-10-01

Sarcoidosis is a systemic disease characterized by noncaseating granulomatous inflammation with tremendous clinical heterogeneity and uncertain pathobiology and lacking in clinically useful biomarkers. The Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study is an observational cohort study designed to explore the role of the lung microbiome and genome in these two diseases. This article describes the design and rationale for the GRADS study sarcoidosis protocol. The study addresses the hypothesis that distinct patterns in the lung microbiome are characteristic of sarcoidosis phenotypes and are reflected in changes in systemic inflammatory responses as measured by peripheral blood changes in gene transcription. The goal is to enroll 400 participants, with a minimum of 35 in each of 9 clinical phenotype subgroups prioritized by their clinical relevance to understanding of the pathobiology and clinical heterogeneity of sarcoidosis. Participants with a confirmed diagnosis of sarcoidosis undergo a baseline visit with self-administered questionnaires, chest computed tomography, pulmonary function tests, and blood and urine testing. A research or clinical bronchoscopy with a research bronchoalveolar lavage will be performed to obtain samples for genomic and microbiome analyses. Comparisons will be made by blood genomic analysis and with clinical phenotypic variables. A 6-month follow-up visit is planned to assess each participant's clinical course. By the use of an integrative approach to the analysis of the microbiome and genome in selected clinical phenotypes, the GRADS study is powerfully positioned to inform and direct studies on the pathobiology of sarcoidosis, identify diagnostic or prognostic biomarkers, and provide novel molecular phenotypes that could lead to improved personalized approaches to therapy for sarcoidosis.

Rationale and Design of the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) Study. Sarcoidosis Protocol

PubMed Central

Koth, Laura L.; Maier, Lisa A.; Morris, Alison; Drake, Wonder; Rossman, Milton; Leader, Joseph K.; Collman, Ronald G.; Hamzeh, Nabeel; Sweiss, Nadera J.; Zhang, Yingze; O’Neal, Scott; Senior, Robert M.; Becich, Michael; Hochheiser, Harry S.; Kaminski, Naftali; Wisniewski, Stephen R.; Gibson, Kevin F.

2015-01-01

Sarcoidosis is a systemic disease characterized by noncaseating granulomatous inflammation with tremendous clinical heterogeneity and uncertain pathobiology and lacking in clinically useful biomarkers. The Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study is an observational cohort study designed to explore the role of the lung microbiome and genome in these two diseases. This article describes the design and rationale for the GRADS study sarcoidosis protocol. The study addresses the hypothesis that distinct patterns in the lung microbiome are characteristic of sarcoidosis phenotypes and are reflected in changes in systemic inflammatory responses as measured by peripheral blood changes in gene transcription. The goal is to enroll 400 participants, with a minimum of 35 in each of 9 clinical phenotype subgroups prioritized by their clinical relevance to understanding of the pathobiology and clinical heterogeneity of sarcoidosis. Participants with a confirmed diagnosis of sarcoidosis undergo a baseline visit with self-administered questionnaires, chest computed tomography, pulmonary function tests, and blood and urine testing. A research or clinical bronchoscopy with a research bronchoalveolar lavage will be performed to obtain samples for genomic and microbiome analyses. Comparisons will be made by blood genomic analysis and with clinical phenotypic variables. A 6-month follow-up visit is planned to assess each participant’s clinical course. By the use of an integrative approach to the analysis of the microbiome and genome in selected clinical phenotypes, the GRADS study is powerfully positioned to inform and direct studies on the pathobiology of sarcoidosis, identify diagnostic or prognostic biomarkers, and provide novel molecular phenotypes that could lead to improved personalized approaches to therapy for sarcoidosis. PMID:26193069

From psychiatric disorders to animal models: a bidirectional and dimensional approach

PubMed Central

Donaldson, Zoe. R.; Hen, René

2014-01-01

Psychiatric genetics research is bidirectional in nature, with human and animal studies becoming more closely integrated as techniques for genetic manipulations allow for more subtle exploration of disease phenotypes. This synergy, however, highlights the importance of considering the way in which we approach the genotype-phenotype relationship. In particular, the nosological divide of psychiatric illness, while clinically relevant, is not directly translatable in animal models. For instance, mice will never fully re-capitulate the broad criteria for many psychiatric disorders; nor will they have guilty ruminations, suicidal thoughts, or rapid speech. Instead, animal models have been and continue to provide a means to explore dimensions of psychiatric disorders in order to identify neural circuits and mechanisms underlying disease-relevant phenotypes. Thus, the genetic investigation of psychiatric illness will yield the greatest insights if efforts continue to identify and utilize biologically valid phenotypes across species. In this review we discuss the progress to date and the future efforts that will enhance translation between human and animal studies, including the identification of intermediate phenotypes that can be studied across species, as well as the importance of refined modeling of human disease-associated genetic variation in mice and other animal models. PMID:24650688

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Genome-wide identification of translationally inhibited and degraded miR-155 targets using RNA-interacting protein-IP

PubMed Central

Meier, Jan; Hovestadt, Volker; Zapatka, Marc; Pscherer, Armin; Lichter, Peter; Seiffert, Martina

2013-01-01

MicroRNAs (miRNAs) are single-stranded, small, non-coding RNAs, which fine-tune protein expression by degrading and/or translationally inhibiting mRNAs. Manipulation of miRNA expression in animal models frequently results in severe phenotypes indicating their relevance in controlling cellular functions, most likely by interacting with multiple targets. To better understand the effect of miRNA activities, genome-wide analysis of their targets are required. MicroRNA profiling as well as transcriptome analysis upon enforced miRNA expression were frequently used to investigate their relevance. However, these approaches often fail to identify relevant miRNAs targets. Therefore, we tested the precision of RNA-interacting protein immunoprecipitation (RIP) using AGO2-specific antibodies, a core component of the “RNA-induced silencing complex” (RISC), followed by RNA sequencing (Seq) in a defined cellular system, the HEK293T cells with stable, ectopic expression of miR-155. Thereby, we identified 100 AGO2-associated mRNAs in miR-155-expressing cells, of which 67 were in silico predicted miR-155 target genes. An integrated analysis of the corresponding expression profiles indicated that these targets were either regulated by mRNA decay or by translational repression. Of the identified miR-155 targets, 17 were related to cell cycle control, suggesting their involvement in the observed increase in cell proliferation of HEK293T cells upon miR-155 expression. Additional, secondary changes within the gene expression profile were detected and might contribute to this phenotype as well. Interestingly, by analyzing RIP-Seq data of HEK-293T cells and two B-cell lines we identified a recurrent disproportional enrichment of several miRNAs, including miR-155 and miRNAs of the miR-17-92 cluster, in the AGO2-associated precipitates, suggesting discrepancies in miRNA expression and activity. PMID:23673373

Genetic association of impulsivity in young adults: a multivariate study

PubMed Central

Khadka, S; Narayanan, B; Meda, S A; Gelernter, J; Han, S; Sawyer, B; Aslanzadeh, F; Stevens, M C; Hawkins, K A; Anticevic, A; Potenza, M N; Pearlson, G D

2014-01-01

Impulsivity is a heritable, multifaceted construct with clinically relevant links to multiple psychopathologies. We assessed impulsivity in young adult (N~2100) participants in a longitudinal study, using self-report questionnaires and computer-based behavioral tasks. Analysis was restricted to the subset (N=426) who underwent genotyping. Multivariate association between impulsivity measures and single-nucleotide polymorphism data was implemented using parallel independent component analysis (Para-ICA). Pathways associated with multiple genes in components that correlated significantly with impulsivity phenotypes were then identified using a pathway enrichment analysis. Para-ICA revealed two significantly correlated genotype–phenotype component pairs. One impulsivity component included the reward responsiveness subscale and behavioral inhibition scale of the Behavioral-Inhibition System/Behavioral-Activation System scale, and the second impulsivity component included the non-planning subscale of the Barratt Impulsiveness Scale and the Experiential Discounting Task. Pathway analysis identified processes related to neurogenesis, nervous system signal generation/amplification, neurotransmission and immune response. We identified various genes and gene regulatory pathways associated with empirically derived impulsivity components. Our study suggests that gene networks implicated previously in brain development, neurotransmission and immune response are related to impulsive tendencies and behaviors. PMID:25268255

Cri du Chat syndrome

PubMed Central

Cerruti Mainardi, Paola

2006-01-01

The Cri du Chat syndrome (CdCS) is a genetic disease resulting from a deletion of variable size occurring on the short arm of chromosome 5 (5p-). The incidence ranges from 1:15,000 to 1:50,000 live-born infants. The main clinical features are a high-pitched monochromatic cry, microcephaly, broad nasal bridge, epicanthal folds, micrognathia, abnormal dermatoglyphics, and severe psychomotor and mental retardation. Malformations, although not very frequent, may be present: cardiac, neurological and renal abnormalities, preauricular tags, syndactyly, hypospadias, and cryptorchidism. Molecular cytogenetic analysis has allowed a cytogenetic and phenotypic map of 5p to be defined, even if results from the studies reported up to now are not completely in agreement. Genotype-phenotype correlation studies showed a clinical and cytogenetic variability. The identification of phenotypic subsets associated with a specific size and type of deletion is of diagnostic and prognostic relevance. Specific growth and psychomotor development charts have been established. Two genes, Semaphorin F (SEMAF) and δ-catenin (CTNND2), which have been mapped to the "critical regions", are potentially involved in cerebral development and their deletion may be associated with mental retardation in CdCS patients. Deletion of the telomerase reverse transcriptase (hTERT) gene, localised to 5p15.33, could contribute to the phenotypic changes in CdCS. The critical regions were recently refined by using array comparative genomic hybridisation. The cat-like cry critical region was further narrowed using quantitative polymerase chain reaction (PCR) and three candidate genes were characterised in this region. The diagnosis is based on typical clinical manifestations. Karyotype analysis and, in doubtful cases, FISH analysis will confirm the diagnosis. There is no specific therapy for CdCS but early rehabilitative and educational interventions improve the prognosis and considerable progress has been made in the social adjustment of CdCS patients. PMID:16953888

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Using iterative cluster merging with improved gap statistics to perform online phenotype discovery in the context of high-throughput RNAi screens

PubMed Central

Yin, Zheng; Zhou, Xiaobo; Bakal, Chris; Li, Fuhai; Sun, Youxian; Perrimon, Norbert; Wong, Stephen TC

2008-01-01

Background The recent emergence of high-throughput automated image acquisition technologies has forever changed how cell biologists collect and analyze data. Historically, the interpretation of cellular phenotypes in different experimental conditions has been dependent upon the expert opinions of well-trained biologists. Such qualitative analysis is particularly effective in detecting subtle, but important, deviations in phenotypes. However, while the rapid and continuing development of automated microscope-based technologies now facilitates the acquisition of trillions of cells in thousands of diverse experimental conditions, such as in the context of RNA interference (RNAi) or small-molecule screens, the massive size of these datasets precludes human analysis. Thus, the development of automated methods which aim to identify novel and biological relevant phenotypes online is one of the major challenges in high-throughput image-based screening. Ideally, phenotype discovery methods should be designed to utilize prior/existing information and tackle three challenging tasks, i.e. restoring pre-defined biological meaningful phenotypes, differentiating novel phenotypes from known ones and clarifying novel phenotypes from each other. Arbitrarily extracted information causes biased analysis, while combining the complete existing datasets with each new image is intractable in high-throughput screens. Results Here we present the design and implementation of a novel and robust online phenotype discovery method with broad applicability that can be used in diverse experimental contexts, especially high-throughput RNAi screens. This method features phenotype modelling and iterative cluster merging using improved gap statistics. A Gaussian Mixture Model (GMM) is employed to estimate the distribution of each existing phenotype, and then used as reference distribution in gap statistics. This method is broadly applicable to a number of different types of image-based datasets derived from a wide spectrum of experimental conditions and is suitable to adaptively process new images which are continuously added to existing datasets. Validations were carried out on different dataset, including published RNAi screening using Drosophila embryos [Additional files 1, 2], dataset for cell cycle phase identification using HeLa cells [Additional files 1, 3, 4] and synthetic dataset using polygons, our methods tackled three aforementioned tasks effectively with an accuracy range of 85%–90%. When our method is implemented in the context of a Drosophila genome-scale RNAi image-based screening of cultured cells aimed to identifying the contribution of individual genes towards the regulation of cell-shape, it efficiently discovers meaningful new phenotypes and provides novel biological insight. We also propose a two-step procedure to modify the novelty detection method based on one-class SVM, so that it can be used to online phenotype discovery. In different conditions, we compared the SVM based method with our method using various datasets and our methods consistently outperformed SVM based method in at least two of three tasks by 2% to 5%. These results demonstrate that our methods can be used to better identify novel phenotypes in image-based datasets from a wide range of conditions and organisms. Conclusion We demonstrate that our method can detect various novel phenotypes effectively in complex datasets. Experiment results also validate that our method performs consistently under different order of image input, variation of starting conditions including the number and composition of existing phenotypes, and dataset from different screens. In our findings, the proposed method is suitable for online phenotype discovery in diverse high-throughput image-based genetic and chemical screens. PMID:18534020

An in vivo multiplexed small molecule screening platform

PubMed Central

Yang, Dian; Ogasawara, Daisuke; Dix, Melissa M.; Rogers, Zoë N.; Chuang, Chen-Hua; McFarland, Christopher D.; Chiou, Shin-Heng; Brown, J. Mark; Cravatt, Benjamin F.; Bogyo, Matthew; Winslow, Monte M.

2016-01-01

Phenotype-based small molecule screening is a powerful method to identify regulators of cellular function. However, such screens are generally performed in vitro using conditions that do not necessarily model complex physiological conditions or disease states. Here, we use molecular cell barcoding to enable direct in vivo phenotypic screening of libraries of small molecules. The multiplexed nature of this approach allows rapid in vivo analysis of hundreds to thousands of compounds. Using this platform, we screened >700 covalent inhibitors directed towards hydrolases for their effect on pancreatic cancer metastatic seeding. We identified multiple hits and confirmed the relevant target of one compound as the lipase ABHD6. Pharmacological and genetic studies confirmed the role of this enzyme as a regulator of metastatic fitness. Our results highlight the applicability of this multiplexed screening platform for investigating complex processes in vivo. PMID:27617390

BDNF rs6265 methylation and genotype interact on risk for schizophrenia.

PubMed

Ursini, Gianluca; Cavalleri, Tommaso; Fazio, Leonardo; Angrisano, Tiziana; Iacovelli, Luisa; Porcelli, Annamaria; Maddalena, Giancarlo; Punzi, Giovanna; Mancini, Marina; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Calabrese, Francesca; Rampino, Antonio; Taurisano, Paolo; Di Giorgio, Annabella; Keller, Simona; Tarantini, Letizia; Sinibaldi, Lorenzo; Quarto, Tiziana; Popolizio, Teresa; Caforio, Grazia; Blasi, Giuseppe; Riva, Marco A; De Blasi, Antonio; Chiariotti, Lorenzo; Bollati, Valentina; Bertolino, Alessandro

2016-01-01

Epigenetic mechanisms can mediate gene-environment interactions relevant for complex disorders. The BDNF gene is crucial for development and brain plasticity, is sensitive to environmental stressors, such as hypoxia, and harbors the functional SNP rs6265 (Val(66)Met), which creates or abolishes a CpG dinucleotide for DNA methylation. We found that methylation at the BDNF rs6265 Val allele in peripheral blood of healthy subjects is associated with hypoxia-related early life events (hOCs) and intermediate phenotypes for schizophrenia in a distinctive manner, depending on rs6265 genotype: in ValVal individuals increased methylation is associated with exposure to hOCs and impaired working memory (WM) accuracy, while the opposite is true for ValMet subjects. Also, rs6265 methylation and hOCs interact in modulating WM-related prefrontal activity, another intermediate phenotype for schizophrenia, with an analogous opposite direction in the 2 genotypes. Consistently, rs6265 methylation has a different association with schizophrenia risk in ValVals and ValMets. The relationships of methylation with BDNF levels and of genotype with BHLHB2 binding likely contribute to these opposite effects of methylation. We conclude that BDNF rs6265 methylation interacts with genotype to bridge early environmental exposures to adult phenotypes, relevant for schizophrenia. The study of epigenetic changes in regions containing genetic variation relevant for human diseases may have beneficial implications for the understanding of how genes are actually translated into phenotypes.

Developmental origins of a novel gut morphology in frogs.

PubMed

Bloom, Stephanie; Ledon-Rettig, Cris; Infante, Carlos; Everly, Anne; Hanken, James; Nascone-Yoder, Nanette

2013-05-01

Phenotypic variation is a prerequisite for evolution by natural selection, yet the processes that give rise to the novel morphologies upon which selection acts are poorly understood. We employed a chemical genetic screen to identify developmental changes capable of generating ecologically relevant morphological variation as observed among extant species. Specifically, we assayed for exogenously applied small molecules capable of transforming the ancestral larval foregut of the herbivorous Xenopus laevis to resemble the derived larval foregut of the carnivorous Lepidobatrachus laevis. Appropriately, the small molecules that demonstrate this capacity modulate conserved morphogenetic pathways involved in gut development, including downregulation of retinoic acid (RA) signaling. Identical manipulation of RA signaling in a species that is more closely related to Lepidobatrachus, Ceratophrys cranwelli, yielded even more similar transformations, corroborating the relevance of RA signaling variation in interspecific morphological change. Finally, we were able to recover the ancestral gut phenotype in Lepidobatrachus by performing a reverse chemical manipulation to upregulate RA signaling, providing strong evidence that modifications to this specific pathway promoted the emergence of a lineage-specific phenotypic novelty. Interestingly, our screen also revealed pathways that have not yet been implicated in early gut morphogenesis, such as thyroid hormone signaling. In general, the chemical genetic screen may be a valuable tool for identifying developmental mechanisms that underlie ecologically and evolutionarily relevant phenotypic variation. © 2013 Wiley Periodicals, Inc.

Prediction and Validation of Disease Genes Using HeteSim Scores.

PubMed

Zeng, Xiangxiang; Liao, Yuanlu; Liu, Yuansheng; Zou, Quan

2017-01-01

Deciphering the gene disease association is an important goal in biomedical research. In this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate disease genes. Two methods based on heterogeneous networks constructed using protein-protein interaction, gene-phenotype associations, and phenotype-phenotype similarity, are presented. In HeteSim_MultiPath (HSMP), HeteSim scores of different paths are combined with a constant that dampens the contributions of longer paths. In HeteSim_SVM (HSSVM), HeteSim scores are combined with a machine learning method. The 3-fold experiments show that our non-machine learning method HSMP performs better than the existing non-machine learning methods, our machine learning method HSSVM obtains similar accuracy with the best existing machine learning method CATAPULT. From the analysis of the top 10 predicted genes for different diseases, we found that HSSVM avoid the disadvantage of the existing machine learning based methods, which always predict similar genes for different diseases. The data sets and Matlab code for the two methods are freely available for download at http://lab.malab.cn/data/HeteSim/index.jsp.

Phenotypic approaches to drought in cassava: review

PubMed Central

Okogbenin, Emmanuel; Setter, Tim L.; Ferguson, Morag; Mutegi, Rose; Ceballos, Hernan; Olasanmi, Bunmi; Fregene, Martin

2012-01-01

Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12–18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding. PMID:23717282

The Population Structure and Diversity of Eggplant from Asia and the Mediterranean Basin

PubMed Central

Cericola, Fabio; Portis, Ezio; Toppino, Laura; Barchi, Lorenzo; Acciarri, Nazareno; Ciriaci, Tommaso; Sala, Tea; Rotino, Giuseppe Leonardo; Lanteri, Sergio

2013-01-01

A collection of 238 eggplant breeding lines, heritage varieties and selections within local landraces provenanced from Asia and the Mediterranean Basin was phenotyped with respect to key plant and fruit traits, and genotyped using 24 microsatellite loci distributed uniformly throughout the genome. STRUCTURE analysis based on the genotypic data identified two major sub-groups, which to a large extent mirrored the provenance of the entries. With the goal to identify true-breeding types, 38 of the entries were discarded on the basis of microsatellite-based residual heterozygosity, along with a further nine which were not phenotypically uniform. The remaining 191 entries were scored for a set of 19 fruit and plant traits in a replicated experimental field trial. The phenotypic data were subjected to principal component and hierarchical principal component analyses, allowing three major morphological groups to be identified. All three morphological groups were represented in both the “Occidental” and the “Oriental” germplasm, so the correlation between the phenotypic and the genotypic data sets was quite weak. The relevance of these results for evolutionary studies and the further improvement of eggplant are discussed. The population structure of the core set of germplasm shows that it can be used as a basis for an association mapping approach. PMID:24040032

The population structure and diversity of eggplant from Asia and the Mediterranean Basin.

PubMed

Cericola, Fabio; Portis, Ezio; Toppino, Laura; Barchi, Lorenzo; Acciarri, Nazareno; Ciriaci, Tommaso; Sala, Tea; Rotino, Giuseppe Leonardo; Lanteri, Sergio

2013-01-01

A collection of 238 eggplant breeding lines, heritage varieties and selections within local landraces provenanced from Asia and the Mediterranean Basin was phenotyped with respect to key plant and fruit traits, and genotyped using 24 microsatellite loci distributed uniformly throughout the genome. STRUCTURE analysis based on the genotypic data identified two major sub-groups, which to a large extent mirrored the provenance of the entries. With the goal to identify true-breeding types, 38 of the entries were discarded on the basis of microsatellite-based residual heterozygosity, along with a further nine which were not phenotypically uniform. The remaining 191 entries were scored for a set of 19 fruit and plant traits in a replicated experimental field trial. The phenotypic data were subjected to principal component and hierarchical principal component analyses, allowing three major morphological groups to be identified. All three morphological groups were represented in both the "Occidental" and the "Oriental" germplasm, so the correlation between the phenotypic and the genotypic data sets was quite weak. The relevance of these results for evolutionary studies and the further improvement of eggplant are discussed. The population structure of the core set of germplasm shows that it can be used as a basis for an association mapping approach.

Biotinidase deficiency: Genotype-biochemical phenotype association in Brazilian patients

PubMed Central

Borsatto, Taciane; Sperb-Ludwig, Fernanda; Lima, Samyra E.; S. Carvalho, Maria R.; S. Fonseca, Pablo A.; S. Camelo, José; M. Ribeiro, Erlane; F. V. de Medeiros, Paula; M. Lourenço, Charles; F. M. de Souza, Carolina; Boy, Raquel; Félix, Têmis M.; M. Bittar, Camila; L. C. Pinto, Louise; C. Neto, Eurico; J. Blom, Henk; D. Schwartz, Ida V.

2017-01-01

Introduction The association between the BTD genotype and biochemical phenotype [profound biotinidase deficiency (BD), partial BD or heterozygous activity] is not always consistent. This study aimed to investigate the genotype-biochemical phenotype association in patients with low biotinidase activity. Methods All exons, the 5'UTR and the promoter of the BTD gene were sequenced in 72 Brazilian individuals who exhibited low biotinidase activity. For each patient, the expected biochemical phenotype based on the known genotype was compared with the observed biochemical phenotype. Additional non-genetic factors that could affect the biotinidase activity were also analysed. Results Most individuals were identified by neonatal screening (n = 66/72). When consecutive results for the same patient were compared, age, prematurity and neonatal jaundice appeared to affect the level of biotinidase activity. The biochemical phenotype at the time of the second blood collection changed in 11/22 patients compared to results from the first sample. Three novel variants were found: c.1337T>C (p.L446P), c.1466A>G (p.N489S) and c.962G>A (p.W321*). Some patients with the same genotype presented different biochemical phenotypes. The expected and observed biochemical phenotypes agreed in 68.5% of cases (concordant patients). The non-coding variants c.-183G>A, c.-315A>G and c.-514C>T were present in heterozygosis in 5/17 discordant patients. In addition, c.-183G>A and c.-514C>T were also present in 10/37 concordant patients. Conclusions The variants found in the promoter region do not appear to have a strong impact on biotinidase activity. Since there is a disparity between the BTD genotype and biochemical phenotype, and biotinidase activity may be affected by both genetic and non-genetic factors, we suggest that the diagnosis of BD should be based on more than one measurement of plasma biotinidase activity. DNA analysis can be of additional relevance to differentiate between partial BD and heterozygosity. PMID:28498829

A Phocus on Phenotyping: opportunities and challenges in local and centralized trait evaluation from the VitisGen experience

USDA-ARS?s Scientific Manuscript database

The integration of relevant genetic resources, robust phenotypes, and cutting-edge genotypic data is a challenge that individual scientists rarely overcome successfully. In the USDA-NIFA VitisGen project ( www.vitisgen.org ) for grapevine cultivar improvement, our research team has pursued a shared ...

Design of Biomedical Robots for Phenotype Prediction Problems

PubMed Central

deAndrés-Galiana, Enrique J.; Sonis, Stephen T.

2016-01-01

Abstract Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem. PMID:27347715

Design of Biomedical Robots for Phenotype Prediction Problems.

PubMed

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

2016-08-01

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

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution

PubMed Central

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D.; Rainey, Paul B.; de Visser, J. Arjan G. M.; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes–via growth–over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology. PMID:27077662

Lineage Tracking for Probing Heritable Phenotypes at Single-Cell Resolution.

PubMed

Cottinet, Denis; Condamine, Florence; Bremond, Nicolas; Griffiths, Andrew D; Rainey, Paul B; de Visser, J Arjan G M; Baudry, Jean; Bibette, Jérôme

2016-01-01

Determining the phenotype and genotype of single cells is central to understand microbial evolution. DNA sequencing technologies allow the detection of mutants at high resolution, but similar approaches for phenotypic analyses are still lacking. We show that a drop-based millifluidic system enables the detection of heritable phenotypic changes in evolving bacterial populations. At time intervals, cells were sampled and individually compartmentalized in 100 nL drops. Growth through 15 generations was monitored using a fluorescent protein reporter. Amplification of heritable changes-via growth-over multiple generations yields phenotypically distinct clusters reflecting variation relevant for evolution. To demonstrate the utility of this approach, we follow the evolution of Escherichia coli populations during 30 days of starvation. Phenotypic diversity was observed to rapidly increase upon starvation with the emergence of heritable phenotypes. Mutations corresponding to each phenotypic class were identified by DNA sequencing. This scalable lineage-tracking technology opens the door to large-scale phenotyping methods with special utility for microbiology and microbial population biology.

Cumulative live birth rates after IVF in patients with polycystic ovaries: phenotype matters.

PubMed

De Vos, Michel; Pareyn, Stéphanie; Drakopoulos, Panagiotis; Raimundo, José M; Anckaert, Ellen; Santos-Ribeiro, Samuel; Polyzos, Nikolaos P; Tournaye, Herman; Blockeel, Christophe

2018-05-07

Do cumulative live birth rates (CLBR) vary among women with different polycystic ovary syndrome (PCOS) phenotypes who undergo IVF/intracytoplasmic sperm injection (ICSI) treatment? In this retrospective cohort study, data from 567 patients undergoing an assisted reproductive technology (ART) cycle between January 2010 and December 2015 were collected. Demographical traits, cycle characteristics and clinical and laboratory data were analysed. After conventional ovarian stimulation using a gonadotrophin-releasing hormone antagonist protocol, the median number of oocytes retrieved ranged between 11 and 13.5 and did not differ significantly among the studied groups. Live birth rate (LBR) after fresh embryo transfer and CLBR after transfer of all fresh and vitrified embryos were significantly lower in women with hyperandrogenic PCOS phenotypes A (LBR 16.7%, CLBR 25.8%) and C (LBR 18.5%, CLBR 27.8%) compared with women with normoandrogenic PCOS phenotype D (LBR 33.7%, CLBR 48%) (P-value for LBR 0.01 and 0.03, respectively; P-value for CLBR 0.002 and 0.01, respectively) and controls with a polycystic ovarian morphology (LBR 37.1%, CLBR 53.3%) (P-value for LBR 0.002 and 0.01, respectively; P-value for CLBR <0.001 and 0.001, respectively). Multivariate regression analysis indicated that after adjustment for relevant confounders, PCOS phenotype was an independent predictor for CLBR. Hyperandrogenic PCOS phenotypes confer significantly lower CLBR compared with their normoandrogenic counterparts. These findings may imply the need for adapted counselling and tailored approaches when treating PCOS patients with hyperandrogenism who require ART. Copyright © 2018 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Multilocus Genotypes of Relevance for Drug Metabolizing Enzymes and Therapy with Thiopurines in Patients with Acute Lymphoblastic Leukemia

PubMed Central

Stocco, Gabriele; Franca, Raffaella; Verzegnassi, Federico; Londero, Margherita; Rabusin, Marco; Decorti, Giuliana

2013-01-01

Multilocus genotypes have been shown to be of relevance for using pharmacogenomic principles to individualize drug therapy. As it relates to thiopurine therapy, genetic polymorphisms of TPMT are strongly associated with the pharmacokinetics and clinical effects of thiopurines (mercaptopurine and azathioprine), influencing their toxicity and efficacy. We have recently demonstrated that TPMT and ITPA genotypes constitute a multilocus genotype of pharmacogenetic relevance for children with acute lymphoblastic leukemia (ALL) receiving thiopurine therapy. The use of high-throughput genomic analysis allows identification of additional candidate genetic factors associated with pharmacogenetic phenotypes, such as TPMT enzymatic activity: PACSIN2 polymorphisms have been identified by a genome-wide analysis, combining evaluation of polymorphisms and gene expression, as a significant determinant of TPMT activity in the HapMap CEU cell lines and the effects of PACSIN2 on TPMT activity and mercaptopurine induced adverse effects were confirmed in children with ALL. Combination of genetic factors of relevance for thiopurine metabolizing enzyme activity, based on the growing understanding of their association with drug metabolism and efficacy, is particularly promising for patients with pediatric ALL. The knowledge basis and clinical applications for multilocus genotypes of importance for therapy with mercaptopurine in pediatric ALL is discussed in the present review. PMID:23335936

The osteogenic response of undifferentiated human mesenchymal stem cells (hMSCs) to mechanical strain is inversely related to body mass index of the donor.

PubMed

Friedl, Gerald; Windhager, Reinhard; Schmidt, Helena; Aigner, Reingard

2009-08-01

While the importance of physical factors in the maintenance and regeneration of bone tissue has been recognized for many years and the mechano-sensitivity of bone cells is well established, there is increasing evidence that body fat constitutes an independent risk factor for complications in bone fracture healing and aseptic loosening of implants. Although mechanical causes have been widely suggested, we hypothesized that the osteogenic mechano-response of human mesenchymal stem cells (hMSCs) may be altered in obese patients. We determined the phenotypic and genotypic response of undifferentiated hMSCs of 10 donors to cyclic tensile strain (CTS) under controlled in vitro conditions and analyzed the potential relationship relevant to the donor's anthropomorphometric and biochemical parameters related to donor's fat and bone metabolism. The osteogenic marker genes were all statistically significantly upregulated by CTS, which was accompanied by a significant increase in cell-based ALP activity. Linear correlation analysis revealed that there was a significant correlation between phenotypic CTS response and the body mass index of the donor (r = -0.91, p < 0.001) and phenotypic CTS response was also significantly related to leptin levels (r = -0.68) and estradiol levels (r = 0.67) within the bone marrow microenvironment of the donor. Such an upstream imprinting process mediated by factors tightly related to the donor's fat metabolism, which hampers the mechanosensitivity of hMSCs in obese patients, may be of pathogenetic relevance for the complications associated with obesity that are seen in orthopedic surgery.

Characterization of transgenic mice--a comparison of protocols for welfare evaluation and phenotype characterization of mice with a suggestion on a future certificate of instruction.

PubMed

Jegstrup, I; Thon, R; Hansen, A K; Hoitinga, M Ritskes

2003-01-01

A thorough welfare evaluation performed as part of a general phenotype characterization for both transgenic and traditional mouse strains could not only contribute to the improvement of the welfare of laboratory animals, but could also be of benefit to scientists, laboratory veterinarians and the inspecting authorities. A literature review has been performed to identify and critically evaluate already existing protocols for phenotype and welfare characterization. There are several relevant schemes available, among others the SHIRPA method, the modified score sheet of Morton and Griffiths, the FRIMORFO phenotype characterization scheme and the behavioural phenotype schemes as described by Crawley. These protocols have been evaluated according to four goals: Their ability (1) to reveal any special needs or problems with a transgenic strain, (2) to cover the informational needs of the purchaser/user of the strain, (3) to refine the welfare of the transgenic animal model by identifying relevant humane endpoints, (4) to prevent the duplication of animal models that have already been developed. The protocols described are useful for characterizing the phenotype and judging welfare disturbances, however the total amount of information and the degree of detail varies considerably from one scheme to another. We present a proposal regarding the practical application of the various schemes that will secure proper treatment and the identification of humane endpoints. It is advocated that with every purchase of a particular strain, an instruction document should accompany the strain. This document needs to give detailed descriptions of the typical characteristics of the strain, as well as necessary actions concerning relevant treatment and humane endpoints. At the moment no such documents are required. The introduction of these types of documents will contribute to improvements in animal welfare as well as experimental results in laboratory animal experimentation.

Transcriptomic Analysis Using Olive Varieties and Breeding Progenies Identifies Candidate Genes Involved in Plant Architecture.

PubMed

González-Plaza, Juan J; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R

2016-01-01

Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species.

Targeted next-generation sequencing reveals novel USH2A mutations associated with diverse disease phenotypes: implications for clinical and molecular diagnosis.

PubMed

Chen, Xue; Sheng, Xunlun; Liu, Xiaoxing; Li, Huiping; Liu, Yani; Rong, Weining; Ha, Shaoping; Liu, Wenzhou; Kang, Xiaoli; Zhao, Kanxing; Zhao, Chen

2014-01-01

USH2A mutations have been implicated in the disease etiology of several inherited diseases, including Usher syndrome type 2 (USH2), nonsyndromic retinitis pigmentosa (RP), and nonsyndromic deafness. The complex genetic and phenotypic spectrums relevant to USH2A defects make it difficult to manage patients with such mutations. In the present study, we aim to determine the genetic etiology and to characterize the correlated clinical phenotypes for three Chinese pedigrees with nonsyndromic RP, one with RP sine pigmento (RPSP), and one with USH2. Family histories and clinical details for all included patients were reviewed. Ophthalmic examinations included best corrected visual acuities, visual field measurements, funduscopy, and electroretinography. Targeted next-generation sequencing (NGS) was applied using two sequence capture arrays to reveal the disease causative mutations for each family. Genotype-phenotype correlations were also annotated. Seven USH2A mutations, including four missense substitutions (p.P2762A, p.G3320C, p.R3719H, and p.G4763R), two splice site variants (c.8223+1G>A and c.8559-2T>C), and a nonsense mutation (p.Y3745*), were identified as disease causative in the five investigated families, of which three reported to have consanguineous marriage. Among all seven mutations, six were novel, and one was recurrent. Two homozygous missense mutations (p.P2762A and p.G3320C) were found in one individual family suggesting a potential double hit effect. Significant phenotypic divergences were revealed among the five families. Three families of the five families were affected with early, moderated, or late onset RP, one with RPSP, and the other one with USH2. Our study expands the genotypic and phenotypic variability relevant to USH2A mutations, which would help with a clear insight into the complex genetic and phenotypic spectrums relevant to USH2A defects, and is complementary for a better management of patients with such mutations. We have also demonstrated that a targeted NGS approach is a valuable tool for the genetic diagnosis of USH2 and RP.

Targeted Next-Generation Sequencing Reveals Novel USH2A Mutations Associated with Diverse Disease Phenotypes: Implications for Clinical and Molecular Diagnosis

PubMed Central

Li, Huiping; Liu, Yani; Rong, Weining; Ha, Shaoping; Liu, Wenzhou; Kang, Xiaoli; Zhao, Kanxing; Zhao, Chen

2014-01-01

USH2A mutations have been implicated in the disease etiology of several inherited diseases, including Usher syndrome type 2 (USH2), nonsyndromic retinitis pigmentosa (RP), and nonsyndromic deafness. The complex genetic and phenotypic spectrums relevant to USH2A defects make it difficult to manage patients with such mutations. In the present study, we aim to determine the genetic etiology and to characterize the correlated clinical phenotypes for three Chinese pedigrees with nonsyndromic RP, one with RP sine pigmento (RPSP), and one with USH2. Family histories and clinical details for all included patients were reviewed. Ophthalmic examinations included best corrected visual acuities, visual field measurements, funduscopy, and electroretinography. Targeted next-generation sequencing (NGS) was applied using two sequence capture arrays to reveal the disease causative mutations for each family. Genotype-phenotype correlations were also annotated. Seven USH2A mutations, including four missense substitutions (p.P2762A, p.G3320C, p.R3719H, and p.G4763R), two splice site variants (c.8223+1G>A and c.8559-2T>C), and a nonsense mutation (p.Y3745*), were identified as disease causative in the five investigated families, of which three reported to have consanguineous marriage. Among all seven mutations, six were novel, and one was recurrent. Two homozygous missense mutations (p.P2762A and p.G3320C) were found in one individual family suggesting a potential double hit effect. Significant phenotypic divergences were revealed among the five families. Three families of the five families were affected with early, moderated, or late onset RP, one with RPSP, and the other one with USH2. Our study expands the genotypic and phenotypic variability relevant to USH2A mutations, which would help with a clear insight into the complex genetic and phenotypic spectrums relevant to USH2A defects, and is complementary for a better management of patients with such mutations. We have also demonstrated that a targeted NGS approach is a valuable tool for the genetic diagnosis of USH2 and RP. PMID:25133613

Use of phylogenetic and phenotypic analyses to identify nonhemolytic streptococci isolated from bacteremic patients.

PubMed

Hoshino, Tomonori; Fujiwara, Taku; Kilian, Mogens

2005-12-01

The aim of this study was to evaluate molecular and phenotypic methods for the identification of nonhemolytic streptococci. A collection of 148 strains consisting of 115 clinical isolates from cases of infective endocarditis, septicemia, and meningitis and 33 reference strains, including type strains of all relevant Streptococcus species, were examined. Identification was performed by phylogenetic analysis of nucleotide sequences of four housekeeping genes, ddl, gdh, rpoB, and sodA; by PCR analysis of the glucosyltransferase (gtf) gene; and by conventional phenotypic characterization and identification using two commercial kits, Rapid ID 32 STREP and STREPTOGRAM and the associated databases. A phylogenetic tree based on concatenated sequences of the four housekeeping genes allowed unequivocal differentiation of recognized species and was used as the reference. Analysis of single gene sequences revealed deviation clustering in eight strains (5.4%) due to homologous recombination with other species. This was particularly evident in S. sanguinis and in members of the anginosus group of streptococci. The rate of correct identification of the strains by both commercial identification kits was below 50% but varied significantly between species. The most significant problems were observed with S. mitis and S. oralis and 11 Streptococcus species described since 1991. Our data indicate that identification based on multilocus sequence analysis is optimal. As a more practical alternative we recommend identification based on sodA sequences with reference to a comprehensive set of sequences that is available for downloading from our server. An analysis of the species distribution of 107 nonhemolytic streptococci from bacteremic patients showed a predominance of S. oralis and S. anginosus with various underlying infections.

Assessing the complex architecture of polygenic traits in diverged yeast populations.

PubMed

Cubillos, Francisco A; Billi, Eleonora; Zörgö, Enikö; Parts, Leopold; Fargier, Patrick; Omholt, Stig; Blomberg, Anders; Warringer, Jonas; Louis, Edward J; Liti, Gianni

2011-04-01

Phenotypic variation arising from populations adapting to different niches has a complex underlying genetic architecture. A major challenge in modern biology is to identify the causative variants driving phenotypic variation. Recently, the baker's yeast, Saccharomyces cerevisiae has emerged as a powerful model for dissecting complex traits. However, past studies using a laboratory strain were unable to reveal the complete architecture of polygenic traits. Here, we present a linkage study using 576 recombinant strains obtained from crosses of isolates representative of the major lineages. The meiotic recombinational landscape appears largely conserved between populations; however, strain-specific hotspots were also detected. Quantitative measurements of growth in 23 distinct ecologically relevant environments show that our recombinant population recapitulates most of the standing phenotypic variation described in the species. Linkage analysis detected an average of 6.3 distinct QTLs for each condition tested in all crosses, explaining on average 39% of the phenotypic variation. The QTLs detected are not constrained to a small number of loci, and the majority are specific to a single cross-combination and to a specific environment. Moreover, crosses between strains of similar phenotypes generate greater variation in the offspring, suggesting the presence of many antagonistic alleles and epistatic interactions. We found that subtelomeric regions play a key role in defining individual quantitative variation, emphasizing the importance of the adaptive nature of these regions in natural populations. This set of recombinant strains is a powerful tool for investigating the complex architecture of polygenic traits. © 2011 Blackwell Publishing Ltd.

Genome-wide association study to identify potential genetic modifiers in a canine model for Duchenne muscular dystrophy.

PubMed

Brinkmeyer-Langford, Candice; Balog-Alvarez, Cynthia; Cai, James J; Davis, Brian W; Kornegay, Joe N

2016-08-22

Duchenne muscular dystrophy (DMD) causes progressive muscle degeneration, cardiomyopathy and respiratory failure in approximately 1/5,000 boys. Golden Retriever muscular dystrophy (GRMD) resembles DMD both clinically and pathologically. Like DMD, GRMD exhibits remarkable phenotypic variation among affected dogs, suggesting the influence of modifiers. Understanding the role(s) of genetic modifiers of GRMD may identify genes and pathways that also modify phenotypes in DMD and reveal novel therapies. Therefore, our objective in this study was to identify genetic modifiers that affect discrete GRMD phenotypes. We performed a linear mixed-model (LMM) analysis using 16 variably-affected dogs from our GRMD colony (8 dystrophic, 8 non-dystrophic). All of these dogs were either full or half-siblings, and phenotyped for 19 objective, quantitative biomarkers at ages 6 and 12 months. Each biomarker was individually assessed. Gene expression profiles of 59 possible candidate genes were generated for two muscle types: the cranial tibialis and medial head of the gastrocnemius. SNPs significantly associated with GRMD biomarkers were identified on multiple chromosomes (including the X chromosome). Gene expression levels for candidate genes located near these SNPs correlated with biomarker values, suggesting possible roles as GRMD modifiers. The results of this study enhance our understanding of GRMD pathology and represent a first step toward the characterization of GRMD modifiers that may be relevant to DMD pathology. Such modifiers are likely to be useful for DMD treatment development based on their relationships to GRMD phenotypes.

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.

Characteristics of Rare or Recently Described Corynebacterium Species Recovered from Human Clinical Material in Canada

PubMed Central

Bernard, K. A.; Munro, C.; Wiebe, D.; Ongsansoy, E.

2002-01-01

Nineteen new Corynebacterium species or taxa described since 1995 have been associated with human disease. We report the characteristics of 72 strains identified as or most closely resembling 14 of these newer, medically relevant Corynebacterium species or taxa, as well as describe in brief an isolate of Corynebacterium bovis, a rare pathogen for humans. The bacteria studied in this report were nearly all derived from human clinical specimens and were identified by a polyphasic approach. Most were characterized by nearly full 16S rRNA gene sequence analysis. Some isolates were recovered from previously unreported sources and exhibited unusual phenotypes or represented the first isolates found outside Europe. Products of fermentation, with emphasis on the presence or absence of propionic acid, were also studied in order to provide an additional characteristic with which to differentiate among phenotypically similar species. PMID:12409436

BDNF rs6265 methylation and genotype interact on risk for schizophrenia

PubMed Central

Ursini, Gianluca; Cavalleri, Tommaso; Fazio, Leonardo; Angrisano, Tiziana; Iacovelli, Luisa; Porcelli, Annamaria; Maddalena, Giancarlo; Punzi, Giovanna; Mancini, Marina; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Calabrese, Francesca; Rampino, Antonio; Taurisano, Paolo; Giorgio, Annabella Di; Keller, Simona; Tarantini, Letizia; Sinibaldi, Lorenzo; Quarto, Tiziana; Popolizio, Teresa; Caforio, Grazia; Blasi, Giuseppe; Riva, Marco A.; De Blasi, Antonio; Chiariotti, Lorenzo; Bollati, Valentina; Bertolino, Alessandro

2016-01-01

Abstract Epigenetic mechanisms can mediate gene-environment interactions relevant for complex disorders. The BDNF gene is crucial for development and brain plasticity, is sensitive to environmental stressors, such as hypoxia, and harbors the functional SNP rs6265 (Val66Met), which creates or abolishes a CpG dinucleotide for DNA methylation. We found that methylation at the BDNF rs6265 Val allele in peripheral blood of healthy subjects is associated with hypoxia-related early life events (hOCs) and intermediate phenotypes for schizophrenia in a distinctive manner, depending on rs6265 genotype: in ValVal individuals increased methylation is associated with exposure to hOCs and impaired working memory (WM) accuracy, while the opposite is true for ValMet subjects. Also, rs6265 methylation and hOCs interact in modulating WM-related prefrontal activity, another intermediate phenotype for schizophrenia, with an analogous opposite direction in the 2 genotypes. Consistently, rs6265 methylation has a different association with schizophrenia risk in ValVals and ValMets. The relationships of methylation with BDNF levels and of genotype with BHLHB2 binding likely contribute to these opposite effects of methylation. We conclude that BDNF rs6265 methylation interacts with genotype to bridge early environmental exposures to adult phenotypes, relevant for schizophrenia. The study of epigenetic changes in regions containing genetic variation relevant for human diseases may have beneficial implications for the understanding of how genes are actually translated into phenotypes. PMID:26889735

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

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

SacconePhD, Scott F; Chesler, Elissa J; Bierut, Laura J

Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well representedmore » by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.« less

Prevalence and clinical characteristics of metabolically healthy obese individuals and other obese/non-obese metabolic phenotypes in a working population: results from the Icaria study.

PubMed

Goday, Albert; Calvo, Eva; Vázquez, Luis Alberto; Caveda, Elena; Margallo, Teresa; Catalina-Romero, Carlos; Reviriego, Jesús

2016-04-01

Metabolically healthy obese (MHO) phenotype may present with distinct characteristics compared with those with a metabolically unhealthy obese phenotype. Epidemiologic data on the distribution of these conditions in the working population are lacking. We aimed to evaluate the prevalence and clinical characteristics of MHO and other obese/non-obese metabolic phenotypes in a working population. Cross-sectional analysis of all subjects who had undergone a medical examination with Ibermutuamur Prevention Society from May 2004 to December 2007. Participants were classified into 5 categories according to their body mass index (BMI); within each of these categories, participants were further classified as metabolically healthy (MH) or metabolically unhealthy (MUH) according to the modified NCEP-ATPIII criteria. A logistic regression analysis was performed to evaluate some clinically relevant factors associated with a MH status. In the overall population, the prevalence of the MHO phenotype was 8.6%. The proportions of MH individuals in the overweight and obese categories were: 87.1% (overweight) and 55.5% (obese I-III [58.8, 40.0, and 38.7% of the obese I, II, and III categories, respectively]). When the overweight and obese categories were considered, compared with individuals who were MUH, those who were MH tended to be younger and more likely to be female or participate in physical exercise; they were also less likely to smoke, or to be a heavy drinker. In the underweight and normal weight categories, compared with individuals who were MH, those who were MUH were more likely to be older, male, manual (blue collar) workers, smokers and heavy drinkers. Among participants in the MUH, normal weight group, the proportion of individuals with a sedentary lifestyle was higher relative to those in the MH, normal weight group. The factors more strongly associated with the MUH phenotype were BMI and age, followed by the presence of hypercholesterolemia, male sex, being a smoker, being a heavy drinker, and lack of physical exercise. The prevalence of individuals with a MHO phenotype in the working population is high. This population may constitute an appropriate target group in whom to implement lifestyle modification initiatives to reduce the likelihood of transition to a MUH phenotype.

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

Systematic Internal Transcribed Spacer Sequence Analysis for Identification of Clinical Mold Isolates in Diagnostic Mycology: a 5-Year Study▿ †

PubMed Central

Ciardo, Diana E.; Lucke, Katja; Imhof, Alex; Bloemberg, Guido V.; Böttger, Erik C.

2010-01-01

The implementation of internal transcribed spacer (ITS) sequencing for routine identification of molds in the diagnostic mycology laboratory was analyzed in a 5-year study. All mold isolates (n = 6,900) recovered in our laboratory from 2005 to 2009 were included in this study. According to a defined work flow, which in addition to troublesome phenotypic identification takes clinical relevance into account, 233 isolates were subjected to ITS sequence analysis. Sequencing resulted in successful identification for 78.6% of the analyzed isolates (57.1% at species level, 21.5% at genus level). In comparison, extended in-depth phenotypic characterization of the isolates subjected to sequencing achieved taxonomic assignment for 47.6% of these, with a mere 13.3% at species level. Optimization of DNA extraction further improved the efficacy of molecular identification. This study is the first of its kind to testify to the systematic implementation of sequence-based identification procedures in the routine workup of mold isolates in the diagnostic mycology laboratory. PMID:20573873

Comparative genotypic and phenotypic analysis of human peripheral blood monocytes and surrogate monocyte-like cell lines commonly used in metabolic disease research.

PubMed

Riddy, Darren M; Goy, Emily; Delerive, Philippe; Summers, Roger J; Sexton, Patrick M; Langmead, Christopher J

2018-01-01

Monocyte-like cell lines (MCLCs), including THP-1, HL-60 and U-937 cells, are used routinely as surrogates for isolated human peripheral blood mononuclear cells (PBMCs). To systematically evaluate these immortalised cells and PBMCs as model systems to study inflammation relevant to the pathogenesis of type II diabetes and immuno-metabolism, we compared mRNA expression of inflammation-relevant genes, cell surface expression of cluster of differentiation (CD) markers, and chemotactic responses to inflammatory stimuli. Messenger RNA expression analysis suggested most genes were present at similar levels across all undifferentiated cells, though notably, IDO1, which encodes for indoleamine 2,3-dioxygenase and catabolises tryptophan to kynureninase (shown to be elevated in serum from diabetic patients), was not expressed in any PMA-treated MCLC, but present in GM-CSF-treated PBMCs. There was little overall difference in the pattern of expression of CD markers across all cells, though absolute expression levels varied considerably and the correlation between MCLCs and PBMCs was improved upon MCLC differentiation. Functionally, THP-1 and PBMCs migrated in response to chemoattractants in a transwell assay, with varying sensitivity to MCP-1, MIP-1α and LTB-4. However, despite similar gene and CD expression profiles, U-937 cells were functionally impaired as no migration was observed to any chemoattractant. Our analysis reveals that the MCLCs examined only partly replicate the genotypic and phenotypic properties of human PBMCs. To overcome such issues a universal differentiation protocol should be implemented for these cell lines, similar to those already used with isolated monocytes. Although not perfect, in our hands the THP-1 cells represent the closest, simplified surrogate model of PBMCs for study of inflammatory cell migration.

SIN3A mutations are rare in men with azoospermia.

PubMed

Miyamoto, T; Koh, E; Tsujimura, A; Miyagawa, Y; Minase, G; Ueda, Y; Namiki, M; Sengoku, K

2015-11-01

A loss of function of the murine Sin3A gene resulted in male infertility with Sertoli cell-only syndrome (SCOS) phenotype in mice. Here, we investigated the relevance of this gene to human male infertility with azoospermia caused by SCOS. Mutation analysis of SIN3A in the coding region was performed on 80 Japanese patients. However, no variants could be detected. This study suggests a lack of association of SIN3A gene sequence variants with azoospermia caused by SCOS in humans. © 2014 Blackwell Verlag GmbH.

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.

Multi-system Component Phenotypes of Bipolar Disorder for Genetic Investigations of Extended Pedigrees

PubMed Central

Fears, Scott C.; Service, Susan K.; Kremeyer, Barbara; Araya, Carmen; Araya, Xinia; Bejarano, Julio; Ramirez, Margarita; Castrillón, Gabriel; Gomez-Franco, Juliana; Lopez, Maria C.; Montoya, Gabriel; Montoya, Patricia; Aldana, Ileana; Teshiba, Terri M.; Abaryan, Zvart; Al-Sharif, Noor B.; Ericson, Marissa; Jalbrzikowski, Maria; Luykx, Jurjen J.; Navarro, Linda; Tishler, Todd A.; Altshuler, Lori; Bartzokis, George; Escobar, Javier; Glahn, David C.; Ospina-Duque, Jorge; Risch, Neil; Ruiz-Linares, Andrés; Thompson, Paul M.; Cantor, Rita M.; Lopez-Jaramillo, Carlos; Macaya, Gabriel; Molina, Julio; Reus, Victor I.; Sabatti, Chiara; Freimer, Nelson B.; Bearden, Carrie E.

2014-01-01

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), yet its pathogenesis remains poorly understood. A focus on measuring multi-system quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that impact on BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomic phenotypes that appear heritable and associated with severe bipolar disorder (BP-I), and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN Multi-generational pedigree study in two closely related, genetically isolated populations: the Central Valley of Costa Rica (CVCR) and Antioquia, Colombia (ANT). PARTICIPANTS 738 individuals, all from CVCR and ANT pedigrees, of whom 181 are affected with BP-I. MAIN OUTCOME MEASURE Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) phenotypes. RESULTS Seventy-five percent (126) of the phenotypes investigated were significantly heritable, and 31% (53) were associated with BP-I. About 1/4 of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions, and volume and microstructural integrity of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND RELEVANCE This is the most extensive investigation of BP-relevant component phenotypes to date. Our results identify brain and behavioral quantitative traits that appear to be genetically influenced and show a pattern of BP-I-association within families that is consistent with expectations from case-control studies. Together these phenotypes provide a basis for identifying loci contributing to BP-I risk and for genetic dissection of the disorder. PMID:24522887

Gait disorders in the elderly and dual task gait analysis: a new approach for identifying motor phenotypes.

PubMed

Auvinet, Bernard; Touzard, Claude; Montestruc, François; Delafond, Arnaud; Goeb, Vincent

2017-01-31

Gait disorders and gait analysis under single and dual-task conditions are topics of great interest, but very few studies have looked for the relevance of gait analysis under dual-task conditions in elderly people on the basis of a clinical approach. An observational study including 103 patients (mean age 76.3 ± 7.2, women 56%) suffering from gait disorders or memory impairment was conducted. Gait analysis under dual-task conditions was carried out for all patients. Brain MRI was performed in the absence of contra-indications. Three main gait variables were measured: walking speed, stride frequency, and stride regularity. For each gait variable, the dual task cost was computed and a quartile analysis was obtained. Nonparametric tests were used for all the comparisons (Wilcoxon, Kruskal-Wallis, Fisher or Chi 2 tests). Four clinical subgroups were identified: gait instability (45%), recurrent falls (29%), memory impairment (18%), and cautious gait (8%). The biomechanical severity of these subgroups was ordered according to walking speed and stride regularity under both conditions, from least to most serious as follows: memory impairment, gait instability, recurrent falls, cautious gait (p < 0.01 for walking speed, p = 0.05 for stride regularity). According to the established diagnoses of gait disorders, 5 main pathological subgroups were identified (musculoskeletal diseases (n = 11), vestibular diseases (n = 6), mild cognitive impairment (n = 24), central nervous system pathologies, (n = 51), and without diagnosis (n = 8)). The dual task cost for walking speed, stride frequency and stride regularity were different among these subgroups (p < 0.01). The subgroups mild cognitive impairment and central nervous system pathologies both showed together a higher dual task cost for each variable compared to the other subgroups combined (p = 0.01). The quartile analysis of dual task cost for stride frequency and stride regularity allowed the identification of 3 motor phenotypes (p < 0.01), without any difference for white matter hyperintensities, but with an increased Scheltens score from the first to the third motor phenotype (p = 0.05). Gait analysis under dual-task conditions in elderly people suffering from gait disorders or memory impairment is of great value in assessing the severity of gait disorders, differentiating between peripheral pathologies and central nervous system pathologies, and identifying motor phenotypes. Correlations between motor phenotypes and brain imaging require further studies.

The differential view of genotype–phenotype relationships

PubMed Central

Orgogozo, Virginie; Morizot, Baptiste; Martin, Arnaud

2015-01-01

An integrative view of diversity and singularity in the living world requires a better understanding of the intricate link between genotypes and phenotypes. Here we re-emphasize the old standpoint that the genotype–phenotype (GP) relationship is best viewed as a connection between two differences, one at the genetic level and one at the phenotypic level. As of today, predominant thinking in biology research is that multiple genes interact with multiple environmental variables (such as abiotic factors, culture, or symbionts) to produce the phenotype. Often, the problem of linking genotypes and phenotypes is framed in terms of genotype and phenotype maps, and such graphical representations implicitly bring us away from the differential view of GP relationships. Here we show that the differential view of GP relationships is a useful explanatory framework in the context of pervasive pleiotropy, epistasis, and environmental effects. In such cases, it is relevant to view GP relationships as differences embedded into differences. Thinking in terms of differences clarifies the comparison between environmental and genetic effects on phenotypes and helps to further understand the connection between genotypes and phenotypes. PMID:26042146

The down syndrome behavioral phenotype: implications for practice and research in occupational therapy.

PubMed

Daunhauer, Lisa A; Fidler, Deborah J

2011-01-01

ABSTRACT Down syndrome (DS) is the most common chromosomal cause of intellectual disability. The genetic causes of DS are associated with characteristic outcomes, such as relative strengths in visual-spatial skills and relative challenges in motor planning. This profile of outcomes, called the DS behavioral phenotype, may be a critical tool for intervention planning and research in this population. In this article, aspects of the DS behavioral phenotype potentially relevant to occupational therapy practice are reviewed. Implications and challenges for etiology-informed research and practice are discussed.

Bedside Back to Bench: Building Bridges between Basic and Clinical Genomic Research.

PubMed

Manolio, Teri A; Fowler, Douglas M; Starita, Lea M; Haendel, Melissa A; MacArthur, Daniel G; Biesecker, Leslie G; Worthey, Elizabeth; Chisholm, Rex L; Green, Eric D; Jacob, Howard J; McLeod, Howard L; Roden, Dan; Rodriguez, Laura Lyman; Williams, Marc S; Cooper, Gregory M; Cox, Nancy J; Herman, Gail E; Kingsmore, Stephen; Lo, Cecilia; Lutz, Cathleen; MacRae, Calum A; Nussbaum, Robert L; Ordovas, Jose M; Ramos, Erin M; Robinson, Peter N; Rubinstein, Wendy S; Seidman, Christine; Stranger, Barbara E; Wang, Haoyi; Westerfield, Monte; Bult, Carol

2017-03-23

Genome sequencing has revolutionized the diagnosis of genetic diseases. Close collaborations between basic scientists and clinical genomicists are now needed to link genetic variants with disease causation. To facilitate such collaborations, we recommend prioritizing clinically relevant genes for functional studies, developing reference variant-phenotype databases, adopting phenotype description standards, and promoting data sharing. Published by Elsevier Inc.

Bedside Back to Bench: Building Bridges between Basic and Clinical Genomic Research

PubMed Central

Manolio, Teri A.; Fowler, Douglas M.; Starita, Lea M.; Haendel, Melissa A.; MacArthur, Daniel G.; Biesecker, Leslie G.; Worthey, Elizabeth; Chisholm, Rex L.; Green, Eric D.; Jacob, Howard J.; McLeod, Howard L.; Roden, Dan; Rodriguez, Laura Lyman; Williams, Marc S.; Cooper, Gregory M.; Cox, Nancy J.; Herman, Gail E.; Kingsmore, Stephen; Lo, Cecilia; Lutz, Cathleen; MacRae, Calum A.; Nussbaum, Robert L.; Ordovas, Jose M.; Ramos, Erin M.; Robinson, Peter N.; Rubinstein, Wendy S.; Seidman, Christine; Stranger, Barbara E.; Wang, Haoyi; Westerfield, Monte; Bult, Carol

2017-01-01

Summary Genome sequencing has revolutionized the diagnosis of genetic diseases. Close collaborations between basic scientists and clinical genomicists are now needed to link genetic variants with disease causation. To facilitate such collaborations we recommend prioritizing clinically relevant genes for functional studies, developing reference variant-phenotype databases, adopting phenotype description standards, and promoting data sharing. PMID:28340351

Exploring the Phenotypic Space and the Evolutionary History of a Natural Mutation in Drosophila melanogaster.

PubMed

Ullastres, Anna; Petit, Natalia; González, Josefa

2015-07-01

A major challenge of modern Biology is elucidating the functional consequences of natural mutations. Although we have a good understanding of the effects of laboratory-induced mutations on the molecular- and organismal-level phenotypes, the study of natural mutations has lagged behind. In this work, we explore the phenotypic space and the evolutionary history of a previously identified adaptive transposable element insertion. We first combined several tests that capture different signatures of selection to show that there is evidence of positive selection in the regions flanking FBti0019386 insertion. We then explored several phenotypes related to known phenotypic effects of nearby genes, and having plausible connections to fitness variation in nature. We found that flies with FBti0019386 insertion had a shorter developmental time and were more sensitive to stress, which are likely to be the adaptive effect and the cost of selection of this mutation, respectively. Interestingly, these phenotypic effects are not consistent with a role of FBti0019386 in temperate adaptation as has been previously suggested. Indeed, a global analysis of the population frequency of FBti0019386 showed that climatic variables explain well the FBti0019386 frequency patterns only in Australia. Finally, although FBti0019386 insertion could be inducing the formation of heterochromatin by recruiting HP1a (Heterochromatin Protein 1a) protein, the insertion is associated with upregulation of sra in adult females. Overall, our integrative approach allowed us to shed light on the evolutionary history, the relevant fitness effects, and the likely molecular mechanisms of an adaptive mutation and highlights the complexity of natural genetic variants. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

In silico molecular comparisons of C. elegans and mammalian pharmacology identify distinct targets that regulate feeding.

PubMed

Lemieux, George A; Keiser, Michael J; Sassano, Maria F; Laggner, Christian; Mayer, Fahima; Bainton, Roland J; Werb, Zena; Roth, Bryan L; Shoichet, Brian K; Ashrafi, Kaveh

2013-11-01

Phenotypic screens can identify molecules that are at once penetrant and active on the integrated circuitry of a whole cell or organism. These advantages are offset by the need to identify the targets underlying the phenotypes. Additionally, logistical considerations limit screening for certain physiological and behavioral phenotypes to organisms such as zebrafish and C. elegans. This further raises the challenge of elucidating whether compound-target relationships found in model organisms are preserved in humans. To address these challenges we searched for compounds that affect feeding behavior in C. elegans and sought to identify their molecular mechanisms of action. Here, we applied predictive chemoinformatics to small molecules previously identified in a C. elegans phenotypic screen likely to be enriched for feeding regulatory compounds. Based on the predictions, 16 of these compounds were tested in vitro against 20 mammalian targets. Of these, nine were active, with affinities ranging from 9 nM to 10 µM. Four of these nine compounds were found to alter feeding. We then verified the in vitro findings in vivo through genetic knockdowns, the use of previously characterized compounds with high affinity for the four targets, and chemical genetic epistasis, which is the effect of combined chemical and genetic perturbations on a phenotype relative to that of each perturbation in isolation. Our findings reveal four previously unrecognized pathways that regulate feeding in C. elegans with strong parallels in mammals. Together, our study addresses three inherent challenges in phenotypic screening: the identification of the molecular targets from a phenotypic screen, the confirmation of the in vivo relevance of these targets, and the evolutionary conservation and relevance of these targets to their human orthologs.

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

PubMed Central

Zhong, Sheng; McPeek, Mary Sara

2016-01-01

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan. PMID:27695091

Phenotypic and genetic overlap between autistic traits at the extremes of the general population.

PubMed

Ronald, Angelica; Happé, Francesca; Price, Thomas S; Baron-Cohen, Simon; Plomin, Robert

2006-10-01

To investigate children selected from a community sample for showing extreme autistic-like traits and to assess the degree to which these individual traits--social impairments (SIs), communication impairments (CIs), and restricted repetitive behaviors and interests (RRBIs)--are caused by genes and environments, whether all of them are caused by the same genes and environments, and how often they occur together (as required by an autism diagnosis). The most extreme-scoring 5% were selected from 3,419 8-year-old pairs in the Twins Early Development Study assessed on the Childhood Asperger Syndrome Test. Phenotypic associations between extreme traits were compared with associations among the full-scale scores. Genetic associations between extreme traits were quantified using bivariate DeFries-Fulker extremes analysis. Phenotypic relationships between extreme SIs, CIs, and RRBIs were modest. There was a degree of genetic overlap between them, but also substantial genetic specificity. This first twin study assessing the links between extreme individual autistic-like traits (SIs, CIs, and RRBIs) found that all are highly heritable but show modest phenotypic and genetic overlap. This finding concurs with that of an earlier study from the same cohort that showed that a total autistic symptoms score at the extreme showed high heritability and that SIs, CIs, and RRBIs show weak links in the general population. This new finding has relevance for both clinical models and future molecular genetic studies.

Comparative proteomic analysis of off-type and normal phenotype somatic plantlets derived from somatic embryos of Feijoa (Acca sellowiana (O. Berg) Burret).

PubMed

Fraga, Hugo Pacheco de Freitas; Agapito-Tenfen, Sarah Zanon; Caprestano, Clarissa Alves; Nodari, Rubens Onofre; Guerra, Miguel Pedro

2013-09-01

Morphological disorders in a relevant portion of emerged somatic embryos have been a limiting factor in the true-to-type plantlet formation in Acca sellowiana. In this sense, the present study undertook a comparison between normal phenotype and off-type somatic plantlets protein profiles by means of the 2-D DIGE proteomics approach. Off-type and normal phenotype somatic plantlets obtained at 10 and 20 days conversion were evaluated. Results indicated 12 exclusive spots between normal and off-type plantlets at 10 days conversion, and 17 exclusive spots at 20 days conversion. Also at 20 days conversion, 4 spots were differentially expressed, up- or down-regulated. Two proteins related to carbohydrate metabolism were only expressed in off-types at 10 days conversion, suggesting a more active respiratory pathway. A vicilin-like storage protein was only found in off-types at 20 days conversion, indicating that plantlets may present an abnormality in the mobilization of storage compounds, causing reduced vigor in the development of derived plantlets. The presence of heat shock proteins were only observed during formation of normal phenotype somatic plantlets, indicating that these proteins may be involved in normal morphogenesis of plantlets formed. These new findings shed light on possible genetic or epigenetic mechanisms governing A. sellowiana morphogenesis. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Phenotypic models of evolution and development: geometry as destiny.

PubMed

François, Paul; Siggia, Eric D

2012-12-01

Quantitative models of development that consider all relevant genes typically are difficult to fit to embryonic data alone and have many redundant parameters. Computational evolution supplies models of phenotype with relatively few variables and parameters that allows the patterning dynamics to be reduced to a geometrical picture for how the state of a cell moves. The clock and wavefront model, that defines the phenotype of somitogenesis, can be represented as a sequence of two discrete dynamical transitions (bifurcations). The expression-time to space map for Hox genes and the posterior dominance rule are phenotypes that naturally follow from computational evolution without considering the genetics of Hox regulation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Geometric Morphometrics on Gene Expression Patterns Within Phenotypes: A Case Example on Limb Development

PubMed Central

Martínez-Abadías, Neus; Mateu, Roger; Niksic, Martina; Russo, Lucia; Sharpe, James

2016-01-01

How the genotype translates into the phenotype through development is critical to fully understand the evolution of phenotypes. We propose a novel approach to directly assess how changes in gene expression patterns are associated with changes in morphology using the limb as a case example. Our method combines molecular biology techniques, such as whole-mount in situ hybridization, with image and shape analysis, extending the use of Geometric Morphometrics to the analysis of nonanatomical shapes, such as gene expression domains. Elliptical Fourier and Procrustes-based semilandmark analyses were used to analyze the variation and covariation patterns of the limb bud shape with the expression patterns of two relevant genes for limb morphogenesis, Hoxa11 and Hoxa13. We devised a multiple thresholding method to semiautomatically segment gene domains at several expression levels in large samples of limb buds from C57Bl6 mouse embryos between 10 and 12 postfertilization days. Besides providing an accurate phenotyping tool to quantify the spatiotemporal dynamics of gene expression patterns within developing structures, our morphometric analyses revealed high, non-random, and gene-specific variation undergoing canalization during limb development. Our results demonstrate that Hoxa11 and Hoxa13, despite being paralogs with analogous functions in limb patterning, show clearly distinct dynamic patterns, both in shape and size, and are associated differently with the limb bud shape. The correspondence between our results and already well-established molecular processes underlying limb development confirms that this morphometric approach is a powerful tool to extract features of development regulating morphogenesis. Such multilevel analyses are promising in systems where not so much molecular information is available and will advance our understanding of the genotype–phenotype map. In systematics, this knowledge will increase our ability to infer how evolution modified a common developmental pattern to generate a wide diversity of morphologies, as in the vertebrate limb. PMID:26377442

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

DOE PAGES

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-08-31

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group ofmore » homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.« less

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

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

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group ofmore » homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.« less

Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions

PubMed Central

Snitkin, Evan S; Dudley, Aimée M; Janse, Daniel M; Wong, Kaisheen; Church, George M; Segrè, Daniel

2008-01-01

Background Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored. Results In this study, we measured growth phenotypes of 465 Saccharomyces cerevisiae gene deletion mutants under 16 metabolically relevant conditions and integrated them with the corresponding flux balance model predictions. We first used discordance between experimental results and model predictions to guide a stage of experimental refinement, which resulted in a significant improvement in the quality of the experimental data. Next, we used discordance still present in the refined experimental data to assess the reliability of yeast metabolism models under different conditions. In addition to estimating predictive capacity based on growth phenotypes, we sought to explain these discordances by examining predicted flux distributions visualized through a new, freely available platform. This analysis led to insight into the glycerol utilization pathway and the potential effects of metabolic shortcuts on model results. Finally, we used model predictions and experimental data to discriminate between alternative raffinose catabolism routes. Conclusions Our study demonstrates how a new level of integration between high throughput measurements and flux balance model predictions can improve understanding of both experimental and computational results. The added value of a joint analysis is a more reliable platform for specific testing of biological hypotheses, such as the catabolic routes of different carbon sources. PMID:18808699

Epileptic spasms are a feature of DEPDC5 mTORopathy

PubMed Central

Carvill, Gemma L.; Crompton, Douglas E.; Regan, Brigid M.; McMahon, Jacinta M.; Saykally, Julia; Zemel, Matthew; Schneider, Amy L.; Dibbens, Leanne; Howell, Katherine B.; Mandelstam, Simone; Leventer, Richard J.; Harvey, A. Simon; Mullen, Saul A.; Berkovic, Samuel F.; Sullivan, Joseph; Scheffer, Ingrid E.

2015-01-01

Objective: To assess the presence of DEPDC5 mutations in a cohort of patients with epileptic spasms. Methods: We performed DEPDC5 resequencing in 130 patients with spasms, segregation analysis of variants of interest, and detailed clinical assessment of patients with possibly and likely pathogenic variants. Results: We identified 3 patients with variants in DEPDC5 in the cohort of 130 patients with spasms. We also describe 3 additional patients with DEPDC5 alterations and epileptic spasms: 2 from a previously described family and a third ascertained by clinical testing. Overall, we describe 6 patients from 5 families with spasms and DEPDC5 variants; 2 arose de novo and 3 were familial. Two individuals had focal cortical dysplasia. Clinical outcome was highly variable. Conclusions: While recent molecular findings in epileptic spasms emphasize the contribution of de novo mutations, we highlight the relevance of inherited mutations in the setting of a family history of focal epilepsies. We also illustrate the utility of clinical diagnostic testing and detailed phenotypic evaluation in characterizing the constellation of phenotypes associated with DEPDC5 alterations. We expand this phenotypic spectrum to include epileptic spasms, aligning DEPDC5 epilepsies more with the recognized features of other mTORopathies. PMID:27066554

Overexpression of Nrp/b (nuclear restrict protein in brain) suppresses the malignant phenotype in the C6/ST1 glioma cell line.

PubMed

Degaki, Theri Leica; Demasi, Marcos Angelo Almeida; Sogayar, Mari Cleide

2009-11-01

Upon searching for glucocorticoid-regulated cDNA sequences associated with the transformed to normal phenotypic reversion of C6/ST1 rat glioma cells, we identified Nrp/b (nuclear restrict protein in brain) as a novel rat gene. Here we report on the identification and functional characterization of the complete sequence encoding the rat NRP/B protein. The cloned cDNA presented a 1767 nucleotides open-reading frame encoding a 589 amino acids residues sequence containing a BTB/POZ (broad complex Tramtrack bric-a-brac/Pox virus and zinc finger) domain in its N-terminal region and kelch motifs in its C-terminal region. Sequence analysis indicates that the rat Nrp/b displays a high level of identity with the equivalent gene orthologs from other organisms. Among rat tissues, Nrp/b expression is more pronounced in brain tissue. We show that overexpression of the Nrp/b cDNA in C6/ST1 cells suppresses anchorage independence in vitro and tumorigenicity in vivo, altering their malignant nature towards a more benign phenotype. Therefore, Nrp/b may be postulated as a novel tumor suppressor gene, with possible relevance for glioblastoma therapy.

T Cell Phenotype and T Cell Receptor Repertoire in Patients with Major Depressive Disorder

PubMed Central

Patas, Kostas; Willing, Anne; Demiralay, Cüneyt; Engler, Jan Broder; Lupu, Andreea; Ramien, Caren; Schäfer, Tobias; Gach, Christian; Stumm, Laura; Chan, Kenneth; Vignali, Marissa; Arck, Petra C.; Friese, Manuel A.; Pless, Ole; Wiedemann, Klaus; Agorastos, Agorastos; Gold, Stefan M.

2018-01-01

While a link between inflammation and the development of neuropsychiatric disorders, including major depressive disorder (MDD) is supported by a growing body of evidence, little is known about the contribution of aberrant adaptive immunity in this context. Here, we conducted in-depth characterization of T cell phenotype and T cell receptor (TCR) repertoire in MDD. For this cross-sectional case–control study, we recruited antidepressant-free patients with MDD without any somatic or psychiatric comorbidities (n = 20), who were individually matched for sex, age, body mass index, and smoking status to a non-depressed control subject (n = 20). T cell phenotype and repertoire were interrogated using a combination of flow cytometry, gene expression analysis, and next generation sequencing. T cells from MDD patients showed significantly lower surface expression of the chemokine receptors CXCR3 and CCR6, which are known to be central to T cell differentiation and trafficking. In addition, we observed a shift within the CD4+ T cell compartment characterized by a higher frequency of CD4+CD25highCD127low/− cells and higher FOXP3 mRNA expression in purified CD4+ T cells obtained from patients with MDD. Finally, flow cytometry-based TCR Vβ repertoire analysis indicated a less diverse CD4+ T cell repertoire in MDD, which was corroborated by next generation sequencing of the TCR β chain CDR3 region. Overall, these results suggest that T cell phenotype and TCR utilization are skewed on several levels in patients with MDD. Our study identifies putative cellular and molecular signatures of dysregulated adaptive immunity and reinforces the notion that T cells are a pathophysiologically relevant cell population in this disorder. PMID:29515587

Transcriptomic Analysis Using Olive Varieties and Breeding Progenies Identifies Candidate Genes Involved in Plant Architecture

PubMed Central

González-Plaza, Juan J.; Ortiz-Martín, Inmaculada; Muñoz-Mérida, Antonio; García-López, Carmen; Sánchez-Sevilla, José F.; Luque, Francisco; Trelles, Oswaldo; Bejarano, Eduardo R.; De La Rosa, Raúl; Valpuesta, Victoriano; Beuzón, Carmen R.

2016-01-01

Plant architecture is a critical trait in fruit crops that can significantly influence yield, pruning, planting density and harvesting. Little is known about how plant architecture is genetically determined in olive, were most of the existing varieties are traditional with an architecture poorly suited for modern growing and harvesting systems. In the present study, we have carried out microarray analysis of meristematic tissue to compare expression profiles of olive varieties displaying differences in architecture, as well as seedlings from their cross pooled on the basis of their sharing architecture-related phenotypes. The microarray used, previously developed by our group has already been applied to identify candidates genes involved in regulating juvenile to adult transition in the shoot apex of seedlings. Varieties with distinct architecture phenotypes and individuals from segregating progenies displaying opposite architecture features were used to link phenotype to expression. Here, we identify 2252 differentially expressed genes (DEGs) associated to differences in plant architecture. Microarray results were validated by quantitative RT-PCR carried out on genes with functional annotation likely related to plant architecture. Twelve of these genes were further analyzed in individual seedlings of the corresponding pool. We also examined Arabidopsis mutants in putative orthologs of these targeted candidate genes, finding altered architecture for most of them. This supports a functional conservation between species and potential biological relevance of the candidate genes identified. This study is the first to identify genes associated to plant architecture in olive, and the results obtained could be of great help in future programs aimed at selecting phenotypes adapted to modern cultivation practices in this species. PMID:26973682

Clonal analysis of synovial fluid stem cells to characterize and identify stable mesenchymal stromal cell/mesenchymal progenitor cell phenotypes in a porcine model: a cell source with enhanced commitment to the chondrogenic lineage.

PubMed

Ando, Wataru; Kutcher, Josh J; Krawetz, Roman; Sen, Arindom; Nakamura, Norimasa; Frank, Cyril B; Hart, David A

2014-06-01

Previous studies have demonstrated that porcine synovial membrane stem cells can adhere to a cartilage defect in vivo through the use of a tissue-engineered construct approach. To optimize this model, we wanted to compare effectiveness of tissue sources to determine whether porcine synovial fluid, synovial membrane, bone marrow and skin sources replicate our understanding of synovial fluid mesenchymal stromal cells or mesenchymal progenitor cells from humans both at the population level and the single-cell level. Synovial fluid clones were subsequently isolated and characterized to identify cells with a highly characterized optimal phenotype. The chondrogenic, osteogenic and adipogenic potentials were assessed in vitro for skin, bone marrow, adipose, synovial fluid and synovial membrane-derived stem cells. Synovial fluid cells then underwent limiting dilution analysis to isolate single clonal populations. These clonal populations were assessed for proliferative and differentiation potential by use of standardized protocols. Porcine-derived cells demonstrated the same relationship between cell sources as that demonstrated previously for humans, suggesting that the pig may be an ideal preclinical animal model. Synovial fluid cells demonstrated the highest chondrogenic potential that was further characterized, demonstrating the existence of a unique clonal phenotype with enhanced chondrogenic potential. Porcine stem cells demonstrate characteristics similar to those in human-derived mesenchymal stromal cells from the same sources. Synovial fluid-derived stem cells contain an inherent phenotype that may be optimal for cartilage repair. This must be more fully investigated for future use in the in vivo tissue-engineered construct approach in this physiologically relevant preclinical porcine model. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Maternal phenotype, independent of family economic capital, predicts educational attainment in lowland nepalese children

PubMed Central

Devakumar, Delan; Wells, Jonathan C.K.; Saville, Naomi; Reid, Alice; Costello, Anthony; Manandhar, Dharma S; Osrin, David

2016-01-01

Objectives Factors acting before children are born or reach school‐going age may explain why some do not complete primary education. Many relevant factors relate to maternal phenotype, but few studies have tested for independent associations of maternal factors relative to those characterizing the family in general. Methods Using data from a longitudinal study of 838 children in Dhanusha, Nepal, we used logistic regression models to test whether indices of maternal somatic and educational capital, or family economic capital, were independently associated with children having had ≤2 versus 3+ years of schooling at a mean age of 8.5 years. We also tested whether maternal age, children's early growth, and urban/rural location mediated such associations. Results Children had a higher risk of completing less schooling if their mothers were short, thin, anemic, and uneducated. Independently, lower family material assets and land acreage also increased children's odds of less schooling. There was an indication of gender differences, with the risk of poor educational attainment in girls associated with low maternal somatic and educational capital, whereas in boys the relevant factors were low maternal education and family land ownership. Conclusions Our analysis demonstrates that, independent of broader indices of family capital such as land or material assets, children's educational attainment is associated with factors embodied in maternal phenotype. Both somatic and educational maternal capital appeared important. A composite index of maternal capital could provide a new measurable proxy, prior to school entry, for identifying children at risk of completing fewer years of schooling. Am. J. Hum. Biol. 28:687–698, 2016. © 2016 Wiley Periodicals, Inc. PMID:27135632

Maternal phenotype, independent of family economic capital, predicts educational attainment in lowland nepalese children.

PubMed

Marphatia, Akanksha A; Devakumar, Delan; Wells, Jonathan C K; Saville, Naomi; Reid, Alice; Costello, Anthony; Manandhar, Dharma S; Osrin, David

2016-09-10

Factors acting before children are born or reach school-going age may explain why some do not complete primary education. Many relevant factors relate to maternal phenotype, but few studies have tested for independent associations of maternal factors relative to those characterizing the family in general. Using data from a longitudinal study of 838 children in Dhanusha, Nepal, we used logistic regression models to test whether indices of maternal somatic and educational capital, or family economic capital, were independently associated with children having had ≤2 versus 3+ years of schooling at a mean age of 8.5 years. We also tested whether maternal age, children's early growth, and urban/rural location mediated such associations. Children had a higher risk of completing less schooling if their mothers were short, thin, anemic, and uneducated. Independently, lower family material assets and land acreage also increased children's odds of less schooling. There was an indication of gender differences, with the risk of poor educational attainment in girls associated with low maternal somatic and educational capital, whereas in boys the relevant factors were low maternal education and family land ownership. Our analysis demonstrates that, independent of broader indices of family capital such as land or material assets, children's educational attainment is associated with factors embodied in maternal phenotype. Both somatic and educational maternal capital appeared important. A composite index of maternal capital could provide a new measurable proxy, prior to school entry, for identifying children at risk of completing fewer years of schooling. Am. J. Hum. Biol. 28:687-698, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors American Journal of Human Biology Published by Wiley Periodicals, Inc.

Parent-of-origin effects on schizophrenia-relevant behaviours of type III neuregulin 1 mutant mice.

PubMed

Shang, Kani; Talmage, David A; Karl, Tim

2017-08-14

A robust, disease-relevant phenotype is paramount to the validity of genetic mouse models, which are an important tool in understanding complex diseases. Recent evidence from genome-wide association studies suggests the genetic contribution of parents to offspring is not equivalent. Despite this, few studies to date have examined the potential impact of parent genotype (i.e. origin of mutation) on the offspring of disease-relevant genetic mouse models. To elucidate the potential impact of the sex of the mutant parent on offspring phenotype, we characterized male and female offspring of an established schizophrenia mouse model, which had been generated using two different breeding schemes, in a range of disease-relevant behaviours. We compared heterozygous type III neuregulin 1 mutant (type III Nrg1 +/- ) and wild type-like control (WT) offspring from mutant father x WT mother pairings with offspring from mutant mother x WT father pairings. Offspring were tested in schizophrenia-relevant paradigms including the elevated plus maze (EPM), fear conditioning (FC), prepulse inhibition (PPI), social interaction (SI), and open field (OF). We found type III Nrg1 +/- males from mutant fathers, but not mutant mothers, showed deficits in contextual fear-associated memory and exhibited increased social interaction, compared to their WT littermates. Type III Nrg1 +/- females across breeding colonies only exhibited a subtle change to their acoustic startle response and sensorimotor gating. These results suggest a paternal-dependent transmission of genetically induced behavioural characteristics. Though the mechanisms governing this phenomenon are unclear, our results show that parental origin of mutation can alter the behavioural phenotype of genetic mouse models. Thus, researchers should carefully consider their breeding scheme when dealing with genetic mouse models of diseases such as schizophrenia. Copyright © 2017. Published by Elsevier B.V.

Budding off: bringing functional genomics to Candida albicans

PubMed Central

Anderson, Matthew Z.

2016-01-01

Candida species are the most prevalent human fungal pathogens, with Candida albicans being the most clinically relevant species. Candida albicans resides as a commensal of the human gastrointestinal tract but is a frequent cause of opportunistic mucosal and systemic infections. Investigation of C. albicans virulence has traditionally relied on candidate gene approaches, but recent advances in functional genomics have now facilitated global, unbiased studies of gene function. Such studies include comparative genomics (both between and within Candida species), analysis of total RNA expression, and regulation and delineation of protein–DNA interactions. Additionally, large collections of mutant strains have begun to aid systematic screening of clinically relevant phenotypes. Here, we will highlight the development of functional genomics in C. albicans and discuss the use of these approaches to addressing both commensalism and pathogenesis in this species. PMID:26424829

13C-based metabolic flux analysis: fundamentals and practice.

PubMed

Yang, Tae Hoon

2013-01-01

Isotope-based metabolic flux analysis is one of the emerging technologies applied to system level metabolic phenotype characterization in metabolic engineering. Among the developed approaches, (13)C-based metabolic flux analysis has been established as a standard tool and has been widely applied to quantitative pathway characterization of diverse biological systems. To implement (13)C-based metabolic flux analysis in practice, comprehending the underlying mathematical and computational modeling fundamentals is of importance along with carefully conducted experiments and analytical measurements. Such knowledge is also crucial when designing (13)C-labeling experiments and properly acquiring key data sets essential for in vivo flux analysis implementation. In this regard, the modeling fundamentals of (13)C-labeling systems and analytical data processing are the main topics we will deal with in this chapter. Along with this, the relevant numerical optimization techniques are addressed to help implementation of the entire computational procedures aiming at (13)C-based metabolic flux analysis in vivo.

Recovery of phenotypes obtained by adaptive evolution through inverse metabolic engineering.

PubMed

Hong, Kuk-Ki; Nielsen, Jens

2012-11-01

In a previous study, system level analysis of adaptively evolved yeast mutants showing improved galactose utilization revealed relevant mutations. The governing mutations were suggested to be in the Ras/PKA signaling pathway and ergosterol metabolism. Here, site-directed mutants having one of the mutations RAS2(Lys77), RAS2(Tyr112), and ERG5(Pro370) were constructed and evaluated. The mutants were also combined with overexpression of PGM2, earlier proved as a beneficial target for galactose utilization. The constructed strains were analyzed for their gross phenotype, transcriptome and targeted metabolites, and the results were compared to those obtained from reference strains and the evolved strains. The RAS2(Lys77) mutation resulted in the highest specific galactose uptake rate among all of the strains with an increased maximum specific growth rate on galactose. The RAS2(Tyr112) mutation also improved the specific galactose uptake rate and also resulted in many transcriptional changes, including ergosterol metabolism. The ERG5(Pro370) mutation only showed a small improvement, but when it was combined with PGM2 overexpression, the phenotype was almost the same as that of the evolved mutants. Combination of the RAS2 mutations with PGM2 overexpression also led to a complete recovery of the adaptive phenotype in galactose utilization. Recovery of the gross phenotype by the reconstructed mutants was achieved with much fewer changes in the genome and transcriptome than for the evolved mutants. Our study demonstrates how the identification of specific mutations by systems biology can direct new metabolic engineering strategies for improving galactose utilization by yeast.

Phenotypic concordance in familial inflammatory bowel disease (IBD). Results of a nationwide IBD Spanish database.

PubMed

Cabré, Eduard; Mañosa, Míriam; García-Sánchez, Valle; Gutiérrez, Ana; Ricart, Elena; Esteve, Maria; Guardiola, Jordi; Aguas, Mariam; Merino, Olga; Ponferrada, Angel; Gisbert, Javier P; Garcia-Planella, Esther; Ceña, Gloria; Cabriada, José L; Montoro, Miguel; Domènech, Eugeni

2014-07-01

Disease outcome has been found to be poorer in familial inflammatory bowel disease (IBD) than in sporadic forms, but assessment of phenotypic concordance in familial IBD provided controversial results. We assessed the concordance for disease type and phenotypic features in IBD families. Patients with familial IBD were identified from the IBD Spanish database ENEIDA. Families in whom at least two members were in the database were selected for concordance analysis (κ index). Concordance for type of IBD [Crohn's disease (CD) vs. ulcerative colitis (UC)], as well as for disease extent, localization and behaviour, perianal disease, extraintestinal manifestations, and indicators of severe disease (i.e., need for immunosuppressors, biological agents, and surgery) for those pairs concordant for IBD type, were analyzed. 798 out of 11,905 IBD patients (7%) in ENEIDA had familial history of IBD. Complete data of 107 families (231 patients and 144 consanguineous pairs) were available for concordance analyses. The youngest members of the pairs were diagnosed with IBD at a significantly younger age (p<0.001) than the oldest ones. Seventy-six percent of pairs matched up for the IBD type (κ=0.58; 95%CI: 0.42-0.73, moderate concordance). There was no relevant concordance for any of the phenotypic items assessed in both diseases. Familial IBD is associated with diagnostic anticipation in younger individuals. Familial history does not allow predicting any phenotypic feature other than IBD type. Copyright © 2013 European Crohn's and Colitis Organisation. Published by Elsevier B.V. All rights reserved.

The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants.

PubMed

Hoehndorf, Robert; Alshahrani, Mona; Gkoutos, Georgios V; Gosline, George; Groom, Quentin; Hamann, Thomas; Kattge, Jens; de Oliveira, Sylvia Mota; Schmidt, Marco; Sierra, Soraya; Smets, Erik; Vos, Rutger A; Weiland, Claus

2016-11-14

The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text. We have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities. The FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established vocabularies or ontologies, but rather serve as an overarching framework based on which different application- and domain-specific ontologies, thesauri and vocabularies of phenotypes observed in flowering plants can be integrated.

Inheritance of brewing-relevant phenotypes in constructed Saccharomyces cerevisiae × Saccharomyces eubayanus hybrids.

PubMed

Krogerus, Kristoffer; Seppänen-Laakso, Tuulikki; Castillo, Sandra; Gibson, Brian

2017-04-21

Interspecific hybridization has proven to be a potentially valuable technique for generating de novo lager yeast strains that possess diverse and improved traits compared to their parent strains. To further enhance the value of hybridization for strain development, it would be desirable to combine phenotypic traits from more than two parent strains, as well as remove unwanted traits from hybrids. One such trait, that has limited the industrial use of de novo lager yeast hybrids, is their inherent tendency to produce phenolic off-flavours; an undesirable trait inherited from the Saccharomyces eubayanus parent. Trait removal and the addition of traits from a third strain could be achieved through sporulation and meiotic recombination or further mating. However, interspecies hybrids tend to be sterile, which impedes this opportunity. Here we generated a set of five hybrids from three different parent strains, two of which contained DNA from all three parent strains. These hybrids were constructed with fertile allotetraploid intermediates, which were capable of efficient sporulation. We used these eight brewing strains to examine two brewing-relevant phenotypes: stress tolerance and phenolic off-flavour formation. Lipidomics and multivariate analysis revealed links between several lipid species and the ability to ferment in low temperatures and high ethanol concentrations. Unsaturated fatty acids, such as oleic acid, and ergosterol were shown to positively influence growth at high ethanol concentrations. The ability to produce phenolic off-flavours was also successfully removed from one of the hybrids, Hybrid T2, through meiotic segregation. The potential application of these strains in industrial fermentations was demonstrated in wort fermentations, which revealed that the meiotic segregant Hybrid T2 not only didn't produce any phenolic off-flavours, but also reached the highest ethanol concentration and consumed the most maltotriose. Our study demonstrates the possibility of constructing complex yeast hybrids that possess traits that are relevant to industrial lager beer fermentation and that are derived from several parent strains. Yeast lipid composition was also shown to have a central role in determining ethanol and cold tolerance in brewing strains.

A Multivariate Twin Study of the DSM-IV Criteria for Antisocial Personality Disorder

PubMed Central

Kendler, Kenneth S.; Aggen, Steven H.; Patrick, Christopher J.

2012-01-01

BACKGROUND Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). METHODS Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4,291 twins (including both members of 1,647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. RESULTS Phenotypic factor analysis produced evidence for 2 correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. CONCLUSION From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. PMID:21762879

Mucosal wrinkling in animal antra induced by volumetric growth

NASA Astrophysics Data System (ADS)

Li, Bo; Cao, Yan-Ping; Feng, Xi-Qiao; Yu, Shou-Wen

2011-04-01

Surface wrinkling of animal mucosas is crucial for the biological functions of some tissues, and the change in their surface patterns is a phenotypic characteristic of certain diseases. Here we develop a biomechanical model to study the relationship between morphogenesis and volumetric growth, either physiological or pathological, of mucosas. Theoretical analysis and numerical simulations are performed to unravel the critical characteristics of mucosal wrinkling in a spherical antrum. It is shown that the thicknesses and elastic moduli of mucosal and submucosal layers dictate the surface buckling morphology. The results hold clinical relevance for such diseases as inflammation and gastritis.

Behavioral Genetic Toolkits: Toward the Evolutionary Origins of Complex Phenotypes.

PubMed

Rittschof, C C; Robinson, G E

2016-01-01

The discovery of toolkit genes, which are highly conserved genes that consistently regulate the development of similar morphological phenotypes across diverse species, is one of the most well-known observations in the field of evolutionary developmental biology. Surprisingly, this phenomenon is also relevant for a wide array of behavioral phenotypes, despite the fact that these phenotypes are highly complex and regulated by many genes operating in diverse tissues. In this chapter, we review the use of the toolkit concept in the context of behavior, noting the challenges of comparing behaviors and genes across diverse species, but emphasizing the successes in identifying genetic toolkits for behavior; these successes are largely attributable to the creative research approaches fueled by advances in behavioral genomics. We have two general goals: (1) to acknowledge the groundbreaking progress in this field, which offers new approaches to the difficult but exciting challenge of understanding the evolutionary genetic basis of behaviors, some of the most complex phenotypes known, and (2) to provide a theoretical framework that encompasses the scope of behavioral genetic toolkit studies in order to clearly articulate the research questions relevant to the toolkit concept. We emphasize areas for growth and highlight the emerging approaches that are being used to drive the field forward. Behavioral genetic toolkit research has elevated the use of integrative and comparative approaches in the study of behavior, with potentially broad implications for evolutionary biologists and behavioral ecologists alike. © 2016 Elsevier Inc. All rights reserved.

Random forests-based differential analysis of gene sets for gene expression data.

PubMed

Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

2013-04-10

In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for interpretation of data in complex biological systems. The classifications of biologically defined gene sets can reveal the underlying interactions of gene sets associated with the phenotypes, and provide an insightful complement to conventional gene set analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices.

PubMed

Torous, J; Onnela, J-P; Keshavan, M

2017-03-07

Mobile and connected devices like smartphones and wearable sensors can facilitate the collection of novel naturalistic and longitudinal data relevant to psychiatry at both the personal and population level. The National Institute of Mental Health's Research Domain Criteria framework offers a useful roadmap to organize, guide and lead new digital phenotyping data towards research discoveries and clinical advances.

Helicase-inactivating mutations as a basis for dominant negative phenotypes

PubMed Central

Wu, Yuliang

2010-01-01

There is ample evidence from studies of both unicellular and multicellular organisms that helicase-inactivating mutations lead to cellular dysfunction and disease phenotypes. In this review, we will discuss the mechanisms underlying the basis for abnormal phenotypes linked to mutations in genes encoding DNA helicases. Recent evidence demonstrates that a clinically relevant patient missense mutation in Fanconi Anemia Complementation Group J exerts detrimental effects on the biochemical activities of the FANC J helicase, and these molecular defects are responsible for aberrant genomic stability and a poor DNA damage response. The ability of FANC J to use the energy from AT P hydrolysis to produce the force required to unwind duplex or G-quadruplex DNA structures or destabilize protein bound to DNA is required for its DNA repair functions in vivo. Strikingly, helicase-inactivating mutations can exert a spectrum of dominant negative phenotypes, indicating that expression of the mutant helicase protein potentially interferes with normal DNA metabolism and has an effect on basic cellular processes such as DNA replication, the DNA damage response and protein trafficking. This review emphasizes that future studies of clinically relevant mutations in helicase genes will be important to understand the molecular pathologies of the associated diseases and their impact on heterozygote carriers. PMID:20980836

Mutational robustness accelerates the origin of novel RNA phenotypes through phenotypic plasticity.

PubMed

Wagner, Andreas

2014-02-18

Novel phenotypes can originate either through mutations in existing genotypes or through phenotypic plasticity, the ability of one genotype to form multiple phenotypes. From molecules to organisms, plasticity is a ubiquitous feature of life, and a potential source of exaptations, adaptive traits that originated for nonadaptive reasons. Another ubiquitous feature is robustness to mutations, although it is unknown whether such robustness helps or hinders the origin of new phenotypes through plasticity. RNA is ideal to address this question, because it shows extensive plasticity in its secondary structure phenotypes, a consequence of their continual folding and unfolding, and these phenotypes have important biological functions. Moreover, RNA is to some extent robust to mutations. This robustness structures RNA genotype space into myriad connected networks of genotypes with the same phenotype, and it influences the dynamics of evolving populations on a genotype network. In this study I show that both effects help accelerate the exploration of novel phenotypes through plasticity. My observations are based on many RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules. They are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolution of biological RNA. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Histologic prognosticators in feline osteosarcoma: a comparison with phenotypically similar canine osteosarcoma.

PubMed

Dimopoulou, Maria; Kirpensteijn, Jolle; Moens, Hester; Kik, Marja

2008-07-01

To investigate the histologic characteristics of feline osteosarcoma (OS) and compare the histologic data with phenotypically comparable canine OS. The effects of histologic and clinical variables on survival statistics were evaluated. Retrospective study. Cats (n=62) and dogs (22). Medical records of 62 cats with OS were reviewed for clinically relevant data. Clinical outcome was obtained by telephone interview. Histologic characteristics of OS were classified using a standardized grading system. Histologic characteristics in 22 feline skeletal OS were compared with 22 canine skeletal OS of identical location and subtype. Prognostic variables for clinical outcome were determined using multivariate analysis. Feline OS was characterized by moderate to abundant cellular pleomorphism, low mitotic index, small to moderate amounts of matrix, high cellularity, and a moderate amount of necrosis. There was no significant difference between histologic variables in feline and canine OS. Histologic grade, surgery, and mitotic index significantly influenced clinical outcome as determined by multivariate analysis. Tumor invasion into vessels was not identified as a significant prognosticator. Feline and canine skeletal OS have similar histologic but different prognostic characteristics. Prognosis for cats with OS is related to histologic grade and mitotic index of the tumor.

Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease

PubMed Central

Jostins, Luke; Ripke, Stephan; Weersma, Rinse K; Duerr, Richard H; McGovern, Dermot P; Hui, Ken Y; Lee, James C; Schumm, L Philip; Sharma, Yashoda; Anderson, Carl A; Essers, Jonah; Mitrovic, Mitja; Ning, Kaida; Cleynen, Isabelle; Theatre, Emilie; Spain, Sarah L; Raychaudhuri, Soumya; Goyette, Philippe; Wei, Zhi; Abraham, Clara; Achkar, Jean-Paul; Ahmad, Tariq; Amininejad, Leila; Ananthakrishnan, Ashwin N; Andersen, Vibeke; Andrews, Jane M; Baidoo, Leonard; Balschun, Tobias; Bampton, Peter A; Bitton, Alain; Boucher, Gabrielle; Brand, Stephan; Büning, Carsten; Cohain, Ariella; Cichon, Sven; D’Amato, Mauro; De Jong, Dirk; Devaney, Kathy L; Dubinsky, Marla; Edwards, Cathryn; Ellinghaus, David; Ferguson, Lynnette R; Franchimont, Denis; Fransen, Karin; Gearry, Richard; Georges, Michel; Gieger, Christian; Glas, Jürgen; Haritunians, Talin; Hart, Ailsa; Hawkey, Chris; Hedl, Matija; Hu, Xinli; Karlsen, Tom H; Kupcinskas, Limas; Kugathasan, Subra; Latiano, Anna; Laukens, Debby; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mahy, Gillian; Mansfield, John; Morgan, Angharad R; Mowat, Craig; Newman, William; Palmieri, Orazio; Ponsioen, Cyriel Y; Potocnik, Uros; Prescott, Natalie J; Regueiro, Miguel; Rotter, Jerome I; Russell, Richard K; Sanderson, Jeremy D; Sans, Miquel; Satsangi, Jack; Schreiber, Stefan; Simms, Lisa A; Sventoraityte, Jurgita; Targan, Stephan R; Taylor, Kent D; Tremelling, Mark; Verspaget, Hein W; De Vos, Martine; Wijmenga, Cisca; Wilson, David C; Winkelmann, Juliane; Xavier, Ramnik J; Zeissig, Sebastian; Zhang, Bin; Zhang, Clarence K; Zhao, Hongyu; Silverberg, Mark S; Annese, Vito; Hakonarson, Hakon; Brant, Steven R; Radford-Smith, Graham; Mathew, Christopher G; Rioux, John D; Schadt, Eric E; Daly, Mark J; Franke, Andre; Parkes, Miles; Vermeire, Severine; Barrett, Jeffrey C; Cho, Judy H

2012-01-01

Crohn’s disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry with rising prevalence in other populations1. Genome-wide association studies (GWAS) and subsequent meta-analyses of CD and UC2,3 as separate phenotypes implicated previously unsuspected mechanisms, such as autophagy4, in pathogenesis and showed that some IBD loci are shared with other inflammatory diseases5. Here we expand knowledge of relevant pathways by undertaking a meta-analysis of CD and UC genome-wide association scans, with validation of significant findings in more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional and balancing selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe striking overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD. PMID:23128233

Genome-wide association studies to identify rice salt-tolerance markers.

PubMed

Patishtan, Juan; Hartley, Tom N; Fonseca de Carvalho, Raquel; Maathuis, Frans J M

2018-05-01

Salinity is an ever increasing menace that affects agriculture worldwide. Crops such as rice are salt sensitive, but its degree of susceptibility varies widely between cultivars pointing to extensive genetic diversity that can be exploited to identify genes and proteins that are relevant in the response of rice to salt stress. We used a diversity panel of 306 rice accessions and collected phenotypic data after short (6 h), medium (7 d) and long (30 d) salinity treatment (50 mm NaCl). A genome-wide association study (GWAS) was subsequently performed, which identified around 1200 candidate genes from many functional categories, but this was treatment period dependent. Further analysis showed the presence of cation transporters and transcription factors with a known role in salinity tolerance and those that hitherto were not known to be involved in salt stress. Localization analysis of single nucleotide polymorphisms (SNPs) showed the presence of several hundred non-synonymous SNPs (nsSNPs) in coding regions and earmarked specific genomic regions with increased numbers of nsSNPs. It points to components of the ubiquitination pathway as important sources of genetic diversity that could underpin phenotypic variation in stress tolerance. © 2017 John Wiley & Sons Ltd.

Novel Compound Heterozygous Mutations Expand the Recognized Phenotypes of FARS2-Linked Disease.

PubMed

Walker, Melissa A; Mohler, Kyle P; Hopkins, Kyle W; Oakley, Derek H; Sweetser, David A; Ibba, Michael; Frosch, Matthew P; Thibert, Ronald L

2016-08-01

Mutations in mitochondrial aminoacyl-tRNA synthetases are an increasingly recognized cause of human diseases, often arising in individuals with compound heterozygous mutations and presenting with system-specific phenotypes, frequently neurologic. FARS2 encodes mitochondrial phenylalanyl transfer ribonucleic acid (RNA) synthetase (mtPheRS), perturbations of which have been reported in 6 cases of an infantile, lethal disease with refractory epilepsy and progressive myoclonus. Here the authors report the case of juvenile onset refractory epilepsy and progressive myoclonus with compound heterozygous FARS2 mutations. The authors describe the clinical course over 6 years of care at their institution and diagnostic studies including electroencephalogram (EEG), brain magnetic resonance imaging (MRI), serum and cerebrospinal fluid analyses, skeletal muscle biopsy histology, and autopsy gross and histologic findings, which include features shared with Alpers-Huttenlocher syndrome, Leigh syndrome, and a previously published case of FARS2 mutation associated infantile onset disease. The authors also present structure-guided analysis of the relevant mutations based on published mitochondrial phenylalanyl transfer RNA synthetase and related protein crystal structures as well as biochemical analysis of the corresponding recombinant mutant proteins. © The Author(s) 2016.

Inference of Genotype–Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses

PubMed Central

Steinbrück, Lars; McHardy, Alice Carolyn

2012-01-01

Distinguishing mutations that determine an organism's phenotype from (near-) neutral ‘hitchhikers’ is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring ‘antigenic trees’ for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of ‘phenotype trees’ and genotype–phenotype relationships from other types of pairwise phenotype distances. PMID:22532796

Polymorphisms in TAS2R38 and the taste bud trophic factor, gustin gene co-operate in modulating PROP taste phenotype.

PubMed

Calò, Carla; Padiglia, Alessandra; Zonza, Andrea; Corrias, Laura; Contu, Paolo; Tepper, Beverly J; Barbarossa, Iole Tomassini

2011-10-24

The PROP taste phenotype varies greatly among individuals, influencing eating behavior and therefore may play a role in body composition. This variation is associated with polymorphisms in the bitter receptor gene TAS2R38 and the taste-bud trophic factor gustin gene. The aim of this study was to examine the relationship between TAS2R38 haplotypes and the gustin gene polymorphism rs2274333 in modulating PROP taste phenotype. PROP phenotype was determined in seventy-six volunteers (29 males, 47 females, age 25±3 y) by scaling methods and threshold measurements. TAS2R38 and gustin gene genotyping was performed using PCR techniques. The lowest responsiveness in PROP nontasters is strongly associated with the AVI nontasting TAS2R38 variant and the highest responsiveness in supertasters is strongly associated to allele A and genotype AA of the gustin gene. These data support the hypothesis that the greater sensitivity of supertasters could be mediated by a greater taste-bud density. Polymorphisms in TAS2R38 and gustin gene, together, accounted for up to 60% of the phenotypic variance in PROP bitterness and to 40% in threshold values. These data, suggest that other unidentified factors may be more relevant for detecting low concentrations of PROP. Moreover, the presence of the PAV variant receptor may be important for detecting high concentrations of PROP, whereas the presence of allele A in gustin polymorphism may be relevant for perceiving low concentrations. These data show how the combination of the TAS2R38 and gustin gene genotypes modulate PROP phenotype, providing an additional tool for the evaluation of human eating behavior and nutritional status. Copyright © 2011 Elsevier Inc. All rights reserved.

Interoperability between phenotype and anatomy ontologies.

PubMed

Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

2010-12-15

Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

Neopolyploidy and diversification in Heuchera grossulariifolia

PubMed Central

Oswald, Benjamin P.; Nuismer, Scott L.

2013-01-01

Newly formed polyploid lineages must contend with several obstacles to avoid extinction, including minority cytotype exclusion, competition, and inbreeding depression. If polyploidization results in immediate divergence of phenotypic characters these hurdles may be reduced and establishment made more likely. In addition, if polyploidization alters the phenotypic and genotypic associations between traits, i.e. the P and G matrices, polyploids may be able to explore novel evolutionary paths, facilitating their divergence and successful establishment. Here we report results from a study of the perennial plant Heuchera grossulariifolia in which the phenotypic divergence and changes in phenotypic and genotypic covariance matrices caused by neopolyploidization have been estimated. Our results reveal that polyploidization causes immediate divergence for traits relevant to establishment and results in significant changes in the structure of the phenotypic covariance matrix. In contrast, our results do not provide evidence that polyploidization results in immediate and substantial shifts in the genetic covariance matrix. PMID:21143472

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species

PubMed Central

Mungall, Christopher J.; McMurry, Julie A.; Köhler, Sebastian; Balhoff, James P.; Borromeo, Charles; Brush, Matthew; Carbon, Seth; Conlin, Tom; Dunn, Nathan; Engelstad, Mark; Foster, Erin; Gourdine, J.P.; Jacobsen, Julius O.B.; Keith, Dan; Laraway, Bryan; Lewis, Suzanna E.; NguyenXuan, Jeremy; Shefchek, Kent; Vasilevsky, Nicole; Yuan, Zhou; Washington, Nicole; Hochheiser, Harry; Groza, Tudor; Smedley, Damian; Robinson, Peter N.; Haendel, Melissa A.

2017-01-01

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype–phenotype associations. Non-human organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research data can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype–phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species. PMID:27899636

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species

DOE PAGES

Mungall, Christopher J.; McMurry, Julie A.; Köhler, Sebastian; ...

2016-11-29

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype-phenotype associations. Nonhuman organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research datamore » can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype-phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species.« less

Genetic and phenotypic features defining industrial relevant Lactococcus lactis, L. cremoris and L. lactis biovar. diacetylactis strains.

PubMed

Manno, Mariano Torres; Zuljan, Federico; Alarcón, Sergio; Esteban, Luis; Blancato, Victor; Espariz, Martín; Magni, Christian

2018-06-23

Lactococcus lactis strains constitute one of the most important starter cultures for cheese production. In this study, a genome-wide analysis was performed including 68 available genomes of L. lactis group strains showing the existence of two species (L. lactis and L. cremoris) and two biovars (L. lactis biovar. diacetylactis and L. cremoris biovar. lactis). The proposed classification scheme revealed coherency among phenotypic (through in silico and in vivo bacterial function profiling), phylogenomic (through maximum likelihood trees) and genomic (using overall genome sequence-based parameters) approaches. Strain biodiversity for the industrial biovar. diacetylactis was also analyzed, finding they are formed by at least three variants with the CC1 clonal complex as the only one distributed worldwide. These findings and methodologies will help improve the selection of L. lactis group strains for industrial use as well as facilitate the interpretation of previous or future research studies on this diverse group of bacteria. Copyright © 2018. Published by Elsevier B.V.

Budding off: bringing functional genomics to Candida albicans.

PubMed

Anderson, Matthew Z; Bennett, Richard J

2016-03-01

Candida species are the most prevalent human fungal pathogens, with Candida albicans being the most clinically relevant species. Candida albicans resides as a commensal of the human gastrointestinal tract but is a frequent cause of opportunistic mucosal and systemic infections. Investigation of C. albicans virulence has traditionally relied on candidate gene approaches, but recent advances in functional genomics have now facilitated global, unbiased studies of gene function. Such studies include comparative genomics (both between and within Candida species), analysis of total RNA expression, and regulation and delineation of protein-DNA interactions. Additionally, large collections of mutant strains have begun to aid systematic screening of clinically relevant phenotypes. Here, we will highlight the development of functional genomics in C. albicans and discuss the use of these approaches to addressing both commensalism and pathogenesis in this species. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Geographic atrophy phenotype identification by cluster analysis.

PubMed

Monés, Jordi; Biarnés, Marc

2018-03-01

To identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis. This was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared. Data were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm 2 /year, respectively, p=0.0005). Cluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Novel subgroups of attention-deficit/hyperactivity disorder identified by topological data analysis and their functional network modular organizations

PubMed Central

Kyeong, Sunghyon; Kim, Jae-Jin; Kim, Eunjoo

2017-01-01

Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous condition and identification of clinically meaningful subgroups would open up a new window for personalized medicine. Thus, we aimed to identify new clinical phenotypes in children and adolescents with ADHD and to investigate whether neuroimaging findings validate the identified phenotypes. Neuroimaging and clinical data from 67 children with ADHD and 62 typically developing controls (TDCs) from the ADHD-200 database were selected. Clinical measures of ADHD symptoms and intelligence quotient (IQ) were used as input features into a topological data analysis (TDA) to identify ADHD subgroups within our sample. As external validators, graph theoretical measures obtained from the functional connectome were compared to address the biological meaningfulness of the identified subtypes. The TDA identified two unique subgroups of ADHD, labelled as mild symptom ADHD (mADHD) and severe symptom ADHD (sADHD). The output topology shape was repeatedly observed in the independent validation dataset. The graph theoretical analysis showed a decrease in the degree centrality and PageRank in the bilateral posterior cingulate cortex in the sADHD group compared with the TDC group. The mADHD group showed similar patterns of intra- and inter-module connectivity to the sADHD group. Relative to the TDC group, the inter-module connectivity between the default mode network and executive control network were significantly increased in the sADHD group but not in the mADHD group. Taken together, our results show that the data-driven TDA is potentially useful in identifying objective and biologically relevant disease phenotypes in children and adolescents with ADHD. PMID:28829775

Insights into Mutation Effect in Three Poikiloderma with Neutropenia Patients by Transcript Analysis and Disease Evolution of Reported Patients with the Same Pathogenic Variants.

PubMed

Colombo, Elisa A; Elcioglu, Nursel H; Graziano, Claudio; Farinelli, Pamela; Di Fede, Elisabetta; Neri, Iria; Facchini, Elena; Greco, Mariangela; Gervasini, Cristina; Larizza, Lidia

2018-05-16

Poikiloderma with neutropenia (PN) is a genodermatosis currently described in 77 patients, all presenting with early-onset poikiloderma, neutropenia, and several additional signs. Biallelic loss-of-function mutations in USB1 gene are detected in all molecularly tested patients but genotype-phenotype correlation remains elusive. Cancer predisposition is recognized among PN features and pathogenic variants found in patients who developed early in life myelodysplasia (n = 12), acute myeloid leukemia (n = 2), and squamous cell carcinoma (n = 2) should be kept into account in management and follow-up of novel patients. This will hopefully allow achieving data clustered on specific mutations relevant to oncological surveillance of the carrier patients. We describe the clinical features of three unreported PN patients and characterize their USB1 pathogenic variants by transcript analysis to get insights into the effect on the overall phenotype and disease evolution. A Turkish boy is homozygous for the c.531delA deletion, a recurrent mutation in Turkey; an adult Italian male is compound heterozygous for two nonsense mutations, c.243G>A and c.541C>T, while an Italian boy is homozygous for the splicing c.683_693+1del variant. The identified mutations have already been reported in PN patients who developed hematologic or skin cancer. Aberrant mRNAs of all four mutated alleles could be identified confirming that transcripts of USB1 main isoform either carrying stop codons or mis-spliced may at least partially escape nonsense-mediated decay. Our study addresses the need of gathering insights on genotype-phenotype correlations in newly described PN patients, by transcript analysis and information on disease evolution of reported patients with the same pathogenic variants.

Variants in TTC25 affect autistic trait in patients with autism spectrum disorder and general population.

PubMed

Vojinovic, Dina; Brison, Nathalie; Ahmad, Shahzad; Noens, Ilse; Pappa, Irene; Karssen, Lennart C; Tiemeier, Henning; van Duijn, Cornelia M; Peeters, Hilde; Amin, Najaf

2017-08-01

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder with a complex genetic architecture. To identify genetic variants underlying ASD, we performed single-variant and gene-based genome-wide association studies using a dense genotyping array containing over 2.3 million single-nucleotide variants in a discovery sample of 160 families with at least one child affected with non-syndromic ASD using a binary (ASD yes/no) phenotype and a quantitative autistic trait. Replication of the top findings was performed in Psychiatric Genomics Consortium and Erasmus Rucphen Family (ERF) cohort study. Significant association of quantitative autistic trait was observed with the TTC25 gene at 17q21.2 (effect size=10.2, P-value=3.4 × 10 -7 ) in the gene-based analysis. The gene also showed nominally significant association in the cohort-based ERF study (effect=1.75, P-value=0.05). Meta-analysis of discovery and replication improved the association signal (P-value meta =1.5 × 10 -8 ). No genome-wide significant signal was observed in the single-variant analysis of either the binary ASD phenotype or the quantitative autistic trait. Our study has identified a novel gene TTC25 to be associated with quantitative autistic trait in patients with ASD. The replication of association in a cohort-based study and the effect estimate suggest that variants in TTC25 may also be relevant for broader ASD phenotype in the general population. TTC25 is overexpressed in frontal cortex and testis and is known to be involved in cilium movement and thus an interesting candidate gene for autistic trait.

Hierarchical compression of Caenorhabditis elegans locomotion reveals phenotypic differences in the organization of behaviour.

PubMed

Gomez-Marin, Alex; Stephens, Greg J; Brown, André E X

2016-08-01

Regularities in animal behaviour offer insights into the underlying organizational and functional principles of nervous systems and automated tracking provides the opportunity to extract features of behaviour directly from large-scale video data. Yet how to effectively analyse such behavioural data remains an open question. Here, we explore whether a minimum description length principle can be exploited to identify meaningful behaviours and phenotypes. We apply a dictionary compression algorithm to behavioural sequences from the nematode worm Caenorhabditis elegans freely crawling on an agar plate both with and without food and during chemotaxis. We find that the motifs identified by the compression algorithm are rare but relevant for comparisons between worms in different environments, suggesting that hierarchical compression can be a useful step in behaviour analysis. We also use compressibility as a new quantitative phenotype and find that the behaviour of wild-isolated strains of C. elegans is more compressible than that of the laboratory strain N2 as well as the majority of mutant strains examined. Importantly, in distinction to more conventional phenotypes such as overall motor activity or aggregation behaviour, the increased compressibility of wild isolates is not explained by the loss of function of the gene npr-1, which suggests that erratic locomotion is a laboratory-derived trait with a novel genetic basis. Because hierarchical compression can be applied to any sequence, we anticipate that compressibility can offer insights into the organization of behaviour in other animals including humans. © 2016 The Authors.

Sports genetics moving forward: lessons learned from medical research.

PubMed

Mattsson, C Mikael; Wheeler, Matthew T; Waggott, Daryl; Caleshu, Colleen; Ashley, Euan A

2016-03-01

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy. Copyright © 2016 the American Physiological Society.

Mediation of seed provisioning in the transmission of environmental maternal effects in Maritime pine (Pinus pinaster Aiton).

PubMed

Zas, R; Cendán, C; Sampedro, L

2013-09-01

Although maternal environmental effects are increasingly recognized as an important source of phenotypic variation with relevant impacts in evolutionary processes, their relevance in long-lived plants such as pine trees is largely unknown. Here, we used a powerful sample size and a strong quantitative genetic approach to analyse the sources of variation of early seedling performance and to identify seed mass (SM)-dependent and -independent maternal environmental effects in Maritime pine. We measured SM of 8924 individual seeds collected from 10 genotypes clonally replicated in two environments of contrasting quality (favourable and stressful), and we measured seedling growth rate and biomass allocation to roots and shoots. SM was extremely variable (up to 14-fold) and strongly determined by the maternal environment and the genotype of the mother tree. The favourable maternal environment led to larger cones, larger seeds and reduced SM variability. The maternal environment also determined the offspring phenotype, with seedlings coming from the favourable environment being 35% larger and with greater root/shoot ratio. Transgenerational plasticity appears, thus, to be a relevant source of phenotypic variation in the early performance of this pine species. Seed provisioning explained most of the effect of the maternal environment on seedling total biomass. Environmental maternal effects on seedling biomass allocation were, however, determined through SM-independent mechanisms, suggesting that other epigenetic regulation channels may be involved.

Mediation of seed provisioning in the transmission of environmental maternal effects in Maritime pine (Pinus pinaster Aiton)

PubMed Central

Zas, R; Cendán, C; Sampedro, L

2013-01-01

Although maternal environmental effects are increasingly recognized as an important source of phenotypic variation with relevant impacts in evolutionary processes, their relevance in long-lived plants such as pine trees is largely unknown. Here, we used a powerful sample size and a strong quantitative genetic approach to analyse the sources of variation of early seedling performance and to identify seed mass (SM)-dependent and -independent maternal environmental effects in Maritime pine. We measured SM of 8924 individual seeds collected from 10 genotypes clonally replicated in two environments of contrasting quality (favourable and stressful), and we measured seedling growth rate and biomass allocation to roots and shoots. SM was extremely variable (up to 14-fold) and strongly determined by the maternal environment and the genotype of the mother tree. The favourable maternal environment led to larger cones, larger seeds and reduced SM variability. The maternal environment also determined the offspring phenotype, with seedlings coming from the favourable environment being 35% larger and with greater root/shoot ratio. Transgenerational plasticity appears, thus, to be a relevant source of phenotypic variation in the early performance of this pine species. Seed provisioning explained most of the effect of the maternal environment on seedling total biomass. Environmental maternal effects on seedling biomass allocation were, however, determined through SM-independent mechanisms, suggesting that other epigenetic regulation channels may be involved. PMID:23652562

HIV-1 co-receptor usage: influence on mother-to-child transmission and pediatric infection.

PubMed

Cavarelli, Mariangela; Scarlatti, Gabriella

2011-01-27

Viral CCR5 usage is not a predictive marker of mother to child transmission (MTCT) of HIV-1. CXCR4-using viral variants are little represented in pregnant women, have an increased although not significant risk of transmission and can be eventually also detected in the neonates. Genetic polymorphisms are more frequently of relevance in the child than in the mother. However, specific tissues as the placenta or the intestine, which are involved in the prevalent routes of infection in MTCT, may play an important role of selective barriers. The virus phenotype of the infected children, like that of adults, can evolve from R5 to CXCR4-using phenotype or remain R5 despite clinical progression to overt immune deficiency. The refined classification of R5 viruses into R5(narrow) and R5(broad) resolves the enigma of the R5 phenotype being associated with the state of immune deficiency. Studies are needed to address more in specific the relevance of these factors in HIV-1 MTCT and pediatric infection of non-B subtypes.

HIV-1 co-receptor usage:influence on mother-to-child transmission and pediatric infection

PubMed Central

2011-01-01

Viral CCR5 usage is not a predictive marker of mother to child transmission (MTCT) of HIV-1. CXCR4-using viral variants are little represented in pregnant women, have an increased although not significant risk of transmission and can be eventually also detected in the neonates. Genetic polymorphisms are more frequently of relevance in the child than in the mother. However, specific tissues as the placenta or the intestine, which are involved in the prevalent routes of infection in MTCT, may play an important role of selective barriers. The virus phenotype of the infected children, like that of adults, can evolve from R5 to CXCR4-using phenotype or remain R5 despite clinical progression to overt immune deficiency. The refined classification of R5 viruses into R5narrow and R5broad resolves the enigma of the R5 phenotype being associated with the state of immune deficiency. Studies are needed to address more in specific the relevance of these factors in HIV-1 MTCT and pediatric infection of non-B subtypes. PMID:21284900

Clinical and mutation-type analysis from an international series of 198 probands with a pathogenic FBN1 exons 24–32 mutation

PubMed Central

Faivre, L; Collod-Beroud, G; Callewaert, B; Child, A; Binquet, C; Gautier, E; Loeys, B L; Arbustini, E; Mayer, K; Arslan-Kirchner, M; Stheneur, C; Kiotsekoglou, A; Comeglio, P; Marziliano, N; Wolf, J E; Bouchot, O; Khau-Van-Kien, P; Beroud, C; Claustres, M; Bonithon-Kopp, C; Robinson, P N; Adès, L; De Backer, J; Coucke, P; Francke, U; De Paepe, A; Jondeau, G; Boileau, C

2009-01-01

Mutations in the FBN1 gene cause Marfan syndrome (MFS) and a wide range of overlapping phenotypes. The severe end of the spectrum is represented by neonatal MFS, the vast majority of probands carrying a mutation within exons 24–32. We previously showed that a mutation in exons 24–32 is predictive of a severe cardiovascular phenotype even in non-neonatal cases, and that mutations leading to premature truncation codons are under-represented in this region. To describe patients carrying a mutation in this so-called ‘neonatal' region, we studied the clinical and molecular characteristics of 198 probands with a mutation in exons 24–32 from a series of 1013 probands with a FBN1 mutation (20%). When comparing patients with mutations leading to a premature termination codon (PTC) within exons 24–32 to patients with an in-frame mutation within the same region, a significantly higher probability of developing ectopia lentis and mitral insufficiency were found in the second group. Patients with a PTC within exons 24–32 rarely displayed a neonatal or severe MFS presentation. We also found a higher probability of neonatal presentations associated with exon 25 mutations, as well as a higher probability of cardiovascular manifestations. A high phenotypic heterogeneity could be described for recurrent mutations, ranging from neonatal to classical MFS phenotype. In conclusion, even if the exons 24–32 location appears as a major cause of the severity of the phenotype in patients with a mutation in this region, other factors such as the type of mutation or modifier genes might also be relevant. PMID:19002209

Molecular epidemiology, genotype-phenotype correlation and BH4 responsiveness in Spanish patients with phenylketonuria.

PubMed

Aldámiz-Echevarría, Luis; Llarena, Marta; Bueno, María A; Dalmau, Jaime; Vitoria, Isidro; Fernández-Marmiesse, Ana; Andrade, Fernando; Blasco, Javier; Alcalde, Carlos; Gil, David; García, María C; González-Lamuño, Domingo; Ruiz, Mónica; Ruiz, María A; Peña-Quintana, Luis; González, David; Sánchez-Valverde, Felix; Desviat, Lourdes R; Pérez, Belen; Couce, María L

2016-08-01

Phenylketonuria (PKU), the most common inborn error of amino acid metabolism, is caused by mutations in the phenylalanine-4-hydroxylase (PAH) gene. This study aimed to assess the genotype-phenotype correlation in the PKU Spanish population and the usefulness in establishing genotype-based predictions of BH4 responsiveness in our population. It involved the molecular characterization of 411 Spanish PKU patients: mild hyperphenylalaninemia non-treated (mild HPA-NT) (34%), mild HPA (8.8%), mild-moderate (20.7%) and classic (36.5%) PKU. BH4 responsiveness was evaluated using a 6R-BH4 loading test. We assessed genotype-phenotype associations and genotype-BH4 responsiveness in our population according to literature and classification of the mutations. The mutational spectrum analysis showed 116 distinct mutations, most missense (70.7%) and located in the catalytic domain (62.9%). The most prevalent mutations were c.1066-11G>A (9.7%), p.Val388Met (6.6%) and p.Arg261Gln (6.3%). Three novel mutations (c.61-13del9, p.Ile283Val and p.Gly148Val) were reported. Although good genotype-phenotype correlation was observed, there was no exact correlation for some genotypes. Among the patients monitored for the 6R-BH4 loading test: 102 were responders (87, carried either one or two BH4-responsive alleles) and 194 non-responders (50, had two non-responsive mutations). More discrepancies were observed in non-responders. Our data reveal a great genetic heterogeneity in our population. Genotype is quite a good predictor of phenotype and BH4 responsiveness, which is relevant for patient management, treatment and follow-up.

Do Children with Specific Language Impairment have a Cognitive Profile Reminiscent of Autism? A Review of the Literature.

PubMed

Taylor, Lauren J; Maybery, Murray T; Whitehouse, Andrew J O

2012-10-01

There is debate regarding the relationship between autism and specific language impairment (SLI), with some researchers proposing aetiological overlap between the conditions and others maintaining their aetiological distinction. Although considerable research has investigated the language phenotypes of these disorders, the relationship between the cognitive phenotypes has been left relatively unexplored. This paper reviews relevant literature on whether individuals with SLI exhibit cognitive characteristics reminiscent of autism. Overall, findings are inconsistent and there is a lack of substantive evidence supporting overlapping cognitive phenotypes in autism and SLI. Better powered and more rigorous experimental designs, as well as studies directly comparing the cognitive phenotype of children with SLI and those with autism will further elucidate the aetiological relationship between these two conditions.

Wine yeast phenomics: A standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions.

PubMed

Peltier, Emilien; Bernard, Margaux; Trujillo, Marine; Prodhomme, Duyên; Barbe, Jean-Christophe; Gibon, Yves; Marullo, Philippe

2018-01-01

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following their weight loss over the time. This dispositive was coupled with robotized enzymatic assays for measuring metabolites of enological interest in natural grape juices. Despite the small volume used, kinetic parameters and fermentation end products measured are similar with those observed in larger scale vats. The vessel used also offers the possibility to assay 32 volatiles compounds using a headspace solid-phase micro-extraction coupled to gas chromatography and mass spectrometry. The vessel shaking applied strongly impacted most of the phenotypes investigated due to oxygen transfer occuring in the first hours of the alcoholic fermentation. The impact of grape must and micro-oxygenation was investigated illustrating some relevant genetic x environmental interactions. By phenotyping a wide panel of commercial wine starters in five grape juices, broad phenotypic correlations between kinetics and metabolic end products were evidentiated. Moreover, a multivariate analysis illustrates that some grape musts are more able than others to discriminate commercial strains since some are less robust to environmental changes.

PDK2 and ABCG2 genes polymorphisms are correlated with blood glucose levels and uric acid in Tibetan gout patients.

PubMed

Ren, Y C; Jin, T B; Sun, X D; Geng, T T; Zhang, M X; Wang, L; Feng, T; Kang, L L; Chen, C

2016-02-11

Previous studies have shown that the PDK2 and ABCG2 genes play important roles in many aspects of gout development in European populations. However, a detailed genotype-phenotype analysis was not performed. The aim of the present study was to investigate the potential association between variants in these two genes and metabolism-related quantitative phenotypes relevant to gout in a Chinese Tibetan population. In total, 316 Chinese Tibetan gout patients were recruited from rheumatology outpatient clinics and 6 single nucleotide polymorphisms in PDK2 and ABCG2 were genotyped, which were possible etiologic variants as identified in the HapMap Chinese Han Beijing population. A significant difference in blood glucose levels was detected between different genotypes of rs2728109 (P = 0.005) in the PDK2 gene. We also detected a significant difference in the mean serum uric levels between different genotypes of rs3114018 (P = 0.004) in the ABCG2 gene. All P values remained significant after Bonferroni's correction for multiple testing. Our data demonstrate potential roles for PDK2 and ABCG2 polymorphisms in the metabolic phenotypes of Tibetan gout patients, which may provide new insights into the etiology of gout. Further studies are required to confirm these findings.

Wine yeast phenomics: A standardized fermentation method for assessing quantitative traits of Saccharomyces cerevisiae strains in enological conditions

PubMed Central

Bernard, Margaux; Trujillo, Marine; Prodhomme, Duyên; Barbe, Jean-Christophe; Gibon, Yves; Marullo, Philippe

2018-01-01

This work describes the set up of a small scale fermentation methodology for measuring quantitative traits of hundreds of samples in an enological context. By using standardized screw cap vessels, the alcoholic fermentation kinetics of Saccharomyces cerevisiae strains were measured by following their weight loss over the time. This dispositive was coupled with robotized enzymatic assays for measuring metabolites of enological interest in natural grape juices. Despite the small volume used, kinetic parameters and fermentation end products measured are similar with those observed in larger scale vats. The vessel used also offers the possibility to assay 32 volatiles compounds using a headspace solid-phase micro-extraction coupled to gas chromatography and mass spectrometry. The vessel shaking applied strongly impacted most of the phenotypes investigated due to oxygen transfer occuring in the first hours of the alcoholic fermentation. The impact of grape must and micro-oxygenation was investigated illustrating some relevant genetic x environmental interactions. By phenotyping a wide panel of commercial wine starters in five grape juices, broad phenotypic correlations between kinetics and metabolic end products were evidentiated. Moreover, a multivariate analysis illustrates that some grape musts are more able than others to discriminate commercial strains since some are less robust to environmental changes. PMID:29351285

A Morpholino-based screen to identify novel genes involved in craniofacial morphogenesis

PubMed Central

Melvin, Vida Senkus; Feng, Weiguo; Hernandez-Lagunas, Laura; Artinger, Kristin Bruk; Williams, Trevor

2014-01-01

BACKGROUND The regulatory mechanisms underpinning facial development are conserved between diverse species. Therefore, results from model systems provide insight into the genetic causes of human craniofacial defects. Previously, we generated a comprehensive dataset examining gene expression during development and fusion of the mouse facial prominences. Here, we used this resource to identify genes that have dynamic expression patterns in the facial prominences, but for which only limited information exists concerning developmental function. RESULTS This set of ~80 genes was used for a high throughput functional analysis in the zebrafish system using Morpholino gene knockdown technology. This screen revealed three classes of cranial cartilage phenotypes depending upon whether knockdown of the gene affected the neurocranium, viscerocranium, or both. The targeted genes that produced consistent phenotypes encoded proteins linked to transcription (meis1, meis2a, tshz2, vgll4l), signaling (pkdcc, vlk, macc1, wu:fb16h09), and extracellular matrix function (smoc2). The majority of these phenotypes were not altered by reduction of p53 levels, demonstrating that both p53 dependent and independent mechanisms were involved in the craniofacial abnormalities. CONCLUSIONS This Morpholino-based screen highlights new genes involved in development of the zebrafish craniofacial skeleton with wider relevance to formation of the face in other species, particularly mouse and human. PMID:23559552

Epimutation profiling in Beckwith-Wiedemann syndrome: relationship with assisted reproductive technology

PubMed Central

2013-01-01

Background Beckwith-Wiedemann syndrome (BWS) is a congenital overgrowth disorder associated with abnormalities in 11p15.5 imprinted genes. The most common cause is loss of methylation (epimutation) at the imprinting control centre 2 (IC2/KvDMR1). Most IC2 epimutations occur sporadically but an association with conception after assisted reproductive technologies (ART) has been reported. A subgroup of IC2 epimutation cases also harbour epimutations at other imprinting centres (ICs) outside of 11p15.5. We have investigated the relationship between these multiple epimutation cases (ME+), history of ART and clinical phenotype in a cohort of 187 BWS IC2 epimutation patients. Results Methylation analysis at PLAGL1, MEST and IGF2R ICs demonstrated an over-representation of patients with abnormally low methylation (8.5%, 12% and 6% respectively). At IGF2R some patients (2%) had gain of methylation but this was also detected in controls. Though there were no significant correlations between the methylation index (MIs) at the three ICs tested, a subset of patients appeared to be susceptible to multiple epimutations (ME+) and 21.2% of ME + patients had been conceived by ART compared to 4.5% (P = 0.0033) without additional epimutations. Methylation array profiling (Illumina Goldengate®) of patients and controls (excluding 11p15.5 loci) demonstrated significant differences between patients and controls. No significant associations were found between aspects of the BWS phenotype and individual epimutations but we describe a case presenting with a post-ART BWS-like phenotype in which molecular analysis demonstrated loss of paternal allele methylation at the 11p15.5 IC1 locus (IC1 regulates imprinting of IGF2 and H19). Loss of paternal allele methylation at the IC1 is the molecular finding associated with Silver-Russell syndrome whereas BWS is associated with gain of maternal allele methylation at IC1. Further analysis demonstrated epimutations at PLAGL1 and MEST consistent with the hypothesis that the presence of multiple epimutations may be of clinical relevance. Conclusions These findings suggest that the ME + subgroup of BWS patients are preferentially, but not exclusively, associated with a history of ART and that, though at present, there are no clear epigenotype-phenotype correlations for ME + BWS patients, non-11p15.5 IC epimutations can influence clinical phenotype. PMID:24325814

Replicable in vivo physiological and behavioral phenotypes of the Shank3B null mutant mouse model of autism.

PubMed

Dhamne, Sameer C; Silverman, Jill L; Super, Chloe E; Lammers, Stephen H T; Hameed, Mustafa Q; Modi, Meera E; Copping, Nycole A; Pride, Michael C; Smith, Daniel G; Rotenberg, Alexander; Crawley, Jacqueline N; Sahin, Mustafa

2017-01-01

Autism spectrum disorder (ASD) is a clinically and biologically heterogeneous condition characterized by social, repetitive, and sensory behavioral abnormalities. No treatments are approved for the core diagnostic symptoms of ASD. To enable the earliest stages of therapeutic discovery and development for ASD, robust and reproducible behavioral phenotypes and biological markers are essential to establish in preclinical animal models. The goal of this study was to identify electroencephalographic (EEG) and behavioral phenotypes that are replicable between independent cohorts in a mouse model of ASD. The larger goal of our strategy is to empower the preclinical biomedical ASD research field by generating robust and reproducible behavioral and physiological phenotypes in animal models of ASD, for the characterization of mechanistic underpinnings of ASD-relevant phenotypes, and to ensure reliability for the discovery of novel therapeutics. Genetic disruption of the SHANK3 gene, a scaffolding protein involved in the stability of the postsynaptic density in excitatory synapses, is thought to be responsible for a relatively large number of cases of ASD. Therefore, we have thoroughly characterized the robustness of ASD-relevant behavioral phenotypes in two cohorts, and for the first time quantified translational EEG activity in Shank3B null mutant mice. In vivo physiology and behavioral assays were conducted in two independently bred and tested full cohorts of Shank3B null mutant ( Shank3B KO) and wildtype littermate control (WT) mice. EEG was recorded via wireless implanted telemeters for 7 days of baseline followed by 20 min of recording following pentylenetetrazol (PTZ) challenge. Behaviors relevant to the diagnostic and associated symptoms of ASD were tested on a battery of established behavioral tests. Assays were designed to reproduce and expand on the original behavioral characterization of Shank3B KO mice. Two or more corroborative tests were conducted within each behavioral domain, including social, repetitive, cognitive, anxiety-related, sensory, and motor categories of assays. Relative to WT mice, Shank3B KO mice displayed a dramatic resistance to PTZ seizure induction and an enhancement of gamma band oscillatory EEG activity indicative of enhanced inhibitory tone. These findings replicated in two separate cohorts. Behaviorally, Shank3B KO mice exhibited repetitive grooming, deficits in aspects of reciprocal social interactions and vocalizations, and reduced open field activity, as well as variable deficits in sensory responses, anxiety-related behaviors, learning and memory. Robust animal models and quantitative, replicable biomarkers of neural dysfunction are needed to decrease risk and enable successful drug discovery and development for ASD and other neurodevelopmental disorders. Complementary to the replicated behavioral phenotypes of the Shank3B mutant mouse is the new identification of a robust, translational in vivo neurophysiological phenotype. Our findings provide strong evidence for robustness and replicability of key translational phenotypes in Shank3B mutant mice and support the usefulness of this mouse model of ASD for therapeutic discovery.

Phenotypic heterogeneity in metabolic traits among single cells of a rare bacterial species in its natural environment quantified with a combination of flow cell sorting and NanoSIMS

PubMed Central

Zimmermann, Matthias; Escrig, Stéphane; Hübschmann, Thomas; Kirf, Mathias K.; Brand, Andreas; Inglis, R. Fredrik; Musat, Niculina; Müller, Susann; Meibom, Anders; Ackermann, Martin; Schreiber, Frank

2015-01-01

Populations of genetically identical microorganisms residing in the same environment can display marked variability in their phenotypic traits; this phenomenon is termed phenotypic heterogeneity. The relevance of such heterogeneity in natural habitats is unknown, because phenotypic characterization of a sufficient number of single cells of the same species in complex microbial communities is technically difficult. We report a procedure that allows to measure phenotypic heterogeneity in bacterial populations from natural environments, and use it to analyze N2 and CO2 fixation of single cells of the green sulfur bacterium Chlorobium phaeobacteroides from the meromictic lake Lago di Cadagno. We incubated lake water with 15N2 and 13CO2 under in situ conditions with and without NH4+. Subsequently, we used flow cell sorting with auto-fluorescence gating based on a pure culture isolate to concentrate C. phaeobacteroides from its natural abundance of 0.2% to now 26.5% of total bacteria. C. phaeobacteroides cells were identified using catalyzed-reporter deposition fluorescence in situ hybridization (CARD-FISH) targeting the 16S rRNA in the sorted population with a species-specific probe. In a last step, we used nanometer-scale secondary ion mass spectrometry to measure the incorporation 15N and 13C stable isotopes in more than 252 cells. We found that C. phaeobacteroides fixes N2 in the absence of NH4+, but not in the presence of NH4+ as has previously been suggested. N2 and CO2 fixation were heterogeneous among cells and positively correlated indicating that N2 and CO2 fixation activity interact and positively facilitate each other in individual cells. However, because CARD-FISH identification cannot detect genetic variability among cells of the same species, we cannot exclude genetic variability as a source for phenotypic heterogeneity in this natural population. Our study demonstrates the technical feasibility of measuring phenotypic heterogeneity in a rare bacterial species in its natural habitat, thus opening the door to study the occurrence and relevance of phenotypic heterogeneity in nature. PMID:25932020

Translation: screening for novel therapeutics with disease-relevant cell types derived from human stem cell models.

PubMed

Haggarty, Stephen J; Perlis, Roy H

2014-06-15

The advent of somatic cell reprogramming technologies-which enables the generation of patient-specific, induced pluripotent stem cell and other trans-differentiated human neuronal cell models-provides new means of gaining insight into the molecular mechanisms and neural substrates of psychiatric disorders. By allowing a more precise understanding of genotype-phenotype relationship in disease-relevant human cell types, the use of reprogramming technologies in tandem with emerging genome engineering approaches provides a previously "missing link" between basic research and translational efforts. In this review, we summarize advances in applying human pluripotent stem cell and reprogramming technologies to generate specific neural subtypes with a focus on the use of these in vitro systems for the discovery of small molecule-probes and novel therapeutics. Examples are given where human cell models of psychiatric disorders have begun to reveal new mechanistic insight into pathophysiology and simultaneously have provided the foundation for developing disease-relevant, phenotypic assays suitable for both functional genomic and chemical screens. A number of areas for future research are discussed, including the need to develop robust methodology for the reproducible, large-scale production of disease-relevant neural cell types in formats compatible with high-throughput screening modalities, including high-content imaging, multidimensional, signature-based screening, and in vitro network with multielectrode arrays. Limitations, including the challenges in recapitulating neurocircuits and non-cell autonomous phenotypes are discussed. Although these technologies are still in active development, we conclude that, as our understanding of how to efficiently generate and probe the plasticity of patient-specific stem models improves, their utility is likely to advance rapidly. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Phenotype analysis of congenital and neurodevelopmental disorders in the next generation sequencing era.

PubMed

Carey, John C

2017-09-01

The designation, phenotype, was proposed as a term by Wilhelm Johannsen in 1909. The word is derived from the Greek, phano (showing) and typo (type), phanotypos. Phenotype has become a widely recognized term, even outside of the genetics community, in recent years with the ongoing identification of human disease genes. The term has been defined as the observable constitution of an organism, but sometimes refers to a condition when a person has a particular clinical presentation. Analysis of phenotype is a timely theme because advances in the understanding of the genetic basis of human disease and the emergence of next generation sequencing have spurred a renewed interest in phenotype and the proposal to establish a "Human Phenome Project." This article summarizes the principles of phenotype analysis that are important in medical genetics and describes approaches to comprehensive phenotype analysis in the investigation of patients with human disorders. I discuss the various elements related to disease phenotypes and highlight neurofibromatosis type 1 and the Elements of Morphology Project as illustrations of the principles. In recent years, the notion of "deep phenotyping" has emerged. Currently there are now a number of proposed strategies and resources to approach this concept. Not since the 1960s and 1970s has there been such an exciting time in the history of medicine surrounding the analysis of phenotype in genetic disorders. © 2017 Wiley Periodicals, Inc.

A 3D in vitro model to explore the inter-conversion between epithelial and mesenchymal states during EMT and its reversion.

PubMed

Bidarra, S J; Oliveira, P; Rocha, S; Saraiva, D P; Oliveira, C; Barrias, C C

2016-06-03

Epithelial-to-mesenchymal transitions (EMT) are strongly implicated in cancer dissemination. Intermediate states, arising from inter-conversion between epithelial (E) and mesenchymal (M) states, are characterized by phenotypic heterogeneity combining E and M features and increased plasticity. Hybrid EMT states are highly relevant in metastatic contexts, but have been largely neglected, partially due to the lack of physiologically-relevant 3D platforms to study them. Here we propose a new in vitro model, combining mammary E cells with a bioengineered 3D matrix, to explore phenotypic and functional properties of cells in transition between E and M states. Optimized alginate-based 3D matrices provided adequate 3D microenvironments, where normal epithelial morphogenesis was recapitulated, with formation of acini-like structures, similar to those found in native mammary tissue. TGFβ1-driven EMT in 3D could be successfully promoted, generating M-like cells. TGFβ1 removal resulted in phenotypic switching to an intermediate state (RE cells), a hybrid cell population expressing both E and M markers at gene/protein levels. RE cells exhibited increased proliferative/clonogenic activity, as compared to M cells, being able to form large colonies containing cells with front-back polarity, suggesting a more aggressive phenotype. Our 3D model provides a powerful tool to investigate the role of the microenvironment on metastable EMT stages.

Behavioral phenotypes of genetic mouse models of autism

PubMed Central

Kazdoba, T. M.; Leach, P. T.; Crawley, J. N.

2016-01-01

More than a hundred de novo single gene mutations and copy-number variants have been implicated in autism, each occurring in a small subset of cases. Mutant mouse models with syntenic mutations offer research tools to gain an understanding of the role of each gene in modulating biological and behavioral phenotypes relevant to autism. Knockout, knockin and transgenic mice incorporating risk gene mutations detected in autism spectrum disorder and comorbid neurodevelopmental disorders are now widely available. At present, autism spectrum disorder is diagnosed solely by behavioral criteria. We developed a constellation of mouse behavioral assays designed to maximize face validity to the types of social deficits and repetitive behaviors that are central to an autism diagnosis. Mouse behavioral assays for associated symptoms of autism, which include cognitive inflexibility, anxiety, hyperactivity, and unusual reactivity to sensory stimuli, are frequently included in the phenotypic analyses. Over the past 10 years, we and many other laboratories around the world have employed these and additional behavioral tests to phenotype a large number of mutant mouse models of autism. In this review, we highlight mouse models with mutations in genes that have been identified as risk genes for autism, which work through synaptic mechanisms and through the mTOR signaling pathway. Robust, replicated autism-relevant behavioral outcomes in a genetic mouse model lend credence to a causal role for specific gene contributions and downstream biological mechanisms in the etiology of autism. PMID:26403076

Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531

PubMed Central

Voigt, Andrew P.; Brodersen, Lisa Eidenschink; Alonzo, Todd A.; Gerbing, Robert B.; Menssen, Andrew J.; Wilson, Elisabeth R.; Kahwash, Samir; Raimondi, Susana C.; Hirsch, Betsy A.; Gamis, Alan S.; Meshinchi, Soheil; Wells, Denise A.; Loken, Michael R.

2017-01-01

Diagnostic biomarkers can be used to determine relapse risk in acute myeloid leukemia, and certain genetic aberrancies have prognostic relevance. A diagnostic immunophenotypic expression profile, which quantifies the amounts of distinct gene products, not just their presence or absence, was established in order to improve outcome prediction for patients with acute myeloid leukemia. The immunophenotypic expression profile, which defines each patient’s leukemia as a location in 15-dimensional space, was generated for 769 patients enrolled in the Children’s Oncology Group AAML0531 protocol. Unsupervised hierarchical clustering grouped patients with similar immunophenotypic expression profiles into eleven patient cohorts, demonstrating high associations among phenotype, genotype, morphology, and outcome. Of 95 patients with inv(16), 79% segregated in Cluster A. Of 109 patients with t(8;21), 92% segregated in Clusters A and B. Of 152 patients with 11q23 alterations, 78% segregated in Clusters D, E, F, G, or H. For both inv(16) and 11q23 abnormalities, differential phenotypic expression identified patient groups with different survival characteristics (P<0.05). Clinical outcome analysis revealed that Cluster B (predominantly t(8;21)) was associated with favorable outcome (P<0.001) and Clusters E, G, H, and K were associated with adverse outcomes (P<0.05). Multivariable regression analysis revealed that Clusters E, G, H, and K were independently associated with worse survival (P range <0.001 to 0.008). The Children’s Oncology Group AAML0531 trial: clinicaltrials.gov Identifier: 00372593. PMID:28883080

A multivariate twin study of the DSM-IV criteria for antisocial personality disorder.

PubMed

Kendler, Kenneth S; Aggen, Steven H; Patrick, Christopher J

2012-02-01

Many assessment instruments for psychopathy are multidimensional, suggesting that distinguishable factors are needed to effectively capture variation in this personality domain. However, no prior study has examined the factor structure of the DSM-IV criteria for antisocial personality disorder (ASPD). Self-report questionnaire items reflecting all A criteria for DSM-IV ASPD were available from 4291 twins (including both members of 1647 pairs) from the Virginia Adult Study of Psychiatric and Substance Use Disorders. Exploratory factor analysis and twin model fitting were performed using, respectively, Mplus and Mx. Phenotypic factor analysis produced evidence for two correlated factors: aggressive-disregard and disinhibition. The best-fitting multivariate twin model included two genetic and one unique environmental common factor, along with criteria-specific genetic and environmental effects. The two genetic factors closely resembled the phenotypic factors and varied in their prediction of a range of relevant criterion variables. Scores on the genetic aggressive-disregard factor score were more strongly associated with risk for conduct disorder, early and heavy alcohol use, and low educational status, whereas scores on the genetic disinhibition factor score were more strongly associated with younger age, novelty seeking, and major depression. From a genetic perspective, the DSM-IV criteria for ASPD do not reflect a single dimension of liability but rather are influenced by two dimensions of genetic risk reflecting aggressive-disregard and disinhibition. The phenotypic structure of the ASPD criteria results largely from genetic and not from environmental influences. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Msx homeobox gene family and craniofacial development.

PubMed

Alappat, Sylvia; Zhang, Zun Yi; Chen, Yi Ping

2003-12-01

Vertebrate Msx genes are unlinked, homeobox-containing genes that bear homology to the Drosophila muscle segment homeobox gene. These genes are expressed at multiple sites of tissue-tissue interactions during vertebrate embryonic development. Inductive interactions mediated by the Msx genes are essential for normal craniofacial, limb and ectodermal organ morphogenesis, and are also essential to survival in mice, as manifested by the phenotypic abnormalities shown in knockout mice and in humans. This review summarizes studies on the expression, regulation, and functional analysis of Msx genes that bear relevance to craniofacial development in humans and mice. Key words: Msx genes, craniofacial, tooth, cleft palate, suture, development, transcription factor, signaling molecule.

Active PI3K Pathway Causes an Invasive Phenotype Which Can Be Reversed or Promoted by Blocking the Pathway at Divergent Nodes

PubMed Central

Wallin, Jeffrey J.; Guan, Jane; Edgar, Kyle A.; Zhou, Wei; Francis, Ross; Torres, Anthony C.; Haverty, Peter M.; Eastham-Anderson, Jeffrey; Arena, Sabrina; Bardelli, Alberto; Griffin, Sue; Goodall, John E.; Grimshaw, Kyla M.; Hoeflich, Klaus P.; Torrance, Christopher; Belvin, Marcia; Friedman, Lori S.

2012-01-01

The PTEN/PI3K pathway is commonly mutated in cancer and therefore represents an attractive target for therapeutic intervention. To investigate the primary phenotypes mediated by increased pathway signaling in a clean, patient-relevant context, an activating PIK3CA mutation (H1047R) was knocked-in to an endogenous allele of the MCF10A non-tumorigenic human breast epithelial cell line. Introduction of an endogenously mutated PIK3CA allele resulted in a marked epithelial-mesenchymal transition (EMT) and invasive phenotype, compared to isogenic wild-type cells. The invasive phenotype was linked to enhanced PIP3 production via a S6K-IRS positive feedback mechanism. Moreover, potent and selective inhibitors of PI3K were highly effective in reversing this phenotype, which is optimally revealed in 3-dimensional cell culture. In contrast, inhibition of Akt or mTOR exacerbated the invasive phenotype. Our results suggest that invasion is a core phenotype mediated by increased PTEN/PI3K pathway activity and that therapeutic agents targeting different nodes of the PI3K pathway may have dramatic differences in their ability to reverse or promote cancer metastasis. PMID:22570710

Behavioral and Psychological Phenotyping of Physical Activity and Sedentary Behavior: Implications for Weight Management.

PubMed

Bryan, Angela D; Jakicic, John M; Hunter, Christine M; Evans, Mary E; Yanovski, Susan Z; Epstein, Leonard H

2017-10-01

Risk for obesity is determined by a complex mix of genetics and lifetime exposures at multiple levels, from the metabolic milieu to psychosocial and environmental influences. These phenotypic differences underlie the variability in risk for obesity and response to weight management interventions, including differences in physical activity and sedentary behavior. As part of a broader effort focused on behavioral and psychological phenotyping in obesity research, the National Institutes of Health convened a multidisciplinary workshop to explore the state of the science in behavioral and psychological phenotyping in humans to explain individual differences in physical activity, both as a risk factor for obesity development and in response to activity-enhancing interventions. Understanding the behavioral and psychological phenotypes that contribute to differences in physical activity and sedentary behavior could allow for improved treatment matching and inform new targets for tailored, innovative, and effective weight management interventions. This summary provides the rationale for identifying psychological and behavioral phenotypes relevant to physical activity and identifies opportunities for future research to better understand, define, measure, and validate putative phenotypic factors and characterize emerging phenotypes that are empirically associated with initiation of physical activity, response to intervention, and sustained changes in physical activity. © 2017 The Obesity Society.

Genomic Characterization of Variable Surface Antigens Reveals a Telomere Position Effect as a Prerequisite for RNA Interference-Mediated Silencing in Paramecium tetraurelia

PubMed Central

Baranasic, Damir; Oppermann, Timo; Cheaib, Miriam; Cullum, John; Schmidt, Helmut

2014-01-01

ABSTRACT Antigenic or phenotypic variation is a widespread phenomenon of expression of variable surface protein coats on eukaryotic microbes. To clarify the mechanism behind mutually exclusive gene expression, we characterized the genetic properties of the surface antigen multigene family in the ciliate Paramecium tetraurelia and the epigenetic factors controlling expression and silencing. Genome analysis indicated that the multigene family consists of intrachromosomal and subtelomeric genes; both classes apparently derive from different gene duplication events: whole-genome and intrachromosomal duplication. Expression analysis provides evidence for telomere position effects, because only subtelomeric genes follow mutually exclusive transcription. Microarray analysis of cultures deficient in Rdr3, an RNA-dependent RNA polymerase, in comparison to serotype-pure wild-type cultures, shows cotranscription of a subset of subtelomeric genes, indicating that the telomere position effect is due to a selective occurrence of Rdr3-mediated silencing in subtelomeric regions. We present a model of surface antigen evolution by intrachromosomal gene duplication involving the maintenance of positive selection of structurally relevant regions. Further analysis of chromosome heterogeneity shows that alternative telomere addition regions clearly affect transcription of closely related genes. Consequently, chromosome fragmentation appears to be of crucial importance for surface antigen expression and evolution. Our data suggest that RNAi-mediated control of this genetic network by trans-acting RNAs allows rapid epigenetic adaptation by phenotypic variation in combination with long-term genetic adaptation by Darwinian evolution of antigen genes. PMID:25389173

Flow cytometry analysis of Clostridium beijerinckii NRRL B-598 populations exhibiting different phenotypes induced by changes in cultivation conditions.

PubMed

Branska, Barbora; Pechacova, Zora; Kolek, Jan; Vasylkivska, Maryna; Patakova, Petra

2018-01-01

Biobutanol production by clostridia via the acetone-butanol-ethanol (ABE) pathway is a promising future technology in bioenergetics , but identifying key regulatory mechanisms for this pathway is essential in order to construct industrially relevant strains with high tolerance and productivity. We have applied flow cytometric analysis to C. beijerinckii NRRL B-598 and carried out comparative screening of physiological changes in terms of viability under different cultivation conditions to determine its dependence on particular stages of the life cycle and the concentration of butanol. Dual staining by propidium iodide (PI) and carboxyfluorescein diacetate (CFDA) provided separation of cells into four subpopulations with different abilities to take up PI and cleave CFDA, reflecting different physiological states. The development of a staining pattern during ABE fermentation showed an apparent decline in viability, starting at the pH shift and onset of solventogenesis, although an appreciable proportion of cells continued to proliferate. This was observed for sporulating as well as non-sporulating phenotypes at low solvent concentrations, suggesting that the increase in percentage of inactive cells was not a result of solvent toxicity or a transition from vegetative to sporulating stages. Additionally, the sporulating phenotype was challenged with butanol and cultivation with a lower starting pH was performed; in both these experiments similar trends were obtained-viability declined after the pH breakpoint, independent of the actual butanol concentration in the medium. Production characteristics of both sporulating and non-sporulating phenotypes were comparable, showing that in C. beijerinckii NRRL B-598, solventogenesis was not conditional on sporulation. We have shown that the decline in C. beijerinckii NRRL B-598 culture viability during ABE fermentation was not only the result of accumulated toxic metabolites, but might also be associated with a special survival strategy triggered by pH change.

Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

PubMed

Vaas, Lea A I; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data.

Mutation analysis of pre-mRNA splicing genes in Chinese families with retinitis pigmentosa

PubMed Central

Pan, Xinyuan; Chen, Xue; Liu, Xiaoxing; Gao, Xiang; Kang, Xiaoli; Xu, Qihua; Chen, Xuejuan; Zhao, Kanxing; Zhang, Xiumei; Chu, Qiaomei; Wang, Xiuying

2014-01-01

Purpose Seven genes involved in precursor mRNA (pre-mRNA) splicing have been implicated in autosomal dominant retinitis pigmentosa (adRP). We sought to detect mutations in all seven genes in Chinese families with RP, to characterize the relevant phenotypes, and to evaluate the prevalence of mutations in splicing genes in patients with adRP. Methods Six unrelated families from our adRP cohort (42 families) and two additional families with RP with uncertain inheritance mode were clinically characterized in the present study. Targeted sequence capture with next-generation massively parallel sequencing (NGS) was performed to screen mutations in 189 genes including all seven pre-mRNA splicing genes associated with adRP. Variants detected with NGS were filtered with bioinformatics analyses, validated with Sanger sequencing, and prioritized with pathogenicity analysis. Results Mutations in pre-mRNA splicing genes were identified in three individual families including one novel frameshift mutation in PRPF31 (p.Leu366fs*1) and two known mutations in SNRNP200 (p.Arg681His and p.Ser1087Leu). The patients carrying SNRNP200 p.R681H showed rapid disease progression, and the family carrying p.S1087L presented earlier onset ages and more severe phenotypes compared to another previously reported family with p.S1087L. In five other families, we identified mutations in other RP-related genes, including RP1 p. Ser781* (novel), RP2 p.Gln65* (novel) and p.Ile137del (novel), IMPDH1 p.Asp311Asn (recurrent), and RHO p.Pro347Leu (recurrent). Conclusions Mutations in splicing genes identified in the present and our previous study account for 9.5% in our adRP cohort, indicating the important role of pre-mRNA splicing deficiency in the etiology of adRP. Mutations in the same splicing gene, or even the same mutation, could correlate with different phenotypic severities, complicating the genotype–phenotype correlation and clinical prognosis. PMID:24940031

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

PubMed Central

Vaas, Lea A. I.; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

Background The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed ‘-omics’ techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. Methodology The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. Conclusions We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data. PMID:22536335

Cognitive Phenotypes and the Evolution of Animal Decisions.

PubMed

Mendelson, Tamra C; Fitzpatrick, Courtney L; Hauber, Mark E; Pence, Charles H; Rodríguez, Rafael L; Safran, Rebecca J; Stern, Caitlin A; Stevens, Jeffrey R

2016-11-01

Despite the clear fitness consequences of animal decisions, the science of animal decision making in evolutionary biology is underdeveloped compared with decision science in human psychology. Specifically, the field lacks a conceptual framework that defines and describes the relevant components of a decision, leading to imprecise language and concepts. The 'judgment and decision-making' (JDM) framework in human psychology is a powerful tool for framing and understanding human decisions, and we apply it here to components of animal decisions, which we refer to as 'cognitive phenotypes'. We distinguish multiple cognitive phenotypes in the context of a JDM framework and highlight empirical approaches to characterize them as evolvable traits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neopolyploidy and diversification in Heuchera grossulariifolia.

PubMed

Oswald, Benjamin P; Nuismer, Scott L

2011-06-01

Newly formed polyploid lineages must contend with several obstacles to avoid extinction, including minority cytotype exclusion, competition, and inbreeding depression. If polyploidization results in immediate divergence of phenotypic characters these hurdles may be reduced and establishment made more likely. In addition, if polyploidization alters the phenotypic and genotypic associations between traits, that is, the P and G matrices, polyploids may be able to explore novel evolutionary paths, facilitating their divergence and successful establishment. Here, we report results from a study of the perennial plant Heuchera grossulariifolia in which the phenotypic divergence and changes in phenotypic and genotypic covariance matrices caused by neopolyploidization have been estimated. Our results reveal that polyploidization causes immediate divergence for traits relevant to establishment and results in significant changes in the structure of the phenotypic covariance matrix. In contrast, our results do not provide evidence that polyploidization results in immediate and substantial shifts in the genetic covariance matrix. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

In Vitro Assays for Mouse Müller Cell Phenotyping Through microRNA Profiling in the Damaged Retina.

PubMed

Reyes-Aguirre, Luis I; Quintero, Heberto; Estrada-Leyva, Brenda; Lamas, Mónica

2018-01-01

microRNA profiling has identified cell-specific expression patterns that could represent molecular signatures triggering the acquisition of a specific phenotype; in other words, of cellular identity and its associated function. Several groups have hypothesized that retinal cell phenotyping could be achieved through the determination of the global pattern of miRNA expression across specific cell types in the adult retina. This is especially relevant for Müller glia in the context of retinal damage, as these cells undergo dramatic changes of gene expression in response to injury, that render them susceptible to acquire a progenitor-like phenotype and be a source of new neurons.We describe a method that combines an experimental protocol for excitotoxic-induced retinal damage through N-methyl-D-aspartate subretinal injection with magnetic-activated cell sorting (MACS) of Müller cells and RNA isolation for microRNA profiling. Comparison of microRNA patterns of expression should allow Müller cell phenotyping under different experimental conditions.

Ponticulus posticus is a frequent radiographic finding on lateral cephalograms in nevoid basal cell carcinoma syndrome (Gorlin-Goltz syndrome).

PubMed

Friedrich, Reinhard E

2014-12-01

Nevoid basal cell carcinoma syndrome (NBCCS) is a predisposition to a rare tumor type with a variable phenotype. Besides tumors, skeletal alterations, such as bifid ribs or frontal bossing constitute the phenotype. Recently, a variant of the first cervical vertebra, the ponticulus posticus, was reported to occur in 50% of patients with NBCCS as revealed by analysis of lateral cephalograms. Lateral cephalograms of eight patients with NBCCS were studied for the presence of ponticulus posticus. The ponticulus posticus was present in all patients. In one case, a series of cephalograms performed during a period of 20 years allowed the slow and continuous recording of a ponticulus posticus formation. Besides the predisposition to developing neoplasms, NBCCS also affects bone development. Some diagnostic criteria for NBCCS rely on certain osseous transformations either in hard tissues, e.g. keratocystic odontogenic tumor in jaws, or in soft tissues, e.g. calcification of the falx cerebri. Furthermore, the physiognomy can be affected by skeletal alterations, e.g. frontal bossing or hypertelorism. Given this wide spectrum of osseous involvement in NBCCS, the high prevalence rate of ponticulus posticus should be added to the relevant diagnostic findings of the skull and vertebral column. However, the onset of ponticulus posticus formation in the life of such patients is unclear and thus the relevance of this finding in early diagnosis of NBCCS remains to be elucidated. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Impact of Insertion Sequences and Recombination on the Population Structure of Staphylococcus haemolyticus.

PubMed

Bouchami, Ons; de Lencastre, Herminia; Miragaia, Maria

2016-01-01

Staphylococcus haemolyticus is one of the most common pathogens associated with medical-device related infections, but its molecular epidemiology is poorly explored. In the current study, we aimed to better understand the genetic mechanisms contributing to S. haemolyticus diversity in the hospital environment and their impact on the population structure and clinical relevant phenotypic traits. The analysis of a representative S. haemolyticus collection by multilocus sequence typing (MLST) has identified a single highly prevalent and diverse genetic lineage of nosocomial S. haemolyticus clonal complex (CC) 29 accounting for 91% of the collection of isolates disseminated worldwide. The examination of the sequence changes at MLST loci during clonal diversification showed that recombination had a higher impact than mutation in shaping the S. haemolyticus population. Also, we ascertained that another mechanism contributing significantly to clonal diversification and adaptation was mediated by insertion sequence (IS) elements. We found that all nosocomial S. haemolyticus, belonging to different STs, were rich in IS1272 copies, as determined by Southern hybridization of macrorestriction patterns. In particular, we observed that the chromosome of a S. haemolyticus strain within CC29 was highly unstable during serial growth in vitro which paralleled with IS1272 transposition events and changes in clinically relevant phenotypic traits namely, mannitol fermentation, susceptibility to beta-lactams, biofilm formation and hemolysis. Our results suggest that recombination and IS transposition might be a strategy of adaptation, evolution and pathogenicity of the major S. haemolyticus prevalent lineage in the hospital environment.

Impact of Insertion Sequences and Recombination on the Population Structure of Staphylococcus haemolyticus

PubMed Central

Bouchami, Ons; de Lencastre, Herminia; Miragaia, Maria

2016-01-01

Staphylococcus haemolyticus is one of the most common pathogens associated with medical-device related infections, but its molecular epidemiology is poorly explored. In the current study, we aimed to better understand the genetic mechanisms contributing to S. haemolyticus diversity in the hospital environment and their impact on the population structure and clinical relevant phenotypic traits. The analysis of a representative S. haemolyticus collection by multilocus sequence typing (MLST) has identified a single highly prevalent and diverse genetic lineage of nosocomial S. haemolyticus clonal complex (CC) 29 accounting for 91% of the collection of isolates disseminated worldwide. The examination of the sequence changes at MLST loci during clonal diversification showed that recombination had a higher impact than mutation in shaping the S. haemolyticus population. Also, we ascertained that another mechanism contributing significantly to clonal diversification and adaptation was mediated by insertion sequence (IS) elements. We found that all nosocomial S. haemolyticus, belonging to different STs, were rich in IS1272 copies, as determined by Southern hybridization of macrorestriction patterns. In particular, we observed that the chromosome of a S. haemolyticus strain within CC29 was highly unstable during serial growth in vitro which paralleled with IS1272 transposition events and changes in clinically relevant phenotypic traits namely, mannitol fermentation, susceptibility to beta-lactams, biofilm formation and hemolysis. Our results suggest that recombination and IS transposition might be a strategy of adaptation, evolution and pathogenicity of the major S. haemolyticus prevalent lineage in the hospital environment. PMID:27249649

Imaging-Genetics in Dyslexia: Connecting risk genetic variants to brain neuroimaging and ultimately to reading impairments

PubMed Central

Eicher, John D.; Gruen, Jeffrey R.

2013-01-01

Dyslexia is a common pediatric disorder that affects 5-17% of schoolchildren in the United States. It is marked by unexpected difficulties in fluent reading despite adequate intelligence, opportunity, and instruction. Classically, neuropsychologists have studied dyslexia using a variety of neurocognitive batteries to gain insight into the specific deficits and impairments in affected children. Since dyslexia is a complex genetic trait with high heritability, analyses conditioned on performance on these neurocognitive batteries have been used to try to identify associated genes. This has led to some successes in identifying contributing genes, although much of the heritability remains unexplained. Additionally, the lack of relevant human brain tissue for analysis and the challenges of modeling a uniquely human trait in animals are barriers to advancing our knowledge of the underlying pathophysiology. In vivo imaging technologies, however, present new opportunities to examine dyslexia and reading skills in a clearly relevant context in human subjects. Recent investigations have started to integrate these imaging data with genetic data in attempts to gain a more complete and complex understanding of reading processes. In addition to bridging the gap from genetic risk variant to a discernible neuroimaging phenotype and ultimately to the clinical impairments in reading performance, the use of neuroimaging phenotypes will reveal novel risk genes and variants. In this article, we briefly discuss the genetic and imaging investigations and take an in-depth look at the recent imaging-genetics investigations of dyslexia. PMID:23916419

Selection against canine hip dysplasia: success or failure?

PubMed

Wilson, Bethany; Nicholas, Frank W; Thomson, Peter C

2011-08-01

Canine hip dysplasia (CHD) is a multifactorial skeletal disorder which is very common in pedigree dogs and represents a huge concern for canine welfare. Control schemes based on selective breeding have been in operation for decades. The aim of these schemes is to reduce the impact of CHD on canine welfare by selecting for reduced radiographic evidence of CHD pathology as assessed by a variety of phenotypes. There is less information regarding the genotypic correlation between these phenotypes and the impact of CHD on canine welfare. Although the phenotypes chosen as the basis for these control schemes have displayed heritable phenotypic variation in many studies, success in achieving improvement in the phenotypes has been mixed. There is significant room for improvement in the current schemes through the use of estimated breeding values (EBVs), which can combine a dog's CHD phenotype with CHD phenotypes of relatives, other phenotypes as they are proven to be genetically correlated with CHD (especially elbow dysplasia phenotypes), and information from genetic tests for population-relevant DNA markers, as such tests become available. Additionally, breed clubs should be encouraged and assisted to formulate rational, evidenced-based breeding recommendations for CHD which suit their individual circumstances and dynamically to adjust the breeding recommendations based on continuous tracking of CHD genetic trends. These improvements can assist in safely and effectively reducing the impact of CHD on pedigree dog welfare. Copyright © 2011 Elsevier Ltd. All rights reserved.

Transcriptional profiling identifies the long noncoding RNA plasmacytoma variant translocation (PVT1) as a novel regulator of the asthmatic phenotype in human airway smooth muscle.

PubMed

Austin, Philip J; Tsitsiou, Eleni; Boardman, Charlotte; Jones, Simon W; Lindsay, Mark A; Adcock, Ian M; Chung, Kian Fan; Perry, Mark M

2017-03-01

The mechanism underlying nonsevere and severe asthma remains unclear, although it is commonly associated with increased airway smooth muscle (ASM) mass. Long noncoding RNAs (lncRNAs) are known to be important in regulating healthy primary airway smooth muscle cells (ASMCs), whereas changed expression has been observed in CD8 T cells from patients with severe asthma. Primary ASMCs were isolated from healthy subjects (n = 9) and patients classified as having nonsevere (n = 9) or severe (n = 9) asthma. ASMCs were exposed to dexamethasone and FCS. mRNA and lncRNA expression was measured by using a microarray and quantitative real-time PCR. Bioinformatic analysis was used to examine relevant biological pathways. Finally, the lncRNA plasmacytoma variant translocation 1 (PVT1) was inhibited by transfection of primary ASMCs with small interfering RNAs, and the effect on ASMC phenotype was examined. The mRNA expression profile was significantly different between patient groups after exposure to dexamethasone and FCS, and these were associated with biological pathways that might be relevant to the pathogenesis of asthma, including cellular proliferation and pathways associated with glucocorticoid activity. We also observed a significant change in lncRNA expression, yet the expression of only one lncRNA (PVT1) is decreased in patients with corticosteroid-sensitive nonsevere asthma and increased in patients with corticosteroid-insensitive severe asthma. Subsequent targeting studies demonstrated the importance of this lncRNA in controlling both proliferation and IL-6 release in ASMCs from patients with severe asthma. lncRNAs are associated with the aberrant phenotype observed in ASMCs from asthmatic patients. Targeting PVT1 might be effective in reducing airway remodeling in asthmatic patients. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Sexual dimorphism of sleep regulated by juvenile hormone signaling in Drosophila

PubMed Central

Zhang, Enyan; Du, Juan; Liu, Suning; Price, Jeffrey

2018-01-01

Sexually dimorphic phenotypes are a universal phenomenon in animals. In the model animal fruit fly Drosophila, males and females exhibit long- and short-sleep phenotypes, respectively. However, the mechanism is still a mystery. In this study, we showed that juvenile hormone (JH) is involved in regulation of sexually dimorphic sleep in Drosophila, in which gain of JH function enlarges differences of the dimorphic sleep phenotype with higher sleep in males and lower sleep in females, while loss of JH function blurs these differences and results in feminization of male sleep and masculinization of female sleep. Further studies indicate that germ cell-expressed (GCE), one of the JH receptors, mediates the response in the JH pathway because the sexually dimorphic sleep phenotypes cannot be rescued by JH hormone in a gce deletion mutant. The JH-GCE regulated sleep dimorphism is generated through the sex differentiation-related genes -fruitless (fru) and doublesex (dsx) in males and sex-lethal (sxl), transformer (tra) and doublesex (dsx) in females. These are the “switch” genes that separately control the sleep pattern in males and females. Moreover, analysis of sleep deprivation and circadian behaviors showed that the sexually dimorphic sleep induced by JH signals is a change of sleep drive and independent of the circadian clock. Furthermore, we found that JH seems to also play an unanticipated role in antagonism of an aging-induced sleep decrease in male flies. Taken together, these results indicate that the JH signal pathway is critical for maintenance of sexually dimorphic sleep by regulating sex-relevant genes. PMID:29617359

Application of a genetically encoded biosensor for live cell imaging of L-valine production in pyruvate dehydrogenase complex-deficient Corynebacterium glutamicum strains.

PubMed

Mustafi, Nurije; Grünberger, Alexander; Mahr, Regina; Helfrich, Stefan; Nöh, Katharina; Blombach, Bastian; Kohlheyer, Dietrich; Frunzke, Julia

2014-01-01

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains.

Application of a Genetically Encoded Biosensor for Live Cell Imaging of L-Valine Production in Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum Strains

PubMed Central

Mahr, Regina; Helfrich, Stefan; Nöh, Katharina; Blombach, Bastian; Kohlheyer, Dietrich; Frunzke, Julia

2014-01-01

The majority of biotechnologically relevant metabolites do not impart a conspicuous phenotype to the producing cell. Consequently, the analysis of microbial metabolite production is still dominated by bulk techniques, which may obscure significant variation at the single-cell level. In this study, we have applied the recently developed Lrp-biosensor for monitoring of amino acid production in single cells of gradually engineered L-valine producing Corynebacterium glutamicum strains based on the pyruvate dehydrogenase complex-deficient (PDHC) strain C. glutamicum ΔaceE. Online monitoring of the sensor output (eYFP fluorescence) during batch cultivation proved the sensor's suitability for visualizing different production levels. In the following, we conducted live cell imaging studies on C. glutamicum sensor strains using microfluidic chip devices. As expected, the sensor output was higher in microcolonies of high-yield producers in comparison to the basic strain C. glutamicum ΔaceE. Microfluidic cultivation in minimal medium revealed a typical Gaussian distribution of single cell fluorescence during the production phase. Remarkably, low amounts of complex nutrients completely changed the observed phenotypic pattern of all strains, resulting in a phenotypic split of the population. Whereas some cells stopped growing and initiated L-valine production, others continued to grow or showed a delayed transition to production. Depending on the cultivation conditions, a considerable fraction of non-fluorescent cells was observed, suggesting a loss of metabolic activity. These studies demonstrate that genetically encoded biosensors are a valuable tool for monitoring single cell productivity and to study the phenotypic pattern of microbial production strains. PMID:24465669

The structure of a gene co-expression network reveals biological functions underlying eQTLs.

PubMed

Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali

2013-01-01

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.

Genome-wide detection of intervals of genetic heterogeneity associated with complex traits

PubMed Central

Llinares-López, Felipe; Grimm, Dominik G.; Bodenham, Dean A.; Gieraths, Udo; Sugiyama, Mahito; Rowan, Beth; Borgwardt, Karsten

2015-01-01

Motivation: Genetic heterogeneity, the fact that several sequence variants give rise to the same phenotype, is a phenomenon that is of the utmost interest in the analysis of complex phenotypes. Current approaches for finding regions in the genome that exhibit genetic heterogeneity suffer from at least one of two shortcomings: (i) they require the definition of an exact interval in the genome that is to be tested for genetic heterogeneity, potentially missing intervals of high relevance, or (ii) they suffer from an enormous multiple hypothesis testing problem due to the large number of potential candidate intervals being tested, which results in either many false positives or a lack of power to detect true intervals. Results: Here, we present an approach that overcomes both problems: it allows one to automatically find all contiguous sequences of single nucleotide polymorphisms in the genome that are jointly associated with the phenotype. It also solves both the inherent computational efficiency problem and the statistical problem of multiple hypothesis testing, which are both caused by the huge number of candidate intervals. We demonstrate on Arabidopsis thaliana genome-wide association study data that our approach can discover regions that exhibit genetic heterogeneity and would be missed by single-locus mapping. Conclusions: Our novel approach can contribute to the genome-wide discovery of intervals that are involved in the genetic heterogeneity underlying complex phenotypes. Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/sis.html. Contact: felipe.llinares@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072488

Preparation of sumoylated substrates for biochemical analysis.

PubMed

Knipscheer, Puck; Klug, Helene; Sixma, Titia K; Pichler, Andrea

2009-01-01

Covalent modification of proteins with SUMO (small ubiquitin related modifier) affects many cellular processes like transcription, nuclear transport, DNA repair and cell cycle progression. Although hundreds of SUMO targets have been identified, for several of them the function remains obscure. In the majority of cases sumoylation is investigated via "loss of modification" analysis by mutating the relevant target lysine. However, in other cases this approach is not successful since mapping of the modification site is problematic or mutation does not cause an obvious phenotype. These latter cases ask for different approaches to investigate the target modification. One possibility is to choose the opposite approach, a "gain in modification" analysis by producing both SUMO modified and unmodified protein in vitro and comparing them in functional assays. Here, we describe the purification of the ubiquitin conjugating enzyme E2-25K, its in vitro sumoylation with recombinant enzymes and the subsequent separation and purification of the modified and the unmodified forms.

Exploratory subsetting of autism families based on savant skills improves evidence of genetic linkage to 15q11-q13.

PubMed

Nurmi, Erika L; Dowd, Michael; Tadevosyan-Leyfer, Ovsanna; Haines, Jonathan L; Folstein, Susan E; Sutcliffe, James S

2003-07-01

Autism displays a remarkably high heritability but a complex genetic etiology. One approach to identifying susceptibility loci under these conditions is to define more homogeneous subsets of families on the basis of genetically relevant phenotypic or biological characteristics that vary from case to case. The authors performed a principal components analysis, using items from the Autism Diagnostic Interview, which resulted in six clusters of variables, five of which showed significant sib-sib correlation. The utility of these phenotypic subsets was tested in an exploratory genetic analysis of the autism candidate region on chromosome 15q11-q13. When the Collaborative Linkage Study of Autism sample was divided, on the basis of mean proband score for the "savant skills" cluster, the heterogeneity logarithm of the odds under a recessive model at D15S511, within the GABRB3 gene, increased from 0.6 to 2.6 in the subset of families in which probands had greater savant skills. These data are consistent with the genetic contribution of a 15q locus to autism susceptibility in a subset of affected individuals exhibiting savant skills. Similar types of skills have been noted in individuals with Prader-Willi syndrome, which results from deletions of this chromosomal region.

Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease.

PubMed

Jostins, Luke; Ripke, Stephan; Weersma, Rinse K; Duerr, Richard H; McGovern, Dermot P; Hui, Ken Y; Lee, James C; Schumm, L Philip; Sharma, Yashoda; Anderson, Carl A; Essers, Jonah; Mitrovic, Mitja; Ning, Kaida; Cleynen, Isabelle; Theatre, Emilie; Spain, Sarah L; Raychaudhuri, Soumya; Goyette, Philippe; Wei, Zhi; Abraham, Clara; Achkar, Jean-Paul; Ahmad, Tariq; Amininejad, Leila; Ananthakrishnan, Ashwin N; Andersen, Vibeke; Andrews, Jane M; Baidoo, Leonard; Balschun, Tobias; Bampton, Peter A; Bitton, Alain; Boucher, Gabrielle; Brand, Stephan; Büning, Carsten; Cohain, Ariella; Cichon, Sven; D'Amato, Mauro; De Jong, Dirk; Devaney, Kathy L; Dubinsky, Marla; Edwards, Cathryn; Ellinghaus, David; Ferguson, Lynnette R; Franchimont, Denis; Fransen, Karin; Gearry, Richard; Georges, Michel; Gieger, Christian; Glas, Jürgen; Haritunians, Talin; Hart, Ailsa; Hawkey, Chris; Hedl, Matija; Hu, Xinli; Karlsen, Tom H; Kupcinskas, Limas; Kugathasan, Subra; Latiano, Anna; Laukens, Debby; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mahy, Gillian; Mansfield, John; Morgan, Angharad R; Mowat, Craig; Newman, William; Palmieri, Orazio; Ponsioen, Cyriel Y; Potocnik, Uros; Prescott, Natalie J; Regueiro, Miguel; Rotter, Jerome I; Russell, Richard K; Sanderson, Jeremy D; Sans, Miquel; Satsangi, Jack; Schreiber, Stefan; Simms, Lisa A; Sventoraityte, Jurgita; Targan, Stephan R; Taylor, Kent D; Tremelling, Mark; Verspaget, Hein W; De Vos, Martine; Wijmenga, Cisca; Wilson, David C; Winkelmann, Juliane; Xavier, Ramnik J; Zeissig, Sebastian; Zhang, Bin; Zhang, Clarence K; Zhao, Hongyu; Silverberg, Mark S; Annese, Vito; Hakonarson, Hakon; Brant, Steven R; Radford-Smith, Graham; Mathew, Christopher G; Rioux, John D; Schadt, Eric E; Daly, Mark J; Franke, Andre; Parkes, Miles; Vermeire, Severine; Barrett, Jeffrey C; Cho, Judy H

2012-11-01

Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations. Genome-wide association studies and subsequent meta-analyses of these two diseases as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy, in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases. Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

Understanding the Onset of Health Impacts Caused by Disturbances

DTIC Science & Technology

2015-09-30

will define the PCoD Health stage in a way that we can start to integrate ecological and physiological PCoD research. OBJECTIVES In order to...for the first time assess the relevance of adipose transcriptomic and metabolomic biomarkers as measures relevant to PCoD in cetaceans. We aim to...individuals. APPROACH The Population Consequences of Disturbances ( PCoD ) paradigm provides a mean to link perturbations of individual phenotypic

Epithelial–mesenchymal transition-associated secretory phenotype predicts survival in lung cancer patients

PubMed Central

Reka, Ajaya Kumar; Chen, Guoan; Keshamouni, Venkateshwar G.

2014-01-01

In cancer cells, the process of epithelial–mesenchymal transition (EMT) confers migratory and invasive capacity, resistance to apoptosis, drug resistance, evasion of host immune surveillance and tumor stem cell traits. Cells undergoing EMT may represent tumor cells with metastatic potential. Characterizing the EMT secretome may identify biomarkers to monitor EMT in tumor progression and provide a prognostic signature to predict patient survival. Utilizing a transforming growth factor-β-induced cell culture model of EMT, we quantitatively profiled differentially secreted proteins, by GeLC-tandem mass spectrometry. Integrating with the corresponding transcriptome, we derived an EMT-associated secretory phenotype (EASP) comprising of proteins that were differentially upregulated both at protein and mRNA levels. Four independent primary tumor-derived gene expression data sets of lung cancers were used for survival analysis by the random survival forests (RSF) method. Analysis of 97-gene EASP expression in human lung adenocarcinoma tumors revealed strong positive correlations with lymph node metastasis, advanced tumor stage and histological grade. RSF analysis built on a training set (n = 442), including age, sex and stage as variables, stratified three independent lung cancer data sets into low-, medium- and high-risk groups with significant differences in overall survival. We further refined EASP to a 20 gene signature (rEASP) based on variable importance scores from RSF analysis. Similar to EASP, rEASP predicted survival of both adenocarcinoma and squamous carcinoma patients. More importantly, it predicted survival in the early-stage cancers. These results demonstrate that integrative analysis of the critical biological process of EMT provides mechanism-based and clinically relevant biomarkers with significant prognostic value. PMID:24510113

Phenotyping for drought tolerance of crops in the genomics era

PubMed Central

Tuberosa, Roberto

2012-01-01

Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognized obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different water regimes. This review provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars. PMID:23049510

Root Traits and Phenotyping Strategies for Plant Improvement

PubMed Central

Paez-Garcia, Ana; Motes, Christy M.; Scheible, Wolf-Rüdiger; Chen, Rujin; Blancaflor, Elison B.; Monteros, Maria J.

2015-01-01

Roots are crucial for nutrient and water acquisition and can be targeted to enhance plant productivity under a broad range of growing conditions. A current challenge for plant breeding is the limited ability to phenotype and select for desirable root characteristics due to their underground location. Plant breeding efforts aimed at modifying root traits can result in novel, more stress-tolerant crops and increased yield by enhancing the capacity of the plant for soil exploration and, thus, water and nutrient acquisition. Available approaches for root phenotyping in laboratory, greenhouse and field encompass simple agar plates to labor-intensive root digging (i.e., shovelomics) and soil boring methods, the construction of underground root observation stations and sophisticated computer-assisted root imaging. Here, we summarize root architectural traits relevant to crop productivity, survey root phenotyping strategies and describe their advantages, limitations and practical value for crop and forage breeding programs. PMID:27135332

Root Traits and Phenotyping Strategies for Plant Improvement.

PubMed

Paez-Garcia, Ana; Motes, Christy M; Scheible, Wolf-Rüdiger; Chen, Rujin; Blancaflor, Elison B; Monteros, Maria J

2015-06-15

Roots are crucial for nutrient and water acquisition and can be targeted to enhance plant productivity under a broad range of growing conditions. A current challenge for plant breeding is the limited ability to phenotype and select for desirable root characteristics due to their underground location. Plant breeding efforts aimed at modifying root traits can result in novel, more stress-tolerant crops and increased yield by enhancing the capacity of the plant for soil exploration and, thus, water and nutrient acquisition. Available approaches for root phenotyping in laboratory, greenhouse and field encompass simple agar plates to labor-intensive root digging (i.e., shovelomics) and soil boring methods, the construction of underground root observation stations and sophisticated computer-assisted root imaging. Here, we summarize root architectural traits relevant to crop productivity, survey root phenotyping strategies and describe their advantages, limitations and practical value for crop and forage breeding programs.

Metabolic functions of Pseudomonas fluorescens strains from Populus deltoides depend on rhizosphere or endosphere isolation compartment

DOE PAGES

Timm, Collin M.; Campbell, Alicia G.; Utturkar, Sagar M.; ...

2015-10-14

The bacterial microbiota of plants is diverse, with ~1000s of operational taxonomic units (OTUs) associated with any individual plant. In this work we investigate how 19 sequenced Pseudomonas fluorescens strains representing a single OTU isolated from Populus deltoides rhizosphere and endosphere differ using phenotypic analysis, comparative genomics, and metabolic models. While no traits were exclusive to either endosphere or rhizosphere P. fluorescens isolates, multiple pathways relevant for bacterial-plant interactions are enriched in endosphere isolate genomes and growth phenotypes such as phosphate solubilization, protease activity, denitrification and root growth promotion are biased towards endosphere isolates. Endosphere isolates have more metabolic pathwaysmore » for plant signaling compounds and an increased metabolic range that includes utilization of energy rich nucleotides and sugars, consistent with endosphere colonization. Rhizosphere P. fluorescens have fewer pathways important for bacterial-plant interactions but show metabolic bias towards chemical substrates often found in root exudates. This work reveals the diverse functions that may contribute to colonization of the endosphere by bacteria that are enriched in event he most closely related isolates.« less

Developmental roles of tyrosine metabolism enzymes in the blood-sucking insect Rhodnius prolixus

PubMed Central

Oliveira, Pedro L.

2017-01-01

The phenylalanine/tyrosine degradation pathway is frequently described as a catabolic pathway that funnels aromatic amino acids into citric acid cycle intermediates. Previously, we demonstrated that the accumulation of tyrosine generated during the hydrolysis of blood meal proteins in Rhodnius prolixus is potentially toxic, a harmful outcome that is prevented by the action of the first two enzymes in the tyrosine degradation pathway. In this work, we further evaluated the relevance of all other enzymes involved in phenylalanine/tyrosine metabolism in the physiology of this insect. The knockdown of most of these enzymes produced a wide spectrum of distinct phenotypes associated with reproduction, development and nymph survival, demonstrating a highly pleiotropic role of tyrosine metabolism. The phenotypes obtained for two of these enzymes, homogentisate dioxygenase and fumarylacetoacetase, have never before been described in any arthropod. To our knowledge, this report is the first comprehensive gene-silencing analysis of an amino acid metabolism pathway in insects. Amino acid metabolism is exceptionally important in haematophagous arthropods due to their particular feeding behaviour. PMID:28469016

Developmental roles of tyrosine metabolism enzymes in the blood-sucking insect Rhodnius prolixus.

PubMed

Sterkel, Marcos; Oliveira, Pedro L

2017-05-17

The phenylalanine/tyrosine degradation pathway is frequently described as a catabolic pathway that funnels aromatic amino acids into citric acid cycle intermediates. Previously, we demonstrated that the accumulation of tyrosine generated during the hydrolysis of blood meal proteins in Rhodnius prolixus is potentially toxic, a harmful outcome that is prevented by the action of the first two enzymes in the tyrosine degradation pathway. In this work, we further evaluated the relevance of all other enzymes involved in phenylalanine/tyrosine metabolism in the physiology of this insect. The knockdown of most of these enzymes produced a wide spectrum of distinct phenotypes associated with reproduction, development and nymph survival, demonstrating a highly pleiotropic role of tyrosine metabolism. The phenotypes obtained for two of these enzymes, homogentisate dioxygenase and fumarylacetoacetase, have never before been described in any arthropod. To our knowledge, this report is the first comprehensive gene-silencing analysis of an amino acid metabolism pathway in insects. Amino acid metabolism is exceptionally important in haematophagous arthropods due to their particular feeding behaviour. © 2017 The Author(s).

From the Psychiatrist’s Couch to Induced Pluripotent Stem Cells: Bipolar Disease in a Dish

PubMed Central

Hoffmann, Anke; Sportelli, Vincenza; Ziller, Michael; Spengler, Dietmar

2018-01-01

Bipolar disease (BD) is one of the major public health burdens worldwide and more people are affected every year. Comprehensive genetic studies have associated thousands of single nucleotide polymorphisms (SNPs) with BD risk; yet, very little is known about their functional roles. Induced pluripotent stem cells (iPSCs) are powerful tools for investigating the relationship between genotype and phenotype in disease-relevant tissues and cell types. Neural cells generated from BD-specific iPSCs are thought to capture associated genetic risk factors, known and unknown, and to allow the analysis of their effects on cellular and molecular phenotypes. Interestingly, an increasing number of studies on BD-derived iPSCs report distinct alterations in neural patterning, postmitotic calcium signaling, and neuronal excitability. Importantly, these alterations are partly normalized by lithium, a first line treatment in BD. In light of these exciting findings, we discuss current challenges to the field of iPSC-based disease modelling and future steps to be taken in order to fully exploit the potential of this approach for the investigation of BD and the development of new therapies. PMID:29517996

An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility

PubMed Central

Lessard, Samuel; Gatof, Emily Stern; Schupp, Patrick G.; Sher, Falak; Ali, Adnan; Prehar, Sukhpal; Kurita, Ryo; Nakamura, Yukio; Baena, Esther; Oceandy, Delvac; Bauer, Daniel E.

2017-01-01

The lack of mechanistic explanations for many genotype-phenotype associations identified by GWAS precludes thorough assessment of their impact on human health. Here, we conducted an expression quantitative trait locus (eQTL) mapping analysis in erythroblasts and found erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of red blood cells (rbc). The same SNPs were previously associated with mean corpuscular hemoglobin concentration (MCHC) and susceptibility to severe malaria infection. We showed that Atp2b4–/– mice demonstrate increased MCHC, confirming ATP2B4 as the causal gene at this GWAS locus. Using CRISPR-Cas9, we fine mapped the genetic signal to an erythroid-specific enhancer of ATP2B4. Erythroid cells with a deletion of the ATP2B4 enhancer had abnormally high intracellular calcium levels. These results illustrate the power of combined transcriptomic, epigenomic, and genome-editing approaches in characterizing noncoding regulatory elements in phenotype-relevant cells. Our study supports ATP2B4 as a potential target for modulating rbc hydration in erythroid disorders and malaria infection. PMID:28714864

Metabolic functions of Pseudomonas fluorescens strains from Populus deltoides depend on rhizosphere or endosphere isolation compartment

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

Timm, Collin M.; Campbell, Alicia G.; Utturkar, Sagar M.

The bacterial microbiota of plants is diverse, with ~1000s of operational taxonomic units (OTUs) associated with any individual plant. In this work we investigate how 19 sequenced Pseudomonas fluorescens strains representing a single OTU isolated from Populus deltoides rhizosphere and endosphere differ using phenotypic analysis, comparative genomics, and metabolic models. While no traits were exclusive to either endosphere or rhizosphere P. fluorescens isolates, multiple pathways relevant for bacterial-plant interactions are enriched in endosphere isolate genomes and growth phenotypes such as phosphate solubilization, protease activity, denitrification and root growth promotion are biased towards endosphere isolates. Endosphere isolates have more metabolic pathwaysmore » for plant signaling compounds and an increased metabolic range that includes utilization of energy rich nucleotides and sugars, consistent with endosphere colonization. Rhizosphere P. fluorescens have fewer pathways important for bacterial-plant interactions but show metabolic bias towards chemical substrates often found in root exudates. This work reveals the diverse functions that may contribute to colonization of the endosphere by bacteria that are enriched in event he most closely related isolates.« less

Molecular basis of Williams-Beuren syndrome: TFII-I regulated targets involved in craniofacial development.

PubMed

Makeyev, Aleksandr V; Bayarsaihan, Dashzeveg

2011-01-01

The aim of this study is to identify gene targets of TFII-I transcription factors involved in craniofacial development. Recent findings in individuals with Williams-Beuren syndrome who show facial dysmorphism and cognitive defects have pointed to TFII-I genes (GTF2I and GTF2IRD1) as the prime candidates responsible for these clinical features. However, TFII-I proteins are multifunctional transcriptional factors regulating a number of genes during development, and how their haploinsufficiency leads to the Williams-Beuren syndrome phenotype is currently unknown. Here we report the identification of three genes with a well-established relevance to craniofacial development as direct TFII-I targets. These genes, craniofacial development protein 1 (Cfdp1), Sec23 homolog A (Sec23a), and nuclear receptor binding SET domain protein 1 (Nsd1), contain consensus TFII-I binding sites in their proximal promoters; the chromatin immunoprecipitation analysis showed that TFII-I transcription factors are recruited to these sites in vivo. The results suggest that transcriptional regulation of these genes by TFII-I proteins could provide a possible genotype-phenotype link in Williams-Beuren syndrome.

An erythroid-specific ATP2B4 enhancer mediates red blood cell hydration and malaria susceptibility.

PubMed

Lessard, Samuel; Gatof, Emily Stern; Beaudoin, Mélissa; Schupp, Patrick G; Sher, Falak; Ali, Adnan; Prehar, Sukhpal; Kurita, Ryo; Nakamura, Yukio; Baena, Esther; Ledoux, Jonathan; Oceandy, Delvac; Bauer, Daniel E; Lettre, Guillaume

2017-08-01

The lack of mechanistic explanations for many genotype-phenotype associations identified by GWAS precludes thorough assessment of their impact on human health. Here, we conducted an expression quantitative trait locus (eQTL) mapping analysis in erythroblasts and found erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of red blood cells (rbc). The same SNPs were previously associated with mean corpuscular hemoglobin concentration (MCHC) and susceptibility to severe malaria infection. We showed that Atp2b4-/- mice demonstrate increased MCHC, confirming ATP2B4 as the causal gene at this GWAS locus. Using CRISPR-Cas9, we fine mapped the genetic signal to an erythroid-specific enhancer of ATP2B4. Erythroid cells with a deletion of the ATP2B4 enhancer had abnormally high intracellular calcium levels. These results illustrate the power of combined transcriptomic, epigenomic, and genome-editing approaches in characterizing noncoding regulatory elements in phenotype-relevant cells. Our study supports ATP2B4 as a potential target for modulating rbc hydration in erythroid disorders and malaria infection.

Expression of Genes Involved in Drosophila Wing Morphogenesis and Vein Patterning Are Altered by Spaceflight

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia A.; Hosamani, Ravikumar; Bhattacharya, Sharmila

2015-01-01

Imaginal wing discs of Drosophila melanogaster (fruit fly) defined during embryogenesis ultimately result in mature wings of stereotyped (specific) venation patterning. Major regulators of wing disc development are the epidermal growth factor receptor (EGF), Notch, Hedgehog (Hh), Wingless (Wg), and Dpp signaling pathways. Highly stereotyped vascular patterning is also characteristic of tissues in other organisms flown in space such as the mouse retina and leaves of Arabidopsis thaliana. Genetic and other adaptations of vascular patterning to space environmental factors have not yet been systematically quantified, despite widespread recognition of their critical importance for terrestrial and microgravity applications. Here we report changes in gene expression with space flight related to Drosophila wing morphogenesis and vein patterning. In addition, genetically modified phenotypes of increasingly abnormal ectopic wing venation in the Drosophila wing1 were analyzed by NASA's VESsel GENeration Analysis (VESGEN) software2. Our goal is to further develop insightful vascular mappings associated with bioinformatic dimensions of genetic or other molecular phenotypes for correlation with genetic and other molecular profiling relevant to NASA's GeneLab and other Space Biology exploration initiatives.

Epithelial-mesenchymal transition (EMT) is not sufficient for spontaneous murine breast cancer metastasis.

PubMed

Lou, Yuanmei; Preobrazhenska, Olena; auf dem Keller, Ulrich; Sutcliffe, Margaret; Barclay, Lorena; McDonald, Paul C; Roskelley, Calvin; Overall, Christopher M; Dedhar, Shoukat

2008-10-01

Epithelial-mesenchymal transition (EMT) has been linked to metastatic propensity. The 4T1 tumor is a clinically relevant model of spontaneous breast cancer metastasis. Here we characterize 4T1-derived cell lines for EMT, in vitro invasiveness and in vivo metastatic ability. Contrary to expectations, 67NR cells, which form primary tumors but fail to metastasize, express vimentin and N-cadherin, but not E-cadherin. 4T1 cells express E-cadherin and ZO-1, but are migratory, invasive, and metastasize to multiple sites. 66cl4 cells form lung metastases and display a mixed phenotype, but are not as migratory or invasive as 67NR cells. These findings demonstrate that the metastatic ability of breast cancer cells does not strictly correlate with genotypic and phenotypic properties of EMT per se, and suggest that other processes may govern metastatic capability. Gene expression analysis of primary tumors did not identify differences in EMT markers, but did reveal candidate genes that may influence metastatic ability. Copyright (c) 2008 Wiley-Liss, Inc.

Genetic Variability of Smoking Persistence in African Americans

PubMed Central

Hamidovic, A; Kasberger, J; Young, T; Goodloe, R; Redline, S; Buxbaum, S; Benowitz, N; Bergen, A; Butler, K; Franceschini, N; Gharib, S; Hitsman, B; Levy, D; Meng, Y; Papanicolaou, G; Preiss, S; Spring, B; Styn, M; Tong, E; White, W; Wiggins, K; Jorgenson, E

2011-01-01

To date, most genetic association analyses of smoking behaviors have been conducted in populations of European ancestry and many of these studies focused on the phenotype that measures smoking quantity, i.e. cigarettes per day. Additional association studies in diverse populations with different linkage disequilibrium (LD) patterns and an alternate phenotype, such as total tobacco exposure which accounts for intermittent periods of smoking cessation within a larger smoking period as measured in large cardiovascular risk studies, can aid the search for variants relevant to smoking behavior. For these reasons, we undertook an association analysis using a genotyping array that includes 2100 genes to analyze smoking persistence in unrelated African-American participants from The Atherosclerosis Risk in Communities (ARIC) study. A locus located ~ 4 Kb downstream from the 3’ UTR of the Brain-Derived Neurotrophic Factor (BDNF) significantly influenced smoking persistence. In addition, independent variants rs12915366 and rs12914385 in the cluster of genes encoding nicotinic acetylcholine receptor subunits (CHRNA5-CHRNA3-CHRNB4) on 15q25.1 were also associated with the phenotype in this sample of African American subjects. To our knowledge, this is the first study to more extensively evaluate the genome in the African American population as a limited number of previous studies of smoking behavior in this population included evaluations of only single genomic regions. PMID:21436384

Characterizing partial AZFc deletions of the Y chromosome with amplicon-specific sequence markers

PubMed Central

Navarro-Costa, Paulo; Pereira, Luísa; Alves, Cíntia; Gusmão, Leonor; Proença, Carmen; Marques-Vidal, Pedro; Rocha, Tiago; Correia, Sónia C; Jorge, Sónia; Neves, António; Soares, Ana P; Nunes, Joaquim; Calhaz-Jorge, Carlos; Amorim, António; Plancha, Carlos E; Gonçalves, João

2007-01-01

Background The AZFc region of the human Y chromosome is a highly recombinogenic locus containing multi-copy male fertility genes located in repeated DNA blocks (amplicons). These AZFc gene families exhibit slight sequence variations between copies which are considered to have functional relevance. Yet, partial AZFc deletions yield phenotypes ranging from normospermia to azoospermia, thwarting definite conclusions on their real impact on fertility. Results The amplicon content of partial AZFc deletion products was characterized with novel amplicon-specific sequence markers. Data indicate that partial AZFc deletions are a male infertility risk [odds ratio: 5.6 (95% CI: 1.6–30.1)] and although high diversity of partial deletion products and sequence conversion profiles were recorded, the AZFc marker profiles detected in fertile men were also observed in infertile men. Additionally, the assessment of rearrangement recurrence by Y-lineage analysis indicated that while partial AZFc deletions occurred in highly diverse samples, haplotype diversity was minimal in fertile men sharing identical marker profiles. Conclusion Although partial AZFc deletion products are highly heterogeneous in terms of amplicon content, this plasticity is not sufficient to account for the observed phenotypical variance. The lack of causative association between the deletion of specific gene copies and infertility suggests that AZFc gene content might be part of a multifactorial network, with Y-lineage evolution emerging as a possible phenotype modulator. PMID:17903263

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.

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.

Behavioral phenotypes of genetic mouse models of autism.

PubMed

Kazdoba, T M; Leach, P T; Crawley, J N

2016-01-01

More than a hundred de novo single gene mutations and copy-number variants have been implicated in autism, each occurring in a small subset of cases. Mutant mouse models with syntenic mutations offer research tools to gain an understanding of the role of each gene in modulating biological and behavioral phenotypes relevant to autism. Knockout, knockin and transgenic mice incorporating risk gene mutations detected in autism spectrum disorder and comorbid neurodevelopmental disorders are now widely available. At present, autism spectrum disorder is diagnosed solely by behavioral criteria. We developed a constellation of mouse behavioral assays designed to maximize face validity to the types of social deficits and repetitive behaviors that are central to an autism diagnosis. Mouse behavioral assays for associated symptoms of autism, which include cognitive inflexibility, anxiety, hyperactivity, and unusual reactivity to sensory stimuli, are frequently included in the phenotypic analyses. Over the past 10 years, we and many other laboratories around the world have employed these and additional behavioral tests to phenotype a large number of mutant mouse models of autism. In this review, we highlight mouse models with mutations in genes that have been identified as risk genes for autism, which work through synaptic mechanisms and through the mTOR signaling pathway. Robust, replicated autism-relevant behavioral outcomes in a genetic mouse model lend credence to a causal role for specific gene contributions and downstream biological mechanisms in the etiology of autism. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models.

PubMed

Schofield, Paul N; Sundberg, John P; Hoehndorf, Robert; Gkoutos, Georgios V

2011-09-01

The systematic investigation of the phenotypes associated with genotypes in model organisms holds the promise of revealing genotype-phenotype relations directly and without additional, intermediate inferences. Large-scale projects are now underway to catalog the complete phenome of a species, notably the mouse. With the increasing amount of phenotype information becoming available, a major challenge that biology faces today is the systematic analysis of this information and the translation of research results across species and into an improved understanding of human disease. The challenge is to integrate and combine phenotype descriptions within a species and to systematically relate them to phenotype descriptions in other species, in order to form a comprehensive understanding of the relations between those phenotypes and the genotypes involved in human disease. We distinguish between two major approaches for comparative phenotype analyses: the first relies on evolutionary relations to bridge the species gap, while the other approach compares phenotypes directly. In particular, the direct comparison of phenotypes relies heavily on the quality and coherence of phenotype and disease databases. We discuss major achievements and future challenges for these databases in light of their potential to contribute to the understanding of the molecular mechanisms underlying human disease. In particular, we discuss how the use of ontologies and automated reasoning can significantly contribute to the analysis of phenotypes and demonstrate their potential for enabling translational research.

Assessing Sociability, Social Memory, and Pup Retrieval in Mice.

PubMed

Zimprich, Annemarie; Niessing, Jörn; Cohen, Lior; Garrett, Lillian; Einicke, Jan; Sperling, Bettina; Schmidt, Mathias V; Hölter, Sabine M

2017-12-20

Adaptive social behavior is important in mammals, both for the well-being of the individual and for the thriving of the species. Dysfunctions in social behavior occur in many neurodevelopmental and psychiatric diseases, and research into the genetic components of disease-relevant social deficits can open up new avenues for understanding the underlying biological mechanisms and therapeutic interventions. Genetically modified mouse models are particularly useful in this respect, and robust experimental protocols are needed to reliably assess relevant social behavior phenotypes. Here we describe in detail three protocols to quantitatively measure sociability, one of the most frequently investigated social behavior phenotypes in mice, using a three-chamber sociability test. These protocols can be extended to also assess social memory. In addition, we provide a detailed protocol on pup retrieval, which is a particularly robust maternal behavior amenable to various scientific questions. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Dissecting Alzheimer disease in Down syndrome using mouse models

PubMed Central

Choong, Xun Yu; Tosh, Justin L.; Pulford, Laura J.; Fisher, Elizabeth M. C.

2015-01-01

Down syndrome (DS) is a common genetic condition caused by the presence of three copies of chromosome 21 (trisomy 21). This greatly increases the risk of Alzheimer disease (AD), but although virtually all people with DS have AD neuropathology by 40 years of age, not all develop dementia. To dissect the genetic contribution of trisomy 21 to DS phenotypes including those relevant to AD, a range of DS mouse models has been generated which are trisomic for chromosome segments syntenic to human chromosome 21. Here, we consider key characteristics of human AD in DS (AD-DS), and our current state of knowledge on related phenotypes in AD and DS mouse models. We go on to review important features needed in future models of AD-DS, to understand this type of dementia and so highlight pathogenic mechanisms relevant to all populations at risk of AD. PMID:26528151

Dissecting Alzheimer disease in Down syndrome using mouse models.

PubMed

Choong, Xun Yu; Tosh, Justin L; Pulford, Laura J; Fisher, Elizabeth M C

2015-01-01

Down syndrome (DS) is a common genetic condition caused by the presence of three copies of chromosome 21 (trisomy 21). This greatly increases the risk of Alzheimer disease (AD), but although virtually all people with DS have AD neuropathology by 40 years of age, not all develop dementia. To dissect the genetic contribution of trisomy 21 to DS phenotypes including those relevant to AD, a range of DS mouse models has been generated which are trisomic for chromosome segments syntenic to human chromosome 21. Here, we consider key characteristics of human AD in DS (AD-DS), and our current state of knowledge on related phenotypes in AD and DS mouse models. We go on to review important features needed in future models of AD-DS, to understand this type of dementia and so highlight pathogenic mechanisms relevant to all populations at risk of AD.

Stem Cell Microencapsulation for Phenotypic Control, Bioprocessing, and Transplantation

PubMed Central

Wilson, Jenna L.

2014-01-01

Cell microencapsulation has been utilized for decades as a means to shield cells from the external environment while simultaneously permitting transport of oxygen, nutrients, and secretory molecules. In designing cell therapies, donor primary cells are often difficult to obtain and expand to appropriate numbers, rendering stem cells an attractive alternative due to their capacities for self-renewal, differentiation, and trophic factor secretion. Microencapsulation of stem cells offers several benefits, namely the creation of a defined microenvironment which can be designed to modulate stem cell phenotype, protection from hydrodynamic forces and prevention of agglomeration during expansion in suspension bioreactors, and a means to transplant cells behind a semi-permeable barrier, allowing for molecular secretion while avoiding immune reaction. This review will provide an overview of relevant microencapsulation processes and characterization in the context of maintaining stem cell potency, directing differentiation, investigating scalable production methods, and transplanting stem cells for clinically relevant disorders. PMID:23239279

Development of Proteomics-Based Fungicides: New Strategies for Environmentally Friendly Control of Fungal Plant Diseases

PubMed Central

Acero, Francisco Javier Fernández; Carbú, María; El-Akhal, Mohamed Rabie; Garrido, Carlos; González-Rodríguez, Victoria E.; Cantoral, Jesús M.

2011-01-01

Proteomics has become one of the most relevant high-throughput technologies. Several approaches have been used for studying, for example, tumor development, biomarker discovery, or microbiology. In this “post-genomic” era, the relevance of these studies has been highlighted as the phenotypes determined by the proteins and not by the genotypes encoding them that is responsible for the final phenotypes. One of the most interesting outcomes of these technologies is the design of new drugs, due to the discovery of new disease factors that may be candidates for new therapeutic targets. To our knowledge, no commercial fungicides have been developed from targeted molecular research, this review will shed some light on future prospects. We will summarize previous research efforts and discuss future innovations, focused on the fight against one of the main agents causing a devastating crops disease, fungal phytopathogens. PMID:21340014

Temporal controls of the asymmetric cell division cycle in Caulobacter crescentus.

PubMed

Li, Shenghua; Brazhnik, Paul; Sobral, Bruno; Tyson, John J

2009-08-01

The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA. The regulatory network is cast into a quantitative computational model to investigate in a systematic fashion how these three proteins control the relevant genetic, biochemical and physiological properties of proliferating bacteria. Different controls for both swarmer and stalked cell cycles are represented in the mathematical scheme. The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions. Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

Building Better Environmental Risk Assessments

PubMed Central

Layton, Raymond; Smith, Joe; Macdonald, Phil; Letchumanan, Ramatha; Keese, Paul; Lema, Martin

2015-01-01

Risk assessment is a reasoned, structured approach to address uncertainty based on scientific and technical evidence. It forms the foundation for regulatory decision-making, which is bound by legislative and policy requirements, as well as the need for making timely decisions using available resources. In order to be most useful, environmental risk assessments (ERAs) for genetically modified (GM) crops should provide consistent, reliable, and transparent results across all types of GM crops, traits, and environments. The assessments must also separate essential information from scientific or agronomic data of marginal relevance or value for evaluating risk and complete the assessment in a timely fashion. Challenges in conducting ERAs differ across regulatory systems – examples are presented from Canada, Malaysia, and Argentina. One challenge faced across the globe is the conduct of risk assessments with limited resources. This challenge can be overcome by clarifying risk concepts, placing greater emphasis on data critical to assess environmental risk (for example, phenotypic and plant performance data rather than molecular data), and adapting advances in risk analysis from other relevant disciplines. PMID:26301217

Building Better Environmental Risk Assessments.

PubMed

Layton, Raymond; Smith, Joe; Macdonald, Phil; Letchumanan, Ramatha; Keese, Paul; Lema, Martin

2015-01-01

Risk assessment is a reasoned, structured approach to address uncertainty based on scientific and technical evidence. It forms the foundation for regulatory decision-making, which is bound by legislative and policy requirements, as well as the need for making timely decisions using available resources. In order to be most useful, environmental risk assessments (ERAs) for genetically modified (GM) crops should provide consistent, reliable, and transparent results across all types of GM crops, traits, and environments. The assessments must also separate essential information from scientific or agronomic data of marginal relevance or value for evaluating risk and complete the assessment in a timely fashion. Challenges in conducting ERAs differ across regulatory systems - examples are presented from Canada, Malaysia, and Argentina. One challenge faced across the globe is the conduct of risk assessments with limited resources. This challenge can be overcome by clarifying risk concepts, placing greater emphasis on data critical to assess environmental risk (for example, phenotypic and plant performance data rather than molecular data), and adapting advances in risk analysis from other relevant disciplines.

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis.

PubMed

Lee, Hyokyeong; Moody-Davis, Asher; Saha, Utsab; Suzuki, Brian M; Asarnow, Daniel; Chen, Steven; Arkin, Michelle; Caffrey, Conor R; Singh, Rahul

2012-01-01

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind.

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind. PMID:22369037

Behavioural phenotyping assays for mouse models of autism

PubMed Central

Silverman, Jill L.; Yang, Mu; Lord, Catherine; Crawley, Jacqueline N.

2011-01-01

Autism is a heterogeneous neurodevelopmental disorder of unknown aetiology that affects 1 in 100–150 individuals. Diagnosis is based on three categories of behavioural criteria: abnormal social interactions, communication deficits and repetitive behaviours. Strong evidence for a genetic basis has prompted the development of mouse models with targeted mutations in candidate genes for autism. As the diagnostic criteria for autism are behavioural, phenotyping these mouse models requires behavioural assays with high relevance to each category of the diagnostic symptoms. Behavioural neuroscientists are generating a comprehensive set of assays for social interaction, communication and repetitive behaviours to test hypotheses about the causes of austism. Robust phenotypes in mouse models hold great promise as translational tools for discovering effective treatments for components of autism spectrum disorders. PMID:20559336

Divergent sensory phenotypes in nonspecific arm pain: comparisons with cervical radiculopathy.

PubMed

Moloney, Niamh; Hall, Toby; Doody, Catherine

2015-02-01

To investigate whether distinct sensory phenotypes were identifiable in individuals with nonspecific arm pain (NSAP) and whether these differed from those in people with cervical radiculopathy. A secondary question considered whether the frequency of features of neuropathic pain, kinesiophobia, high pain ratings, hyperalgesia, and allodynia differed according to subgroups of sensory phenotypes. Cross-sectional study. Higher education institution. Forty office workers with NSAP, 17 people with cervical radiculopathy, and 40 age- and sex-matched healthy controls (N=97). Not applicable. Participants were assessed using quantitative sensory testing (QST) comprising thermal and vibration detection thresholds and thermal and pressure pain thresholds; clinical examination; and relevant questionnaires. Sensory phenotypes were identified for each individual in the patient groups using z-score transformation of the QST data. Individuals with NSAP and cervical radiculopathy present with a spectrum of sensory abnormalities; a dominant sensory phenotype was not identifiable in individuals with NSAP. No distinct pattern between clinical features and questionnaire results across sensory phenotypes was identified in either group. When considering sensory phenotypes, neither individuals with NSAP nor individuals with cervical radiculopathy should be considered homogeneous. Therefore, people with either condition may warrant different intervention approaches according to their individual sensory phenotype. Issues relating to the clinical identification of sensory hypersensitivity and the validity of QST are highlighted. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

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.

The Cancer Genome Atlas Clinical Explorer: a web and mobile interface for identifying clinical-genomic driver associations.

PubMed

Lee, HoJoon; Palm, Jennifer; Grimes, Susan M; Ji, Hanlee P

2015-10-27

The Cancer Genome Atlas (TCGA) project has generated genomic data sets covering over 20 malignancies. These data provide valuable insights into the underlying genetic and genomic basis of cancer. However, exploring the relationship among TCGA genomic results and clinical phenotype remains a challenge, particularly for individuals lacking formal bioinformatics training. Overcoming this hurdle is an important step toward the wider clinical translation of cancer genomic/proteomic data and implementation of precision cancer medicine. Several websites such as the cBio portal or University of California Santa Cruz genome browser make TCGA data accessible but lack interactive features for querying clinically relevant phenotypic associations with cancer drivers. To enable exploration of the clinical-genomic driver associations from TCGA data, we developed the Cancer Genome Atlas Clinical Explorer. The Cancer Genome Atlas Clinical Explorer interface provides a straightforward platform to query TCGA data using one of the following methods: (1) searching for clinically relevant genes, micro RNAs, and proteins by name, cancer types, or clinical parameters; (2) searching for genomic/proteomic profile changes by clinical parameters in a cancer type; or (3) testing two-hit hypotheses. SQL queries run in the background and results are displayed on our portal in an easy-to-navigate interface according to user's input. To derive these associations, we relied on elastic-net estimates of optimal multiple linear regularized regression and clinical parameters in the space of multiple genomic/proteomic features provided by TCGA data. Moreover, we identified and ranked gene/micro RNA/protein predictors of each clinical parameter for each cancer. The robustness of the results was estimated by bootstrapping. Overall, we identify associations of potential clinical relevance among genes/micro RNAs/proteins using our statistical analysis from 25 cancer types and 18 clinical parameters that include clinical stage or smoking history. The Cancer Genome Atlas Clinical Explorer enables the cancer research community and others to explore clinically relevant associations inferred from TCGA data. With its accessible web and mobile interface, users can examine queries and test hypothesis regarding genomic/proteomic alterations across a broad spectrum of malignancies.

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.

Evolving Concepts of Asthma

PubMed Central

Ray, Anuradha; Wenzel, Sally E.

2015-01-01

Our understanding of asthma has evolved over time from a singular disease to a complex of various phenotypes, with varied natural histories, physiologies, and responses to treatment. Early therapies treated most patients with asthma similarly, with bronchodilators and corticosteroids, but these therapies had varying degrees of success. Similarly, despite initial studies that identified an underlying type 2 inflammation in the airways of patients with asthma, biologic therapies targeted toward these type 2 pathways were unsuccessful in all patients. These observations led to increased interest in phenotyping asthma. Clinical approaches, both biased and later unbiased/statistical approaches to large asthma patient cohorts, identified a variety of patient characteristics, but they also consistently identified the importance of age of onset of disease and the presence of eosinophils in determining clinically relevant phenotypes. These paralleled molecular approaches to phenotyping that developed an understanding that not all patients share a type 2 inflammatory pattern. Using biomarkers to select patients with type 2 inflammation, repeated trials of biologics directed toward type 2 cytokine pathways saw newfound success, confirming the importance of phenotyping in asthma. Further research is needed to clarify additional clinical and molecular phenotypes, validate predictive biomarkers, and identify new areas for possible interventions. PMID:26161792

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease.

PubMed

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine-based approach was proposed to identify the underlying molecular modules of PSCS complicated with IHD, which could be used for interpreting the pharmacological mechanisms of well-established Chinese herbal formulas ( e.g., Tao Hong Si Wu Tang, Dan Shen Yin, Hunag Lian Wen Dan Tang and Gua Lou Xie Bai Ban Xia Tang ). In addition, these results delivered novel understandings of the molecular network mechanisms of IHD phenotype subtypes with PSCS complications, which would be both insightful for IHD precision medicine and the integration of disease and TCM syndrome diagnoses.

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease

PubMed Central

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine-based approach was proposed to identify the underlying molecular modules of PSCS complicated with IHD, which could be used for interpreting the pharmacological mechanisms of well-established Chinese herbal formulas (e.g., Tao Hong Si Wu Tang, Dan Shen Yin, Hunag Lian Wen Dan Tang and Gua Lou Xie Bai Ban Xia Tang). In addition, these results delivered novel understandings of the molecular network mechanisms of IHD phenotype subtypes with PSCS complications, which would be both insightful for IHD precision medicine and the integration of disease and TCM syndrome diagnoses. PMID:29403392

Chronic Obstructive Pulmonary Disease: official diagnosis and treatment guidelines of the Czech Pneumological and Phthisiological Society; a novel phenotypic approach to COPD with patient-oriented care.

PubMed

Koblizek, Vladimir; Chlumsky, Jan; Zindr, Vladimir; Neumannova, Katerina; Zatloukal, Jakub; Zak, Jaroslav; Sedlak, Vratislav; Kocianova, Jana; Zatloukal, Jaromir; Hejduk, Karel; Pracharova, Sarka

2013-06-01

COPD is a global concern. Currently, several sets of guidelines, statements and strategies to managing COPD exist around the world. The Czech Pneumological and Phthisiological Society (CPPS) has commissioned an Expert group to draft recommended guidelines for the management of stable COPD. Subsequent revisions were further discussed at the National Consensus Conference (NCC). Reviewers' comments contributed to the establishment of the document's final version. The hallmark of the novel approach to COPD is the integrated evaluation of the patient's lung functions, symptoms, exacerbations and identifications of clinical phenotype(s). The CPPS defines 6 clinically relevant phenotypes: frequent exacerbator, COPD-asthma overlap, COPD-bronchiectasis overlap, emphysematic phenotype, bronchitic phenotype and pulmonary cachexia phenotype. Treatment recommendations can be divided into four steps. 1(st) step = Risk exposure elimination: reduction of smoking and environmental tobacco smoke (ETS), decrease of home and occupational exposure risks. 2(nd) step = Standard treatment: inhaled bronchodilators, regular physical activity, pulmonary rehabilitation, education, inhalation training, comorbidity treatment, vaccination. 3(rd) step = Phenotype-specific therapy: PDE4i, ICS+LABA, LVRS, BVR, AAT augmentation, physiotherapy, mucolytic, ABT. 4(th) step = Care for respiratory insufficiency and terminal COPD: LTOT, lung transplantation, high intensity-NIV and palliative care. Optimal treatment of COPD patients requires an individualised, multidisciplinary approach to the patient's symptoms, clinical phenotypes, needs and wishes. The new Czech COPD guideline reflects and covers these requirements.

Recent findings and technological advances in phosphoproteomics for cells and tissues.

PubMed

von Stechow, Louise; Francavilla, Chiara; Olsen, Jesper V

2015-01-01

Site-specific phosphorylation is a fast and reversible covalent post-translational modification that is tightly regulated in cells. The cellular machinery of enzymes that write, erase and read these modifications (kinases, phosphatases and phospho-binding proteins) is frequently deregulated in different diseases, including cancer. Large-scale studies of phosphoproteins - termed phosphoproteomics - strongly rely on the use of high-performance mass spectrometric instrumentation. This powerful technology has been applied to study a great number of phosphorylation-based phenotypes. Nevertheless, many technical and biological challenges have to be overcome to identify biologically relevant phosphorylation sites in cells and tissues. This review describes different technological strategies to identify and quantify phosphorylation sites with high accuracy, without significant loss of analysis speed and reproducibility in tissues and cells. Moreover, computational tools for analysis, integration and biological interpretation of phosphorylation events are discussed.

Systems Level Metabolic Phenotype of Methotrexate Administration in the Context of Non-alcoholic Steatohepatitis in the Rat

PubMed Central

Kyriakides, Michael; Hardwick, Rhiannon N.; Jin, Zhaosheng; Goedken, Michael J.; Holmes, Elaine; Cherrington, Nathan J.; Coen, Muireann

2014-01-01

Adverse drug reactions (ADRs) represent a significant clinical challenge with respect to patient morbidity and mortality. We investigated the hepatotoxicity and systems level metabolic phenotype of methotrexate (MTX) in the context of a prevalent liver disease; non-alcoholic steatohepatitis (NASH). A nuclear magnetic resonance spectroscopic-based metabonomic approach was employed to analyze the metabolic consequences of MTX (0, 10, 40, and 100 mg/kg) in the urine and liver of healthy rats (control diet) and in a model of NASH (methionine-choline deficient diet). Histopathological analysis confirmed baseline (0 mg/kg) liver necrosis, liver inflammation, and lipid accumulation in the NASH model. Administration of MTX (40 and 100 mg/kg) led to liver necrosis in the control cohort, whereas the NASH cohort also displayed biliary hyperplasia and liver fibrosis (100 mg/kg), providing evidence of the synergistic effect of MTX and NASH. The complementary hepatic and urinary metabolic phenotypes of the NASH model, at baseline, revealed perturbation of multiple metabolites associated with oxidative and energetic stress, and folate homeostasis. Administration of MTX in both diet cohorts showed dose-dependent metabolic consequences affecting gut microbial, energy, nucleobase, nucleoside, and folate metabolism. Furthermore, a unique panel of metabolic changes reflective of the synergistic effect of MTX and NASH was identified, including the elevation of hepatic phenylalanine, urocanate, acetate, and both urinary and hepatic formiminoglutamic acid. This systems level metabonomic analysis of the hepatotoxicity of MTX in the context of NASH provided novel mechanistic insight of potential wider clinical relevance for further understanding the role of liver pathology as a risk factor for ADRs. PMID:25145655

Eco-genetic modeling of contemporary life-history evolution.

PubMed

Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by eco-genetic models can enable and guide evolutionarily sustainable resource management.

Comorbidity of dementia with amyotrophic lateral sclerosis (ALS): insights from a large multicenter Italian cohort.

PubMed

Trojsi, Francesca; Siciliano, Mattia; Femiano, Cinzia; Santangelo, Gabriella; Lunetta, Christian; Calvo, Andrea; Moglia, Cristina; Marinou, Kalliopi; Ticozzi, Nicola; Drago Ferrante, Gianluca; Scialò, Carlo; Sorarù, Gianni; Conte, Amelia; Falzone, Yuri M; Tortelli, Rosanna; Russo, Massimo; Sansone, Valeria Ada; Chiò, Adriano; Mora, Gabriele; Poletti, Barbara; Volanti, Paolo; Caponnetto, Claudia; Querin, Giorgia; Sabatelli, Mario; Riva, Nilo; Logroscino, Giancarlo; Messina, Sonia; Fasano, Antonio; Monsurrò, Maria Rosaria; Tedeschi, Gioacchino; Mandrioli, Jessica

2017-11-01

To assess the association, at diagnosis, between amyotrophic lateral sclerosis (ALS) and dementia in a large cohort of well-characterized Italian patients. We investigated the phenotypic profile of 1638 incident patients with definite, probable or laboratory-supported probable ALS, diagnosed from January 2009 to December 2013 in 13 Italian Referral Centers, located in 10 Italian Regions, and classified in two independent subsamples accounting for presence or not of dementia. The collected ALS features, including survival and other follow-up data, were compared between the two subgroups using a one-way analysis of variance and Chi-square test, as appropriate, logistic regression models and Kaplan-Meier survival analysis. Between-subgroup comparisons showed an older age at clinical observation (p = .006), at onset and at diagnosis (p = .002) in demented versus non demented ALS patients. After adjustment for these variables, diagnosis of dementia was significantly associated with higher odds of family history of ALS (p = .001) and frontotemporal dementia (p = .003) and of bulbar onset (p = .004), and lower odds of flail leg phenotype (p = .019) and spinal onset (p = .008). The median survival time was shorter in demented versus non-demented patients, especially in case of classical, bulbar and flail limb phenotypes and both bulbar and spinal onset. Our multicenter study emphasized the importance of an early diagnosis of comorbid dementia in ALS patients, which may have clinical impact and prognostic relevance. Moreover, our results may give further inputs to validation of ALS-specific tools for the screening of cognitive impairment in clinical practice.

Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.

PubMed

Morrissey, Catherine; Grieve, Ian C; Heinig, Matthias; Atanur, Santosh; Petretto, Enrico; Pravenec, Michal; Hubner, Norbert; Aitman, Timothy J

2011-11-07

The spontaneously hypertensive rat (SHR) is a widely used rodent model of hypertension and metabolic syndrome. Previously we identified thousands of cis-regulated expression quantitative trait loci (eQTLs) across multiple tissues using a panel of rat recombinant inbred (RI) strains derived from Brown Norway and SHR progenitors. These cis-eQTLs represent potential susceptibility loci underlying physiological and pathophysiological traits manifested in SHR. We have prioritized 60 cis-eQTLs and confirmed differential expression between the parental strains by quantitative PCR in 43 (72%) of the eQTL transcripts. Quantitative trait transcript (QTT) analysis in the RI strains showed highly significant correlation between cis-eQTL transcript abundance and clinically relevant traits such as systolic blood pressure and blood glucose, with the physical location of a subset of the cis-eQTLs colocalizing with "physiological" QTLs (pQTLs) for these same traits. These colocalizing correlated cis-eQTLs (c3-eQTLs) are highly attractive as primary susceptibility loci for the colocalizing pQTLs. Furthermore, sequence analysis of the c3-eQTL genes identified single nucleotide polymorphisms (SNPs) that are predicted to affect transcription factor binding affinity, splicing and protein function. These SNPs, which potentially alter transcript abundance and stability, represent strong candidate factors underlying not just eQTL expression phenotypes, but also the correlated metabolic and physiological traits. In conclusion, by integration of genomic sequence, eQTL and QTT datasets we have identified several genes that are strong positional candidates for pathophysiological traits observed in the SHR strain. These findings provide a basis for the functional testing and ultimate elucidation of the molecular basis of these metabolic and cardiovascular phenotypes.

Genome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery.

PubMed

Kertai, Miklos D; Li, Yi-Ju; Li, Yen-Wei; Ji, Yunqi; Alexander, John; Newman, Mark F; Smith, Peter K; Joseph, Diane; Mathew, Joseph P; Podgoreanu, Mihai V

2015-05-06

Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. 107 secondary and tertiary cardiac surgery centres across the USA. We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI. 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.

Asymptotic analysis of noisy fitness maximization, applied to metabolism & growth

NASA Astrophysics Data System (ADS)

De Martino, Daniele; Masoero, Davide

2016-12-01

We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modeling. In the asymptotic regime of slow diffusion, that coincides with the relevant experimental range, the resulting non-linear Fokker-Planck equation is solved for the steady state in the WKB approximation that maps it into the ground state of a quantum particle in an Airy potential plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations and time response with respect to the distance from the maximum growth rate suggesting that suboptimal populations can have a faster response to perturbations.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Controversial constitutive TSHR activity: patients, physiology, and in vitro characterization.

PubMed

Huth, S; Jaeschke, H; Schaarschmidt, J; Paschke, R

2014-06-01

G protein-coupled receptors constitute a large family of transmembrane receptors, which activate cellular responses by signal transmission and regulation of second messenger metabolism after ligand binding. For several of these receptors it is known that they also signal ligand-independently. The G protein-coupled thyroid stimulating hormone receptor (TSHR) is characterized by a high level of constitutive activity in the wild type state. However, little is known yet concerning the physiological relevance of the constitutive wild type TSHR activity. Certainly, knowledge of the physiological relevance of constitutive wild type receptor activity is necessary to better understand thyroid physiology and it is a prerequisite for the development of better therapies for nonautoimmune hyperthyroidism and thyroid cancer. Based on a literature search regarding all published TSHR mutations, this review covers several mutations which are clearly associated with a hyperthyroidism-phenotype, but interestingly show a lack of constitutive activity determined by in vitro characterization. Possible reasons for the observed discrepancies between clinical phenotypes and in vitro characterization results for constitutive TSHR activity are reviewed. All current in vitro characterization methods for constitutive TSHR mutations are "preliminary attempts" and may well be revised by more comprehensive and even better approaches. However, a standardized approach for the determination of constitutive activity can help to identify TSHR mutations for which the investigation of additional signaling mechanisms would be most interesting to find explanations for the current clinical phenotype/in vitro discrepancies and thereby also define suitable methods to explore the physiological relevance of constitutive wild type TSHR activity. © Georg Thieme Verlag KG Stuttgart · New York.

Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.

PubMed

Newton, Katherine M; Peissig, Peggy L; Kho, Abel Ngo; Bielinski, Suzette J; Berg, Richard L; Choudhary, Vidhu; Basford, Melissa; Chute, Christopher G; Kullo, Iftikhar J; Li, Rongling; Pacheco, Jennifer A; Rasmussen, Luke V; Spangler, Leslie; Denny, Joshua C

2013-06-01

Genetic studies require precise phenotype definitions, but electronic medical record (EMR) phenotype data are recorded inconsistently and in a variety of formats. To present lessons learned about validation of EMR-based phenotypes from the Electronic Medical Records and Genomics (eMERGE) studies. The eMERGE network created and validated 13 EMR-derived phenotype algorithms. Network sites are Group Health, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University. By validating EMR-derived phenotypes we learned that: (1) multisite validation improves phenotype algorithm accuracy; (2) targets for validation should be carefully considered and defined; (3) specifying time frames for review of variables eases validation time and improves accuracy; (4) using repeated measures requires defining the relevant time period and specifying the most meaningful value to be studied; (5) patient movement in and out of the health plan (transience) can result in incomplete or fragmented data; (6) the review scope should be defined carefully; (7) particular care is required in combining EMR and research data; (8) medication data can be assessed using claims, medications dispensed, or medications prescribed; (9) algorithm development and validation work best as an iterative process; and (10) validation by content experts or structured chart review can provide accurate results. Despite the diverse structure of the five EMRs of the eMERGE sites, we developed, validated, and successfully deployed 13 electronic phenotype algorithms. Validation is a worthwhile process that not only measures phenotype performance but also strengthens phenotype algorithm definitions and enhances their inter-institutional sharing.

Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis.

PubMed

Harper, Marc; Gronenberg, Luisa; Liao, James; Lee, Christopher

2014-01-01

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome.

Gene regulatory networks and the underlying biology of developmental toxicity

EPA Science Inventory

Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

PubMed

Van Driest, Sara L; Wells, Quinn S; Stallings, Sarah; Bush, William S; Gordon, Adam; Nickerson, Deborah A; Kim, Jerry H; Crosslin, David R; Jarvik, Gail P; Carrell, David S; Ralston, James D; Larson, Eric B; Bielinski, Suzette J; Olson, Janet E; Ye, Zi; Kullo, Iftikhar J; Abul-Husn, Noura S; Scott, Stuart A; Bottinger, Erwin; Almoguera, Berta; Connolly, John; Chiavacci, Rosetta; Hakonarson, Hakon; Rasmussen-Torvik, Laura J; Pan, Vivian; Persell, Stephen D; Smith, Maureen; Chisholm, Rex L; Kitchner, Terrie E; He, Max M; Brilliant, Murray H; Wallace, John R; Doheny, Kimberly F; Shoemaker, M Benjamin; Li, Rongling; Manolio, Teri A; Callis, Thomas E; Macaya, Daniela; Williams, Marc S; Carey, David; Kapplinger, Jamie D; Ackerman, Michael J; Ritchie, Marylyn D; Denny, Joshua C; Roden, Dan M

2016-01-05

Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. One or more variants designated as pathogenic in SCN5A or KCNH2. Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms

PubMed Central

Esplin, M Sean; Manuck, Tracy A.; Varner, Michael W.; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M.; Ilekis, John

2015-01-01

Objective We sought to employ an innovative tool based on common biological pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB), in order to enhance investigators' ability to identify to highlight common mechanisms and underlying genetic factors responsible for SPTB. Study Design A secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks gestation. Each woman was assessed for the presence of underlying SPTB etiologies. A hierarchical cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis using VEGAS software. Results 1028 women with SPTB were assigned phenotypes. Hierarchical clustering of the phenotypes revealed five major clusters. Cluster 1 (N=445) was characterized by maternal stress, cluster 2 (N=294) by premature membrane rupture, cluster 3 (N=120) by familial factors, and cluster 4 (N=63) by maternal comorbidities. Cluster 5 (N=106) was multifactorial, characterized by infection (INF), decidual hemorrhage (DH) and placental dysfunction (PD). These three phenotypes were highly correlated by Chi-square analysis [PD and DH (p<2.2e-6); PD and INF (p=6.2e-10); INF and DH (p=0.0036)]. Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. Conclusion We identified 5 major clusters of SPTB based on a phenotype tool and hierarchal clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors underlying SPTB. PMID:26070700

Toward understanding of the role of reversibility of phenotypic switching in the evolution of resistance to therapy

NASA Astrophysics Data System (ADS)

Horvath, D.; Brutovsky, B.

2018-06-01

Reversibility of state transitions is intensively studied topic in many scientific disciplines over many years. In cell biology, it plays an important role in epigenetic variation of phenotypes, known as phenotypic plasticity. More interestingly, the cell state reversibility is probably crucial in the adaptation of population phenotypic heterogeneity to environmental fluctuations by evolving bet-hedging strategy, which might confer to cancer cells resistance to therapy. In this article, we propose a formalization of the evolution of highly reversible states in the environments of periodic variability. Two interrelated models of heterogeneous cell populations are proposed and their behavior is studied. The first model captures selection dynamics of the cell clones for the respective levels of phenotypic reversibility. The second model focuses on the interplay between reversibility and drug resistance in the particular case of cancer. Overall, our results show that the threshold dependencies are emergent features of the investigated model with eventual therapeutic relevance. Presented examples demonstrate importance of taking into account cell to cell heterogeneity within a system of clones with different reversibility quantified by appropriately chosen genetic and epigenetic entropy measures.

Developmental Origin of Reproductive and Metabolic Dysfunctions: Androgenic Versus Estrogenic Reprogramming

PubMed Central

Padmanabhan, Vasantha; Veiga-Lopez, Almudena

2013-01-01

Polycystic ovary syndrome (PCOS) is one of the most common fertility disorders, affecting several million women worldwide. Women with PCOS manifest neuroendocrine, ovarian, and metabolic defects. A large number of animal models have evolved to understand the etiology of PCOS. These models provide support for the contributing role of excess steroids during development in programming the PCOS phenotype. However, considerable phenotypic variability is evident across animal models, depending on the quality of the steroid administered and the perinatal time of treatment relative to the developmental trajectory of the fetus/offspring. This review focuses on the reproductive and metabolic phenotypes of the various PCOS animal models that have evolved in the last decade to delineate the relative roles of androgens and estrogens in relation to the timing of exposure in programming the various dysfunctions that are part and parcel of the PCOS phenotype. Furthermore, the review addresses the contributory role of the postnatal metabolic environment in exaggerating the severity of the phenotype, the translational relevance of the various animal models to PCOS, and areas for future research. PMID:21710394

Pleiotropic Contribution of MECOM and AVPR1A to Aggression and Subcortical Brain Volumes

PubMed Central

van Donkelaar, Marjolein M. J.; Hoogman, Martine; Pappa, Irene; Tiemeier, Henning; Buitelaar, Jan K.; Franke, Barbara; Bralten, Janita

2018-01-01

Reactive and proactive subtypes of aggression have been recognized to help parse etiological heterogeneity of this complex phenotype. With a heritability of about 50%, genetic factors play a role in the development of aggressive behavior. Imaging studies implicate brain structures related to social behavior in aggression etiology, most notably the amygdala and striatum. This study aimed to gain more insight into the pathways from genetic risk factors for aggression to aggression phenotypes. To this end, we conducted genome-wide gene-based cross-trait meta-analyses of aggression with the volumes of amygdala, nucleus accumbens and caudate nucleus to identify genes influencing both aggression and aggression-related brain volumes. We used data of large-scale genome-wide association studies (GWAS) of: (a) aggressive behavior in children and adolescents (EAGLE, N = 18,988); and (b) Magnetic Resonance Imaging (MRI)-based volume measures of aggression-relevant subcortical brain regions (ENIGMA2, N = 13,171). Second, the identified genes were further investigated in a sample of healthy adults (mean age (SD) = 25.28 (4.62) years; 43% male) who had genome-wide genotyping data and questionnaire data on aggression subtypes available (Brain Imaging Genetics, BIG, N = 501) to study their effect on reactive and proactive subtypes of aggression. Our meta-analysis identified two genes, MECOM and AVPR1A, significantly associated with both aggression risk and nucleus accumbens (MECOM) and amygdala (AVPR1A) brain volume. Subsequent in-depth analysis of these genes in healthy adults (BIG), including sex as an interaction term in the model, revealed no significant subtype-specific gene-wide associations. Using cross-trait meta-analysis of brain measures and psychiatric phenotypes, this study generated new hypotheses about specific links between genes, the brain and behavior. Results indicate that MECOM and AVPR1A may exert an effect on aggression through mechanisms involving nucleus accumbens and amygdala volumes, respectively. PMID:29666571

Characterization of Rheumatoid Arthritis Subtypes Using Symptom Profiles, Clinical Chemistry and Metabolomics Measurements

PubMed Central

van der Kooij, Anita J.; Reijmers, Theo H.; Schroën, Yan; Wang, Mei; Xu, Zhiliang; Wang, Xinchang; Kong, Hongwei; Xu, Guowang; Hankemeier, Thomas; Meulman, Jacqueline J.; van der Greef, Jan

2012-01-01

Objective The aim is to characterize subgroups or phenotypes of rheumatoid arthritis (RA) patients using a systems biology approach. The discovery of subtypes of rheumatoid arthritis patients is an essential research area for the improvement of response to therapy and the development of personalized medicine strategies. Methods In this study, 39 RA patients are phenotyped using clinical chemistry measurements, urine and plasma metabolomics analysis and symptom profiles. In addition, a Chinese medicine expert classified each RA patient as a Cold or Heat type according to Chinese medicine theory. Multivariate data analysis techniques are employed to detect and validate biochemical and symptom relationships with the classification. Results The questionnaire items ‘Red joints’, ‘Swollen joints’, ‘Warm joints’ suggest differences in the level of inflammation between the groups although c-reactive protein (CRP) and rheumatoid factor (RHF) levels were equal. Multivariate analysis of the urine metabolomics data revealed that the levels of 11 acylcarnitines were lower in the Cold RA than in the Heat RA patients, suggesting differences in muscle breakdown. Additionally, higher dehydroepiandrosterone sulfate (DHEAS) levels in Heat patients compared to Cold patients were found suggesting that the Cold RA group has a more suppressed hypothalamic-pituitary-adrenal (HPA) axis function. Conclusion Significant and relevant biochemical differences are found between Cold and Heat RA patients. Differences in immune function, HPA axis involvement and muscle breakdown point towards opportunities to tailor disease management strategies to each of the subgroups RA patient. PMID:22984493

Drought tolerance in cacao is mediated by root phenotypic plasticity

USDA-ARS?s Scientific Manuscript database

This study aimed to evaluate phenotypic relationships and their direct and indirect effects through path analysis, and evaluate the use of the phenotypic plasticity index as criteria for the estimation of the basic and explanatory variables used to analysis several cacao progenies subjected to soil ...

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

PubMed

Katsageorgiou, Vasiliki-Maria; Sona, Diego; Zanotto, Matteo; Lassi, Glenda; Garcia-Garcia, Celina; Tucci, Valter; Murino, Vittorio

2018-05-01

Sleep science is entering a new era, thanks to new data-driven analysis approaches that, combined with mouse gene-editing technologies, show a promise in functional genomics and translational research. However, the investigation of sleep is time consuming and not suitable for large-scale phenotypic datasets, mainly due to the need for subjective manual annotations of electrophysiological states. Moreover, the heterogeneous nature of sleep, with all its physiological aspects, is not fully accounted for by the current system of sleep stage classification. In this study, we present a new data-driven analysis approach offering a plethora of novel features for the characterization of sleep. This novel approach allowed for identifying several substages of sleep that were hidden to standard analysis. For each of these substages, we report an independent set of homeostatic responses following sleep deprivation. By using our new substages classification, we have identified novel differences among various genetic backgrounds. Moreover, in a specific experiment with the Zfhx3 mouse line, a recent circadian mutant expressing both shortening of the circadian period and abnormal sleep architecture, we identified specific sleep states that account for genotypic differences at specific times of the day. These results add a further level of interaction between circadian clock and sleep homeostasis and indicate that dissecting sleep in multiple states is physiologically relevant and can lead to the discovery of new links between sleep phenotypes and genetic determinants. Therefore, our approach has the potential to significantly enhance the understanding of sleep physiology through the study of single mutations. Moreover, this study paves the way to systematic high-throughput analyses of sleep.

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping1[C][W][OPEN

PubMed Central

Klukas, Christian; Chen, Dijun; Pape, Jean-Michel

2014-01-01

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable. PMID:24760818

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Interclonal proteomic responses to predator exposure in Daphnia magna may depend on predator composition of habitats.

PubMed

Otte, Kathrin A; Schrank, Isabella; Fröhlich, Thomas; Arnold, Georg J; Laforsch, Christian

2015-08-01

Phenotypic plasticity, the ability of one genotype to express different phenotypes in response to changing environmental conditions, is one of the most common phenomena characterizing the living world and is not only relevant for the ecology but also for the evolution of species. Daphnia, the water flea, is a textbook example for predator-induced phenotypic plastic defences; however, the analysis of molecular mechanisms underlying these inducible defences is still in its early stages. We exposed Daphnia magna to chemical cues of the predator Triops cancriformis to identify key processes underlying plastic defensive trait formation. To get a more comprehensive idea of this phenomenon, we studied four genotypes with five biological replicates each, originating from habitats characterized by different predator composition, ranging from predator-free habitats to habitats containing T. cancriformis. We analysed the morphologies as well as proteomes of predator-exposed and control animals. Three genotypes showed morphological changes when the predator was present. Using a high-throughput proteomics approach, we found 294 proteins which were significantly altered in their abundance after predator exposure in a general or genotype-dependent manner. Proteins connected to genotype-dependent responses were related to the cuticle, protein synthesis and calcium binding, whereas the yolk protein vitellogenin increased in abundance in all genotypes, indicating their involvement in a more general response. Furthermore, genotype-dependent responses at the proteome level were most distinct for the only genotype that shares its habitat with Triops. Altogether, our study provides new insights concerning genotype-dependent and general molecular processes involved in predator-induced phenotypic plasticity in D. magna. © 2015 John Wiley & Sons Ltd.

Rasd2 Modulates Prefronto-Striatal Phenotypes in Humans and ‘Schizophrenia-Like Behaviors' in Mice

PubMed Central

Vitucci, Daniela; Di Giorgio, Annabella; Napolitano, Francesco; Pelosi, Barbara; Blasi, Giuseppe; Errico, Francesco; Attrotto, Maria Teresa; Gelao, Barbara; Fazio, Leonardo; Taurisano, Paolo; Di Maio, Anna; Marsili, Valentina; Pasqualetti, Massimo; Bertolino, Alessandro; Usiello, Alessandro

2016-01-01

Rasd2 is a thyroid hormone target gene, which encodes for a GTP-binding protein enriched in the striatum where, among other functions, it modulates dopaminergic neurotransmission. Here we report that human RASD2 mRNA is abundant in putamen, but it also occurs in the cerebral cortex, with a distinctive expression pattern that differs from that present in rodents. Consistent with its localization, we found that a genetic variation in RASD2 (rs6518956) affects postmortem prefrontal mRNA expression in healthy humans and is associated with phenotypes of relevance to schizophrenia, including prefrontal and striatal grey matter volume and physiology during working memory, as measured with magnetic resonance imaging. Interestingly, quantitative real-time PCR analysis indicated that RASD2 mRNA is slightly reduced in postmortem prefrontal cortex of patients with schizophrenia. In the attempt to uncover the neurobiological substrates associated with Rasd2 activity, we used knockout mice to analyze the in vivo influence of this G-protein on the prepulse inhibition of the startle response and psychotomimetic drug-related behavioral response. Data showed that Rasd2 mutants display deficits in basal prepulse inhibition that, in turn, exacerbate gating disruption under psychotomimetic drug challenge. Furthermore, we documented that lack of Rasd2 strikingly enhances the behavioral sensitivity to motor stimulation elicited by amphetamine and phencyclidine. Based on animal model data, along with the finding that RASD2 influences prefronto-striatal phenotypes in healthy humans, we suggest that genetic mutation or reduced levels of this G-protein might have a role in cerebral circuitry dysfunction underpinning exaggerated psychotomimetic drugs responses and development of specific biological phenotypes linked to schizophrenia. PMID:26228524

Rasd2 Modulates Prefronto-Striatal Phenotypes in Humans and 'Schizophrenia-Like Behaviors' in Mice.

PubMed

Vitucci, Daniela; Di Giorgio, Annabella; Napolitano, Francesco; Pelosi, Barbara; Blasi, Giuseppe; Errico, Francesco; Attrotto, Maria Teresa; Gelao, Barbara; Fazio, Leonardo; Taurisano, Paolo; Di Maio, Anna; Marsili, Valentina; Pasqualetti, Massimo; Bertolino, Alessandro; Usiello, Alessandro

2016-02-01

Rasd2 is a thyroid hormone target gene, which encodes for a GTP-binding protein enriched in the striatum where, among other functions, it modulates dopaminergic neurotransmission. Here we report that human RASD2 mRNA is abundant in putamen, but it also occurs in the cerebral cortex, with a distinctive expression pattern that differs from that present in rodents. Consistent with its localization, we found that a genetic variation in RASD2 (rs6518956) affects postmortem prefrontal mRNA expression in healthy humans and is associated with phenotypes of relevance to schizophrenia, including prefrontal and striatal grey matter volume and physiology during working memory, as measured with magnetic resonance imaging. Interestingly, quantitative real-time PCR analysis indicated that RASD2 mRNA is slightly reduced in postmortem prefrontal cortex of patients with schizophrenia. In the attempt to uncover the neurobiological substrates associated with Rasd2 activity, we used knockout mice to analyze the in vivo influence of this G-protein on the prepulse inhibition of the startle response and psychotomimetic drug-related behavioral response. Data showed that Rasd2 mutants display deficits in basal prepulse inhibition that, in turn, exacerbate gating disruption under psychotomimetic drug challenge. Furthermore, we documented that lack of Rasd2 strikingly enhances the behavioral sensitivity to motor stimulation elicited by amphetamine and phencyclidine. Based on animal model data, along with the finding that RASD2 influences prefronto-striatal phenotypes in healthy humans, we suggest that genetic mutation or reduced levels of this G-protein might have a role in cerebral circuitry dysfunction underpinning exaggerated psychotomimetic drugs responses and development of specific biological phenotypes linked to schizophrenia.

Home-cage anxiety levels in a transgenic rat model for Spinocerebellar ataxia type 17 measured by an approach-avoidance task: The light spot test.

PubMed

Kyriakou, Elisavet I; Nguyen, Huu Phuc; Homberg, Judith R; Van der Harst, Johanneke E

2018-04-15

Measuring anxiety in a reliable manner is essential for behavioural phenotyping of rodent models such as the rat model for Spinocerebellar ataxia type 17 (SCA17) where anxiety is reported in patients. An automated tool for assessing anxiety within the home cage can minimize human intervention, stress of handling, transportation and novelty. We applied the anxiety test "light spot" (LS) (white led directed at the food-hopper) to our transgenic SCA17 rat model in the PhenoTyper 4500 ® to extend the knowledge of this automated tool for behavioural phenotyping and to verify an anxiety-like phenotype at three different disease stages for use in future therapeutic studies. Locomotor activity was increased in SCA17 rats at 6 and 9 months during the first 15min of the LS, potentially reflecting increased risk assessment. Both genotypes responded to the test with lower duration in the LS zone and higher time spent inside the shelter compared to baseline. We present the first data of a rat model subjected to the LS. The LS can be considered more biologically relevant than a traditional test as it measures anxiety in a familiar situation. The LS successfully evoked avoidance and shelter-seeking in rats. SCA17 rats showed a stronger approach-avoidance conflict reflected by increased activity in the area outside the LS. This home cage test, continuously monitoring pre- and post-effects, provides the opportunity for in-depth analysis, making it a potentially useful tool for detecting subtle or complex anxiety-related traits in rodents. Copyright © 2017 Elsevier B.V. All rights reserved.

Genome-wide analysis of allele frequency change in sunflower crop-wild hybrid populations evolving under natural conditions.

PubMed

Corbi, Jonathan; Baack, Eric J; Dechaine, Jennifer M; Seiler, Gerald; Burke, John M

2018-01-01

Crop-wild hybridization occurs in numerous plant species and could alter the genetic structure and evolutionary dynamics of wild populations. Studying crop-derived alleles in wild populations is also relevant to assessing/mitigating the risks associated with transgene escape. To date, crop-wild hybridization has generally been examined via short-term studies, typically within a single generation, focusing on few traits or genetic markers. Little is known about patterns of selection on crop-derived alleles over multiple generations, particularly at a genome-wide scale. Here, we documented patterns of natural selection in an experimental crop × wild sunflower population that was allowed to evolve under natural conditions for two generations at two locations. Allele frequencies at a genome-wide collection of SNPs were tracked across generations, and a common garden experiment was conducted to compare trait means between generations. These data allowed us to identify instances of selection on crop-derived alleles/traits and, in concert with QTL mapping results, test for congruence between our genotypic and phenotypic results. We found that natural selection overwhelmingly favours wild alleles and phenotypes. However, crop alleles in certain genomic regions can be favoured, and these changes often occurred in parallel across locations. We did not, however, consistently observe close agreement between our genotypic and phenotypic results. For example, when a trait evolved towards the wild phenotype, wild QTL alleles associated with that trait did not consistently increase in frequency. We discuss these results in the context of crop allele introgression into wild populations and implications for the management of GM crops. © 2017 John Wiley & Sons Ltd.

[Inflammatory bowel diseases: an immunological approach].

PubMed

Sepúlveda, Sofía E; Beltrán, Caroll J; Peralta, Alexis; Rivas, Paola; Rojas, Néstor; Figueroa, Carolina; Quera, Rodrigo; Hermoso, Marcela A

2008-03-01

Inflammatory bowel diseases (IBD) are inflammatory diseases with a multifactorial component that involve the intestinal tract. The two relevant IBD syndromes are Crohn's disease (CD) and ulcerative colitis (UC). One factor involved in IBD development is a genetic predisposition, associated to NOD2/CARD15 and Toll-like receptor 4 (TLR4) polymorphisms that might favor infectious enterocolitis that is possibly associated to the development of IBD. The identification of specific immunologic alterations in IBD and their relationship to the etiology of the disease is a relevant research topic. The role of intra and extracellular molecules, such as transcription factors and cytokines that are involved in the inflammatory response, needs to be understood. The relevance of immunologic molecules that might drive the immune response to a T helper (Th) 1, Th 2 or the recently described Th 17 phenotype, has been demonstrated in animal models and clinical studies with IBD patients. CD and UC predominantly behave with a Th 1 and Th 2 immune phenotype, respectively. Recently, an association between CD and Th 17 has been reported. The knowledge acquired from immunologic and molecular research will help to develop accurate diagnostic methods and efficient therapies.

Molecular epidemiology of Pseudomonas aeruginosa.

PubMed

Speert, David P

2002-10-01

Pseudomonas aeruginosa is a serious opportunistic pathogen in certain compromised hosts, such as those with cystic fibrosis, thermal burns and cancer. It also causes less severe noninvasive disease, such as otitis externa and hot tub folliculitis, in normal hosts. P. aeruginosa is phenotypically very unstable, particularly in patients with chronic infection. Phenotypic typing techniques are useful for understanding the epidemiology of acute infections, but they are limited by their discriminatory power and by their inability to group isolates that are phenotypically unrelated but genetically homologous. Molecular typing techniques, developed over the past decade, are highly discriminatory and are useful for typing strains from patients with chronic infection where the bacterial phenotype is unstable; this is particularly true in cystic fibrosis, where patients often are infected with the same strain for several decades, but the bacteria undergo phenotypic alteration. Molecular typing techniques, which have proven useful in typing P. aeruginosa for epidemiological purposes, include pulsed field gel electrophoresis, restriction fragment length polymorphic DNA analysis, random amplified polymorphic DNA analysis, repetitive extrapalindromic PCR analysis, and multilocus sequence typing. These methods are generally only available in specialized laboratories, but they should be used when data from phenotypic typing analysis are ambiguous or when phenotypic methods are unreliable, such as in cystic fibrosis.

Nematode orphan genes are adopted by conserved regulatory networks and find a home in ecology.

PubMed

Mayer, Melanie G; Sommer, Ralf J

2015-01-01

Nematode dauer formation represents an essential survival and dispersal strategy and is one of a few ecologically relevant traits that can be studied in laboratory approaches. Under harsh environmental conditions, the nematode model organisms Caenorhabditis elegans and Pristionchus pacificus arrest their development and induce the formation of stress-resistant dauer larvae in response to dauer pheromones, representing a key example of phenotypic plasticity. Previous studies have indicated that in P. pacificus, many wild isolates show cross-preference of dauer pheromones and compete for access to a limited food source. When investigating the genetic mechanisms underlying this intraspecific competition, we recently discovered that the orphan gene dauerless (dau-1) controls dauer formation by copy number variation. Our results show that dau-1 acts in parallel to or downstream of steroid hormone signaling but upstream of the nuclear hormone receptor daf-12, suggesting that DAU-1 represents a novel inhibitor of DAF-12. Phylogenetic analysis reveals that the observed copy number variation is part of a complex series of gene duplication events that occurred over short evolutionary time scales. Here, we comment on the incorporation of novel or fast-evolving genes into conserved genetic networks as a common principle for the evolution of phenotypic plasticity and intraspecific competition. We discuss the possibility that orphan genes might often function in the regulation and execution of ecologically relevant traits. Given that only few ecological processes can be studied in model organisms, the function of such genes might often go unnoticed, explaining the large number of uncharacterized genes in model system genomes.

Combining Comprehensive Analysis of Off-Site Lambda Phage Integration with a CRISPR-Based Means of Characterizing Downstream Physiology.

PubMed

Tanouchi, Yu; Covert, Markus W

2017-09-19

During its lysogenic life cycle, the phage genome is integrated into the host chromosome by site-specific recombination. In this report, we analyze lambda phage integration into noncanonical sites using next-generation sequencing and show that it generates significant genetic diversity by targeting over 300 unique sites in the host Escherichia coli genome. Moreover, these integration events can have important phenotypic consequences for the host, including changes in cell motility and increased antibiotic resistance. Importantly, the new technologies that we developed to enable this study-sequencing secondary sites using next-generation sequencing and then selecting relevant lysogens using clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-based selection-are broadly applicable to other phage-bacterium systems. IMPORTANCE Bacteriophages play an important role in bacterial evolution through lysogeny, where the phage genome is integrated into the host chromosome. While phage integration generally occurs at a specific site in the host chromosome, it is also known to occur at other, so-called secondary sites. In this study, we developed a new experimental technology to comprehensively study secondary integration sites and discovered that phage can integrate into over 300 unique sites in the host genome, resulting in significant genetic diversity in bacteria. We further developed an assay to examine the phenotypic consequence of such diverse integration events and found that phage integration can cause changes in evolutionarily relevant traits such as bacterial motility and increases in antibiotic resistance. Importantly, our method is readily applicable to other phage-bacterium systems. Copyright © 2017 Tanouchi and Covert.

Defining Phenotypes in Diabetic Nephropathy: a novel approach using a cross-sectional analysis of a single centre cohort.

PubMed

Montero, Rosa M; Herath, Athula; Qureshi, Ashfaq; Esfandiari, Ehsanollah; Pusey, Charles D; Frankel, Andrew H; Tam, Frederick W K

2018-01-08

The global increase in Diabetes Mellitus (DM) has led to an increase in DM-Chronic Kidney Disease (DM-CKD). In this cross-sectional observational study we aimed to define phenotypes for patients with DM-CKD that in future may be used to individualise treatment We report 4 DM-CKD phenotypes in 220 patients recruited from Imperial College NHS Trust clinics from 2004-2012. A robust principal component analysis (PCA) was used to statistically determine clusters with phenotypically different patients. 163 patients with complete data sets were analysed: 77 with CKD and 86 with DM-CKD. Four different clusters were identified. Phenotypes 1 and 2 are entirely composed of patients with DM-CKD and phenotypes 3 and 4 are predominantly CKD (non-DM-CKD). Phenotype 1 depicts a cardiovascular phenotype; phenotype 2: microvascular complications with advanced DM-CKD; phenotype 3: advanced CKD with less anaemia, lower weight and HbA1c; phenotype 4: hypercholesteraemic, younger, less severe CKD. We are the first group to describe different phenotypes in DM-CKD using a PCA approach. Identification of phenotypic groups illustrates the differences and similarities that occur under the umbrella term of DM-CKD providing an opportunity to study phenotypes within these groups thereby facilitating development of precision/personalised targeted medicine.

Patient-reported outcomes in a large community-based pain medicine practice: evaluation for use in phenotype modeling.

PubMed

Juckett, David A; Davis, Fred N; Gostine, Mark; Reed, Philip; Risko, Rebecca

2015-05-28

An academic, community medicine partnership was established to build a phenotype-to-outcome model targeting chronic pain. This model will be used to drive clinical decision support for pain medicine in the community setting. The first step in this effort is an examination of the electronic health records (EHR) from clinics that treat chronic pain. The biopsychosocial components provided by both patients and care providers must be of sufficient scope to populate the spectrum of patient types, treatment modalities, and possible outcomes. The patient health records from a large Midwest pain medicine practice (Michigan Pain Consultants, PC) contains physician notes, administrative codes, and patient-reported outcomes (PRO) on over 30,000 patients during the study period spanning 2010 to mid-2014. The PRO consists of a regularly administered Pain Health Assessment (PHA), a biopsychosocial, demographic, and symptomology questionnaire containing 163 items, which is completed approximately every six months with a compliance rate of over 95%. The biopsychosocial items (74 items with Likert scales of 0-10) were examined by exploratory factor analysis and descriptive statistics to determine the number of independent constructs available for phenotypes and outcomes. Pain outcomes were examined both in the aggregate and the mean of longitudinal changes in each patient. Exploratory factor analysis of the intake PHA revealed 15 orthogonal factors representing pain levels; physical, social, and emotional functions; the effects of pain on these functions; vitality and health; and measures of outcomes and satisfaction. Seven items were independent of the factors, offering unique information. As an exemplar of outcomes from the follow-up PHAs, patients reported approximately 60% relief in their pain. When examined in the aggregate, patients showed both a decrease in pain levels and an increase in coping skills with an increased number of visits. When examined individually, 80-85% of patients presenting with the highest pain levels reported improvement by approximately two points on an 11-point pain scale. We conclude that the data available in a community practice can be a rich source of biopsychosocial information relevant to the phenotypes of chronic pain. It is anticipated that phenotype linkages to best treatments and outcomes can be constructed from this set of records.

Monocyte Activation in Immunopathology: Cellular Test for Development of Diagnostics and Therapy.

PubMed

Ivanova, Ekaterina A; Orekhov, Alexander N

2016-01-01

Several highly prevalent human diseases are associated with immunopathology. Alterations in the immune system are found in such life-threatening disorders as cancer and atherosclerosis. Monocyte activation followed by macrophage polarization is an important step in normal immune response to pathogens and other relevant stimuli. Depending on the nature of the activation signal, macrophages can acquire pro- or anti-inflammatory phenotypes that are characterized by the expression of distinct patterns of secreted cytokines and surface antigens. This process is disturbed in immunopathologies resulting in abnormal monocyte activation and/or bias of macrophage polarization towards one or the other phenotype. Such alterations could be used as important diagnostic markers and also as possible targets for the development of immunomodulating therapy. Recently developed cellular tests are designed to analyze the phenotype and activity of living cells circulating in patient's bloodstream. Monocyte/macrophage activation test is a successful example of cellular test relevant for atherosclerosis and oncopathology. This test demonstrated changes in macrophage activation in subclinical atherosclerosis and breast cancer and could also be used for screening a panel of natural agents with immunomodulatory activity. Further development of cellular tests will allow broadening the scope of their clinical implication. Such tests may become useful tools for drug research and therapy optimization.

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.

Modulation of gut microbiota during probiotic-mediated attenuation of metabolic syndrome in high fat diet-fed mice

PubMed Central

Wang, Jingjing; Tang, Huang; Zhang, Chenhong; Zhao, Yufeng; Derrien, Muriel; Rocher, Emilie; van-Hylckama Vlieg, Johan ET; Strissel, Katherine; Zhao, Liping; Obin, Martin; Shen, Jian

2015-01-01

Structural disruption of gut microbiota and associated inflammation are considered important etiological factors in high fat diet (HFD)-induced metabolic syndrome (MS). Three candidate probiotic strains, Lactobacillus paracasei CNCM I-4270 (LC), L. rhamnosus I-3690 (LR) and Bifidobacterium animalis subsp. lactis I-2494 (BA), were individually administered to HFD-fed mice (108 cells day−1) for 12 weeks. Each strain attenuated weight gain and macrophage infiltration into epididymal adipose tissue and markedly improved glucose–insulin homeostasis and hepatic steatosis. Weighted UniFrac principal coordinate analysis based on 454 pyrosequencing of fecal bacterial 16S rRNA genes showed that the probiotic strains shifted the overall structure of the HFD-disrupted gut microbiota toward that of lean mice fed a normal (chow) diet. Redundancy analysis revealed that abundances of 83 operational taxonomic units (OTUs) were altered by probiotics. Forty-nine altered OTUs were significantly correlated with one or more host MS parameters and were designated ‘functionally relevant phylotypes'. Thirteen of the 15 functionally relevant OTUs that were negatively correlated with MS phenotypes were promoted, and 26 of the 34 functionally relevant OTUs that were positively correlated with MS were reduced by at least one of the probiotics, but each strain changed a distinct set of functionally relevant OTUs. LC and LR increased cecal acetate but did not affect circulating lipopolysaccharide-binding protein; in contrast, BA did not increase acetate but significantly decreased adipose and hepatic tumor necrosis factor-α gene expression. These results suggest that Lactobacillus and Bifidobacterium differentially attenuate obesity comorbidities in part through strain-specific impacts on MS-associated phylotypes of gut microbiota in mice. PMID:24936764

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

PubMed

Rahaman, Md Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

Brief Report: Autism-like Traits are Associated With Enhanced Ability to Disembed Visual Forms.

PubMed

Sabatino DiCriscio, Antoinette; Troiani, Vanessa

2017-05-01

Atypical visual perceptual skills are thought to underlie unusual visual attention in autism spectrum disorders. We assessed whether individual differences in visual processing skills scaled with quantitative traits associated with the broader autism phenotype (BAP). Visual perception was assessed using the Figure-ground subtest of the Test of visual perceptual skills-3rd Edition (TVPS). In a large adult cohort (n = 209), TVPS-Figure Ground scores were positively correlated with autistic-like social features as assessed by the Broader autism phenotype questionnaire. This relationship was gender-specific, with males showing a correspondence between visual perceptual skills and autistic-like traits. This work supports the link between atypical visual perception and autism and highlights the importance in characterizing meaningful individual differences in clinically relevant behavioral phenotypes.

Text-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients.

PubMed

Saklatvala, Jake R; Dand, Nick; Simpson, Michael A

2018-05-01

The genetic diagnosis of rare monogenic diseases using exome/genome sequencing requires the true causal variant(s) to be identified from tens of thousands of observed variants. Typically a virtual gene panel approach is taken whereby only variants in genes known to cause phenotypes resembling the patient under investigation are considered. With the number of known monogenic gene-disease pairs exceeding 5,000, manual curation of personalized virtual panels using exhaustive knowledge of the genetic basis of the human monogenic phenotypic spectrum is challenging. We present improved probabilistic methods for estimating phenotypic similarity based on Human Phenotype Ontology annotation. A limitation of existing methods for evaluating a disease's similarity to a reference set is that reference diseases are typically represented as a series of binary (present/absent) observations of phenotypic terms. We evaluate a quantified disease reference set, using term frequency in phenotypic text descriptions to approximate term relevance. We demonstrate an improved ability to identify related diseases through the use of a quantified reference set, and that vector space similarity measures perform better than established information content-based measures. These improvements enable the generation of bespoke virtual gene panels, facilitating more accurate and efficient interpretation of genomic variant profiles from individuals with rare Mendelian disorders. These methods are available online at https://atlas.genetics.kcl.ac.uk/~jake/cgi-bin/patient_sim.py. © 2018 Wiley Periodicals, Inc.

Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

PubMed

Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

2015-09-01

We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P < 2.2e-6; PD and INF, P = 6.2e-10; INF and DH, (P = .0036). Gene-based testing identified the INS (insulin) gene as significantly associated with cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

PARP inhibition causes premature loss of cohesion in cancer cells

PubMed Central

Kukolj, Eva; Kaufmann, Tanja; Dick, Amalie E.; Zeillinger, Robert; Gerlich, Daniel W.; Slade, Dea

2017-01-01

Poly(ADP-ribose) polymerases (PARPs) regulate various aspects of cellular function including mitotic progression. Although PARP inhibitors have been undergoing various clinical trials and the PARP1/2 inhibitor olaparib was approved as monotherapy for BRCA-mutated ovarian cancer, their mode of action in killing tumour cells is not fully understood. We investigated the effect of PARP inhibition on mitosis in cancerous (cervical, ovary, breast and osteosarcoma) and non-cancerous cells by live-cell imaging. The clinically relevant inhibitor olaparib induced strong perturbations in mitosis, including problems with chromosome alignment at the metaphase plate, anaphase delay, and premature loss of cohesion (cohesion fatigue) after a prolonged metaphase arrest, resulting in sister chromatid scattering. PARP1 and PARP2 depletion suppressed the phenotype while PARP2 overexpression enhanced it, suggesting that olaparib-bound PARP1 and PARP2 rather than the lack of catalytic activity causes this phenotype. Olaparib-induced mitotic chromatid scattering was observed in various cancer cell lines with increased protein levels of PARP1 and PARP2, but not in non-cancer or cancer cell lines that expressed lower levels of PARP1 or PARP2. Interestingly, the sister chromatid scattering phenotype occurred only when olaparib was added during the S-phase preceding mitosis, suggesting that PARP1 and PARP2 entrapment at replication forks impairs sister chromatid cohesion. Clinically relevant DNA-damaging agents that impair replication progression such as topoisomerase inhibitors and cisplatin were also found to induce sister chromatid scattering and metaphase plate alignment problems, suggesting that these mitotic phenotypes are a common outcome of replication perturbation. PMID:29262611

Mice with reduced NMDA receptor expression: more consistent with autism than schizophrenia?

PubMed

Gandal, M J; Anderson, R L; Billingslea, E N; Carlson, G C; Roberts, T P L; Siegel, S J

2012-08-01

Reduced NMDA-receptor (NMDAR) function has been implicated in the pathophysiology of neuropsychiatric disease, most strongly in schizophrenia but also recently in autism spectrum disorders (ASD). To determine the direct contribution of NMDAR dysfunction to disease phenotypes, a mouse model with constitutively reduced expression of the obligatory NR1 subunit has been developed and extensively investigated. Adult NR1(neo-/-) mice show multiple abnormal behaviors, including reduced social interactions, locomotor hyperactivity, self-injury, deficits in prepulse inhibition (PPI) and sensory hypersensitivity, among others. Whereas such phenotypes have largely been interpreted in the context of schizophrenia, these behavioral abnormalities are rather non-specific and are frequently present across models of diseases characterized by negative symptom domains. This study investigated auditory electrophysiological and behavioral paradigms relevant to autism, to determine whether NMDAR hypofunction may be more consistent with adult ASD-like phenotypes. Indeed, transgenic mice showed behavioral deficits relevant to all core ASD symptoms, including decreased social interactions, altered ultrasonic vocalizations and increased repetitive behaviors. NMDAR disruption recapitulated clinical endophenotypes including reduced PPI, auditory-evoked response N1 latency delay and reduced gamma synchrony. Auditory electrophysiological abnormalities more closely resembled those seen in clinical studies of autism than schizophrenia. These results suggest that NMDAR hypofunction may be associated with a continuum of neuropsychiatric diseases, including schizophrenia and autism. Neural synchrony abnormalities suggest an imbalance of glutamatergic and GABAergic coupling and may provide a target, along with behavioral phenotypes, for preclinical screening of novel therapeutics. © 2012 The Authors. Genes, Brain and Behavior © 2012 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

SNPs selection using support vector regression and genetic algorithms in GWAS

PubMed Central

2014-01-01

Introduction This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. Results The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. Conclusions The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels. PMID:25573332

Next Generation Image-Based Phenotyping of Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Shaw, N. M.; Cheng, H.; Larson, B. G.; Craft, E. J.; Shaff, J. E.; Schneider, D. J.; Piñeros, M. A.; Kochian, L. V.

2016-12-01

The development of the Plant Root Imaging and Data Acquisition (PRIDA) hardware/software system enables researchers to collect digital images, along with all the relevant experimental details, of a range of hydroponically grown agricultural crop roots for 2D and 3D trait analysis. Previous efforts of image-based root phenotyping focused on young cereals, such as rice; however, there is a growing need to measure both older and larger root systems, such as those of maize and sorghum, to improve our understanding of the underlying genetics that control favorable rooting traits for plant breeding programs to combat the agricultural risks presented by climate change. Therefore, a larger imaging apparatus has been prototyped for capturing 3D root architecture with an adaptive control system and innovative plant root growth media that retains three-dimensional root architectural features. New publicly available multi-platform software has been released with considerations for both high throughput (e.g., 3D imaging of a single root system in under ten minutes) and high portability (e.g., support for the Raspberry Pi computer). The software features unified data collection, management, exploration and preservation for continued trait and genetics analysis of root system architecture. The new system makes data acquisition efficient and includes features that address the needs of researchers and technicians, such as reduced imaging time, semi-automated camera calibration with uncertainty characterization, and safe storage of the critical experimental data.

Structural and genetic analysis of a mutant of Rhodobacter sphaeroides WS8 deficient in hook length control.

PubMed Central

González-Pedrajo, B; Ballado, T; Campos, A; Sockett, R E; Camarena, L; Dreyfus, G

1997-01-01

Motility in the photosynthetic bacterium Rhodobacter sphaeroides is achieved by the unidirectional rotation of a single subpolar flagellum. In this study, transposon mutagenesis was used to obtain nonmotile flagellar mutants from this bacterium. We report here the isolation and characterization of a mutant that shows a polyhook phenotype. Morphological characterization of the mutant was done by electron microscopy. Polyhooks were obtained by shearing and were used to purify the hook protein monomer (FlgE). The apparent molecular mass of the hook protein was 50 kDa. N-terminal amino acid sequencing and comparisons with the hook proteins of other flagellated bacteria indicated that the Rhodobacter hook protein has consensus sequences common to axial flagellar components. A 25-kb fragment from an R. sphaeroides WS8 cosmid library restored wild-type flagellation and motility to the mutant. Using DNA adjacent to the inserted transposon as a probe, we identified a 4.6-kb SalI restriction fragment that contained the gene responsible for the polyhook phenotype. Nucleotide sequence analysis of this region revealed an open reading frame with a deduced amino acid sequence that was 23.4% identical to that of FliK of Salmonella typhimurium, the polypeptide responsible for hook length control in that enteric bacterium. The relevance of a gene homologous to fliK in the uniflagellated bacterium R. sphaeroides is discussed. PMID:9352903

Developmental Connectivity and Molecular Phenotypes of Unique Cortical Projection Neurons that Express a Synapse-Associated Receptor Tyrosine Kinase.

PubMed

Kast, Ryan J; Wu, Hsiao-Huei; Levitt, Pat

2017-11-28

The complex circuitry and cell-type diversity of the cerebral cortex are required for its high-level functions. The mechanisms underlying the diversification of cortical neurons during prenatal development have received substantial attention, but understanding of neuronal heterogeneity is more limited during later periods of cortical circuit maturation. To address this knowledge gap, connectivity analysis and molecular phenotyping of cortical neuron subtypes that express the developing synapse-enriched MET receptor tyrosine kinase were performed. Experiments used a MetGFP transgenic mouse line, combined with coexpression analysis of class-specific molecular markers and retrograde connectivity mapping. The results reveal that MET is expressed by a minor subset of subcerebral and a larger number of intratelencephalic projection neurons. Remarkably, MET is excluded from most layer 6 corticothalamic neurons. These findings are particularly relevant for understanding the maturation of discrete cortical circuits, given converging evidence that MET influences dendritic elaboration and glutamatergic synapse maturation. The data suggest that classically defined cortical projection classes can be further subdivided based on molecular characteristics that likely influence synaptic maturation and circuit wiring. Additionally, given that MET is classified as a high confidence autism risk gene, the data suggest that projection neuron subpopulations may be differentially vulnerable to disorder-associated genetic variation. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

Cruz, Jeffrey A.; Savage, Linda J.; Zegarac, Robert; ...

2016-06-22

Understanding and improving the productivity and robustness of plant photosynthesis requires high-throughput phenotyping under environmental conditions that are relevant to the field. Here we demonstrate the dynamic environmental photosynthesis imager (DEPI), an experimental platform for integrated, continuous, and high-throughput measurements of photosynthetic parameters during plant growth under reproducible yet dynamic environmental conditions. Using parallel imagers obviates the need to move plants or sensors, reducing artifacts and allowing simultaneous measurement on large numbers of plants. As a result, DEPI can reveal phenotypes that are not evident under standard laboratory conditions but emerge under progressively more dynamic illumination. We show examples inmore » mutants of Arabidopsis of such “emergent phenotypes” that are highly transient and heterogeneous, appearing in different leaves under different conditions and depending in complex ways on both environmental conditions and plant developmental age. Finally, these emergent phenotypes appear to be caused by a range of phenomena, suggesting that such previously unseen processes are critical for plant responses to dynamic environments.« less

Effects and mechanisms of the combined pollution of lanthanum and acid rain on the root phenotype of soybean seedlings.

PubMed

Sun, Zhaoguo; Wang, Lihong; Zhou, Qing; Huang, Xiaohua

2013-09-01

Rare earth pollution and acid rain pollution are both important environmental issues worldwide. In regions which simultaneously occur, the combined pollution of rare earth and acid rain becomes a new environmental issue, and the relevant research is rarely reported. Accordingly, we investigated the combined effects and mechanisms of lanthanum ion (La(3+)) and acid rain on the root phenotype of soybean seedlings. The combined pollution of low-concentration La(3+) and acid rain exerted deleterious effects on the phenotype and growth of roots, which were aggravated by the combined pollution of high-concentration La(3+) and acid rain. The deleterious effects of the combined pollution were stronger than those of single La(3+) or acid rain pollution. These stronger deleterious effects on the root phenotype and growth of roots were due to the increased disturbance of absorption and utilization of mineral nutrients in roots. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Genus Corynebacterium and Other Medically Relevant Coryneform-Like Bacteria

PubMed Central

2012-01-01

Catalase-positive Gram-positive bacilli, commonly called “diphtheroids” or “coryneform” bacteria were historically nearly always dismissed as contaminants when recovered from patients, but increasingly have been implicated as the cause of significant infections. These taxa have been underreported, and the taxa were taxonomically confusing. The mechanisms of pathogenesis, especially for newly described taxa, were rarely studied. Antibiotic susceptibility data were relatively scant. In this minireview, clinical relevance, phenotypic and genetic identification methods, matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) evaluations, and antimicrobial susceptibility testing involving species in the genus Corynebacterium and other medically relevant Gram-positive rods, collectively called coryneforms, are described. PMID:22837327

Dataset of the Botrytis cinerea phosphoproteome induced by different plant-based elicitors.

PubMed

Liñeiro, Eva; Chiva, Cristina; Cantoral, Jesús M; Sabido, Eduard; Fernández-Acero, Francisco Javier

2016-06-01

Phosphorylation is one of the main post-translational modification (PTM) involved in signaling network in the ascomycete Botrytis cinerea , one of the most relevant phytopathogenic fungus. The data presented in this article provided a differential mass spectrometry-based analysis of the phosphoproteome of B. cinerea under two different phenotypical conditions induced by the use of two different elicitors: glucose and deproteinized Tomate Cell Walls (TCW). A total 1138 and 733 phosphoproteins were identified for glucose and TCW culture conditions respectively. Raw data are deposited at the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier (PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD003099). Further interpretation and discussion of these data are provided in our research article entitled "Phosphoproteome analysis of B.cinerea in response to different plant-based elicitors" (Liñeiro et al., 2016) [1].

Whole exome sequencing in an Italian family with isolated maxillary canine agenesis and canine eruption anomalies.

PubMed

Barbato, Ersilia; Traversa, Alice; Guarnieri, Rosanna; Giovannetti, Agnese; Genovesi, Maria Luce; Magliozzi, Maria Rosa; Paolacci, Stefano; Ciolfi, Andrea; Pizzi, Simone; Di Giorgio, Roberto; Tartaglia, Marco; Pizzuti, Antonio; Caputo, Viviana

2018-07-01

The aim of this study was the clinical and molecular characterization of a family segregating a trait consisting of a phenotype specifically involving the maxillary canines, including agenesis, impaction and ectopic eruption, characterized by incomplete penetrance and variable expressivity. Clinical standardized assessment of 14 family members and a whole-exome sequencing (WES) of three affected subjects were performed. WES data analyses (sequence alignment, variant calling, annotation and prioritization) were carried out using an in-house implemented pipeline. Variant filtering retained coding and splice-site high quality private and rare variants. Variant prioritization was performed taking into account both the disruptive impact and the biological relevance of individual variants and genes. Sanger sequencing was performed to validate the variants of interest and to carry out segregation analysis. Prioritization of variants "by function" allowed the identification of multiple variants contributing to the trait, including two concomitant heterozygous variants in EDARADD (c.308C>T, p.Ser103Phe) and COL5A1 (c.1588G>A, p.Gly530Ser), specifically associated with a more severe phenotype (i.e. canine agenesis). Differently, heterozygous variants in genes encoding proteins with a role in the WNT pathway were shared by subjects showing a phenotype of impacted/ectopic erupted canines. This study characterized the genetic contribution underlying a complex trait consisting of isolated canine anomalies in a medium-sized family, highlighting the role of WNT and EDA cell signaling pathways in tooth development. Copyright © 2018 Elsevier Ltd. All rights reserved.

A large-scale, in vivo transcription factor screen defines bivalent chromatin as a key property of regulatory factors mediating Drosophila wing development

PubMed Central

Schertel, Claus; Albarca, Monica; Rockel-Bauer, Claudia; Kelley, Nicholas W.; Bischof, Johannes; Hens, Korneel

2015-01-01

Transcription factors (TFs) are key regulators of cell fate. The estimated 755 genes that encode DNA binding domain-containing proteins comprise ∼5% of all Drosophila genes. However, the majority has remained uncharacterized so far due to the lack of proper genetic tools. We generated 594 site-directed transgenic Drosophila lines that contain integrations of individual UAS-TF constructs to facilitate spatiotemporally controlled misexpression in vivo. All transgenes were expressed in the developing wing, and two-thirds induced specific phenotypic defects. In vivo knockdown of the same genes yielded a phenotype for 50%, with both methods indicating a great potential for misexpression to characterize novel functions in wing growth, patterning, and development. Thus, our UAS-TF library provides an important addition to the genetic toolbox of Drosophila research, enabling the identification of several novel wing development-related TFs. In parallel, we established the chromatin landscape of wing imaginal discs by ChIP-seq analyses of five chromatin marks and RNA Pol II. Subsequent clustering revealed six distinct chromatin states, with two clusters showing enrichment for both active and repressive marks. TFs that carry such “bivalent” chromatin are highly enriched for causing misexpression phenotypes in the wing, and analysis of existing expression data shows that these TFs tend to be differentially expressed across the wing disc. Thus, bivalently marked chromatin can be used as a marker for spatially regulated TFs that are functionally relevant in a developing tissue. PMID:25568052

Image-Based High-Throughput Field Phenotyping of Crop Roots1[W][OPEN

PubMed Central

Bucksch, Alexander; Burridge, James; York, Larry M.; Das, Abhiram; Nord, Eric; Weitz, Joshua S.; Lynch, Jonathan P.

2014-01-01

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions. PMID:25187526

Filaggrin haploinsufficiency is highly penetrant and is associated with increased severity of eczema: further delineation of the skin phenotype in a prospective epidemiological study of 792 school children

PubMed Central

Brown, SJ; Relton, CL; Liao, H; Zhao, Y; Sandilands, A; McLean, WHI; Cordell, HJ; Reynolds, NJ

2009-01-01

Background Null mutations within the filaggrin gene (FLG) cause ichthyosis vulgaris and are associated with atopic eczema. However, the dermatological features of filaggrin haploinsufficiency have not been clearly defined. Objectives This study investigated the genotype–phenotype association between detailed skin phenotype and FLG genotype data in a population-based cohort of children. Methods Children (n= 792) aged 7–9 years were examined by a dermatologist. Features of ichthyosis vulgaris, atopic eczema and xerosis were recorded and eczema severity graded using the Three Item Severity score. Each child was genotyped for the six most prevalent FLG null mutations (R501X, 2282del4, R2447X, S3247X, 3702delG, 3673delC). Fisher’s exact test was used to compare genotype frequencies in phenotype groups; logistic regression analysis was used to estimate odds ratios and penetrance of the FLG null genotype and a permutation test performed to investigate eczema severity in different genotype groups. Results Ten children in this cohort had ichthyosis vulgaris, of whom five had mild–moderate eczema. The penetrance of FLG null mutations with respect to flexural eczema was 55·6% in individuals with two mutations, 16·3% in individuals with one mutation and 14·2% in wild-type individuals. Summating skin features known to be associated with FLG null mutations (ichthyosis, keratosis pilaris, palmar hyperlinearity and flexural eczema) showed a penetrance of 100% in children with two FLG mutations, 87·8% in children with one FLG mutation and 46·5% in wild-type individuals (P< 0·0001, Fisher exact test). FLG null mutations were associated with more severe eczema (P= 0·0042) but the mean difference was only 1–2 points in severity score. Three distinct patterns of palmar hyperlinearity were observed and these are reported for the first time. Conclusions Filaggrin haploinsufficiency appears to be highly penetrant when all relevant skin features are included in the analysis. FLG null mutations are associated with more severe eczema, but the effect size is small in a population setting. PMID:19681860

Phenotypic Analysis of ATM Protein Kinase in DNA Double-Strand Break Formation and Repair.

PubMed

Mian, Elisabeth; Wiesmüller, Lisa

2017-01-01

Ataxia telangiectasia mutated (ATM) encodes a serine/threonine protein kinase, which is involved in various regulatory processes in mammalian cells. Its best-known role is apical activation of the DNA damage response following generation of DNA double-strand breaks (DSBs). When DSBs appear, sensor and mediator proteins are recruited, activating transducers such as ATM, which in turn relay a widespread signal to a multitude of downstream effectors. ATM mutation causes Ataxia telangiectasia (AT), whereby the disease phenotype shows differing characteristics depending on the underlying ATM mutation. However, all phenotypes share progressive neurodegeneration and marked predisposition to malignancies at the organismal level and sensitivity to ionizing radiation and chromosome aberrations at the cellular level. Expression and localization of the ATM protein can be determined via western blotting and immunofluorescence microscopy; however, detection of subtle alterations such as resulting from amino acid exchanges rather than truncating mutations requires functional testing. Previous studies on the role of ATM in DSB repair, which connects with radiosensitivity and chromosomal stability, gave at first sight contradictory results. To systematically explore the effects of clinically relevant ATM mutations on DSB repair, we engaged a series of lymphoblastoid cell lines (LCLs) derived from AT patients and controls. To examine DSB repair both in a quantitative and qualitative manners, we used an EGFP-based assay comprising different substrates for distinct DSB repair mechanisms. In this way, we demonstrated that particular signaling defects caused by individual ATM mutations led to specific DSB repair phenotypes. To explore the impact of ATM on carcinogenic chromosomal aberrations, we monitored chromosomal breakage at a breakpoint cluster region hotspot within the MLL gene that has been associated with therapy-related leukemia. PCR-based MLL-breakage analysis of HeLa cells treated with and without pharmacological kinase inhibitors revealed ATM-dependent chromatin remodeling at the MLL break site giving access to DNA repair proteins but also nucleases triggering MLL rearrangements. This chapter summarizes these methods for functional characterization of ATM in patient LCLs and human cell lines.

Comprehensive Analysis of Immunological Synapse Phenotypes Using Supported Lipid Bilayers.

PubMed

Valvo, Salvatore; Mayya, Viveka; Seraia, Elena; Afrose, Jehan; Novak-Kotzer, Hila; Ebner, Daniel; Dustin, Michael L

2017-01-01

Supported lipid bilayers (SLB) formed on glass substrates have been a useful tool for study of immune cell signaling since the early 1980s. The mobility of lipid-anchored proteins in the system, first described for antibodies binding to synthetic phospholipid head groups, allows for the measurement of two-dimensional binding reactions and signaling processes in a single imaging plane over time or for fixed samples. The fragility of SLB and the challenges of building and validating individual substrates limit most experimenters to ~10 samples per day, perhaps increasing this few-fold when examining fixed samples. Successful experiments might then require further days to fully analyze. We present methods for automation of many steps in SLB formation, imaging in 96-well glass bottom plates, and analysis that enables >100-fold increase in throughput for fixed samples and wide-field fluorescence. This increased throughput will allow better coverage of relevant parameters and more comprehensive analysis of aspects of the immunological synapse that are well reconstituted by SLB.

A standard based approach for biomedical knowledge representation.

PubMed

Farkash, Ariel; Neuvirth, Hani; Goldschmidt, Yaara; Conti, Costanza; Rizzi, Federica; Bianchi, Stefano; Salvi, Erika; Cusi, Daniele; Shabo, Amnon

2011-01-01

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.

Heightened extended amygdala metabolism following threat characterizes the early phenotypic risk to develop anxiety-related psychopathology

PubMed Central

Shackman, Alexander J.; Fox, Andrew S.; Oler, Jonathan A.; Shelton, Steven E.; Oakes, Terrence R.; Davidson, Richard J.; Kalin, Ned H.

2016-01-01

Children with an anxious temperament (AT) are prone to heightened shyness and behavioral inhibition (BI). When chronic and extreme, this anxious, inhibited phenotype is an important early-life risk factor for the development of anxiety disorders, depression, and co-morbid substance abuse. Individuals with extreme AT often show persistent distress in the absence of immediate threat and this contextually inappropriate anxiety predicts future symptom development. Despite its clear clinical relevance, the neural circuitry governing the maladaptive persistence of anxiety remains unknown. Here, we used a well-established nonhuman primate model of childhood temperament and high-resolution 18fluorodeoxyglucose positron emission tomography (FDG-PET) imaging to understand the neural systems governing persistent anxiety and clarify their relevance to early-life phenotypic risk. We focused on BI, a core component of anxious temperament, because it affords the moment-by-moment temporal resolution needed to assess contextually appropriate and inappropriate anxiety. From a pool of 109 peri-adolescent rhesus monkeys, we formed groups characterized by high or low levels of BI, as indexed by freezing in response to an unfamiliar human intruder’s profile. The High-BI group showed consistently elevated signs of anxiety and wariness across more than 2 years of assessments. At the time of brain imaging, 1.5 years after initial phenotyping, the High-BI group showed persistently elevated freezing during a 30-min ‘recovery’ period following an encounter with the intruder — more than an order of magnitude greater than the Low-BI group — and this was associated with increased metabolism in the bed nucleus of the stria terminalis, a key component of the central extended amygdala. These observations provide a neurobiological framework for understanding the early phenotypic risk to develop anxiety-related psychopathology, for accelerating the development of improved interventions, and for understanding the origins of childhood temperament. PMID:27573879

Developmental programming: the role of growth hormone.

PubMed

Oberbauer, Anita M

2015-01-01

Developmental programming of the fetus has consequences for physiologic responses in the offspring as an adult and, more recently, is implicated in the expression of altered phenotypes of future generations. Some phenotypes, such as fertility, bone strength, and adiposity are highly relevant to food animal production and in utero factors that impinge on those traits are vital to understand. A key systemic regulatory hormone is growth hormone (GH), which has a developmental role in virtually all tissues and organs. This review catalogs the impact of GH on tissue programming and how perturbations early in development influence GH function.

A novel taxon within the genus Actinobacillus isolated from alpaca (Vicugna pacos) in the United Kingdom.

PubMed

Hunt, Brian; Bidewell, Cornelia; Koylass, Mark S; Whatmore, Adrian M

2013-05-03

Members of the genus Actinobacillus comprise a diverse group of bacteria associated with mammals and birds including both pathogens and commensals. Here we describe the isolation of a previously undescribed Actinobacillus-like organism from seven epidemiologically unrelated infections of alpaca. The isolates are phenotypically and genotypically distinct from any previously described Actinobacillus species but 16S rRNA analysis unequivocally places the isolates as a novel lineage within the Actinobacillus sensu stricto. The clinical relevance of the organism requires further study however isolation in pure culture from organs of some cases suggests it may be associated with septicaemia in juvenile alpaca. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Genome-Wide Association Study Meta-Analysis of Long Term Average Blood Pressure in East Asians

PubMed Central

Li, Changwei; Kim, Yun Kyoung; Dorajoo, Rajkumar; Li, Huaixing; Lee, I-Te; Cheng, Ching-Yu; He, Meian; Sheu, Wayne H-h; Guo, Xiuqing; Ganesh, Santhi K.; He, Jiang; Lee, Juyoung; Liu, Jianjun; Hu, Yao; Rao, Dabeeru C.; Tsai, Fuu-Jen; Koh, Jia Yu; Hu, Hua; Liang, Kae-Woei; Palmas, Walter; Hixson, James E.; Han, Sohee; Teo, Yik-Ying; Wang, Yiqin; Chen, Jing; Lu, Chieh Hsiang; Zheng, Yingfeng; Gui, Lixuan; Lee, Wen-Jane; Yao, Jie; Gu, Dongfeng; Han, Bok-Ghee; Sim, Xueling; Sun, Liang; Zhao, Jinying; Chen, Chien-Hsiun; Kumari, Neelam; He, Yunfeng; Taylor, Kent D.; Raffel, Leslie J.; Moon, Sanghoon; Rotter, Jerome I.; Ida Chen, Yii-der; Wu, Tangchun; Wong, Tien Yin; Wu, Jer-Yuarn; Lin, Xu; Tai, E-Shyong; Kim, Bong-Jo; Kelly, Tanika N.

2017-01-01

Background Genome-wide single marker and gene-based meta-analyses of long term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP. Methods and Results We conducted genome-wide analysis among 18,422 East Asian participants (stage-1) followed by replication study of up to 46,629 participants of European ancestry (stage-2). Significant SNPs and genes were determined by a P<5.0×10−8 and 2.5×10−6, respectively, in joint analyses of stage-1 and stage-2 data. We identified one novel ARL3 variant, rs4919669 at 10q24.32, influencing LTA systolic BP (stage-1 P=5.03×10−8, stage-2 P=8.64×10−3, joint P=2.63×10−8) and mean arterial pressure (stage-1 P=3.59×10−9, stage-2 P=2.35×10−2, joint P=2.64×10−8). Three previously reported BP loci (WBP1L, NT5C2, and ATP2B1) were also identified for all BP phenotypes. Gene-based analysis provided the first robust evidence for association of KCNJ11 with LTA SBP (stage-1 P=8.55×10−6, stage-2 P=1.62×10−5, joint P=3.28×10−9) and mean arterial pressure (stage-1 P=9.19×10−7, stage-2 P=9.69×10−5, joint P=2.15×10−9) phenotypes. Fourteen genes (TMEM180, ACTR1A, SUFU, ARL3, SFXN2, WBP1L, CYP17A1, C10orf32, C10orf32-ASMT, AS3MT, CNNM2, and NT5C2 at 10q24.32; ATP2B1 at 12q21.33; and NCR3LG1 at 11p15.1) implicated by previous genome-wide association study meta-analyses were also identified. Among the loci identified by the previous genome-wide association study meta-analysis of LTA BP, we trans-ethnically replicated associations of the KCNK3 marker rs1275988 at 2p23.3 with LTA systolic BP and mean arterial pressure phenotypes (P=1.27×10−4 and 3.30×10−4, respectively). Conclusions We identified 1 novel variant and 1 novel gene, and present the first direct evidence of relevance of the KCNK3 locus for LTA BP among East Asians. PMID:28348047

Patient-derived iPSCs show premature neural differentiation and neuron-type specific phenotypes relevant to neurodevelopment

PubMed Central

Yeh, Erika; Dao, Dang Q.; Wu, Zhi Y.; Kandalam, Santoshi M.; Camacho, Federico M.; Tom, Curtis; Zhang, Wandong; Krencik, Robert; Rauen, Katherine A.; Ullian, Erik M.; Weiss, Lauren A.

2017-01-01

Ras/MAPK pathway signaling is a major participant in neurodevelopment, and evidence suggests that BRAF, a key Ras signal mediator, influences human behavior. We studied the role of the mutation BRAFQ257R, the most common cause of cardiofaciocutaneous syndrome (CFC), in an induced pluripotent stem cell (iPSC)-derived model of human neurodevelopment. In iPSC-derived neuronal cultures from CFC subjects, we observed decreased p-AKT and p-ERK1/2 compared to controls, as well as a depleted neural progenitor pool and rapid neuronal maturation. Pharmacological PI3K/AKT pathway manipulation recapitulated cellular phenotypes in control cells and attenuated them in CFC cells. CFC cultures displayed altered cellular subtype ratios and increased intrinsic excitability. Moreover, in CFC cells, Ras/MAPK pathway activation and morphological abnormalities exhibited cell subtype-specific differences. Our results highlight the importance of exploring specific cellular subtypes and of using iPSC models to reveal relevant human-specific neurodevelopmental events. PMID:29158583

Phenotypic and genomic characterization of the antimicrobial producer Rheinheimera sp. EpRS3 isolated from the medicinal plant Echinacea purpurea: insights into its biotechnological relevance.

PubMed

Presta, Luana; Bosi, Emanuele; Fondi, Marco; Maida, Isabel; Perrin, Elena; Miceli, Elisangela; Maggini, Valentina; Bogani, Patrizia; Firenzuoli, Fabio; Di Pilato, Vincenzo; Rossolini, Gian Maria; Mengoni, Alessio; Fani, Renato

2017-04-01

In recent years, there has been increasing interest in plant microbiota; however, despite medicinal plant relevance, very little is known about their highly complex endophytic communities. In this work, we report on the genomic and phenotypic characterization of the antimicrobial compound producer Rheinheimera sp. EpRS3, a bacterial strain isolated from the rhizospheric soil of the medicinal plant Echinacea purpurea. In particular, EpRS3 is able to inhibit growth of different bacterial pathogens (Bcc, Acinetobacter baumannii, and Klebsiella pneumoniae) which might be related to the presence of gene clusters involved in the biosynthesis of different types of secondary metabolites. The outcomes presented in this work highlight the fact that the strain possesses huge biotechnological potential; indeed, it also shows antimicrobial effects upon well-described multidrug-resistant (MDR) human pathogens, and it affects plant root elongation and morphology, mimicking indole acetic acid (IAA) action. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Computable visually observed phenotype ontological framework for plants

PubMed Central

2011-01-01

Background The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research. Conclusions The Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community. PMID:21702966

Against Genetic Tests for Athletic Talent: The Primacy of the Phenotype.

PubMed

Loland, Sigmund

2015-09-01

New insights into the genetics of sport performance lead to new areas of application. One area is the use of genetic tests to identify athletic talent. Athletic performances involve a high number of complex phenotypical traits. Based on the ACCE model (review of Analytic and Clinical validity, Clinical utility, and Ethical, legal and social implications), a critique is offered of the lack of validity and predictive power of genetic tests for talent. Based on the ideal of children's right to an open future, a moral argument is given against such tests on children and young athletes. A possible role of genetic tests in sport is proposed in terms of identifying predisposition for injury. In meeting ACCE requirements, such tests could improve individualised injury prevention and increase athlete health. More generally, limitations of science are discussed in the identification of talent and in the understanding of complex human performance phenotypes. An alternative approach to talent identification is proposed in terms of ethically sensitive, systematic and evidence-based holistic observation over time of relevant phenotypical traits by experienced observers. Talent identification in sport should be based on the primacy of the phenotype.

Selection on skewed characters and the paradox of stasis

PubMed Central

Bonamour, Suzanne; Teplitsky, Céline; Charmantier, Anne; Crochet, Pierre-André; Chevin, Luis-Miguel

2018-01-01

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modelling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold’s (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson-Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate samples size. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date – repeatedly described as more evolutionarily stable than expected –, so this skewness should be accounted for when investigating evolutionary dynamics in the wild. PMID:28921508

Mediterranean blue tits as a case study of local adaptation.

PubMed

Charmantier, Anne; Doutrelant, Claire; Dubuc-Messier, Gabrielle; Fargevieille, Amélie; Szulkin, Marta

2016-01-01

While the study of the origins of biological diversity across species has provided numerous examples of adaptive divergence, the realization that it can occur at microgeographic scales despite gene flow is recent, and scarcely illustrated. We review here evidence suggesting that the striking phenotypic differentiation in ecologically relevant traits exhibited by blue tits Cyanistes caeruleus in their southern range-edge putatively reflects adaptation to the heterogeneity of the Mediterranean habitats. We first summarize the phenotypic divergence for a series of life history, morphological, behavioural, acoustic and colour ornament traits in blue tit populations of evergreen and deciduous forests. For each divergent trait, we review the evidence obtained from common garden experiments regarding a possible genetic origin of the observed phenotypic differentiation as well as evidence for heterogeneous selection. Second, we argue that most phenotypically differentiated traits display heritable variation, a fundamental requirement for evolution to occur. Third, we discuss nonrandom dispersal, selective barriers and assortative mating as processes that could reinforce local adaptation. Finally, we show how population genomics supports isolation - by - environment across landscapes. Overall, the combination of approaches converges to the conclusion that the strong phenotypic differentiation observed in Mediterranean blue tits is a fascinating case of local adaptation.

Deletions and epimutations affecting the human 14q32.2 imprinted region in individuals with paternal and maternal upd(14)-like phenotypes.

PubMed

Kagami, Masayo; Sekita, Yoichi; Nishimura, Gen; Irie, Masahito; Kato, Fumiko; Okada, Michiyo; Yamamori, Shunji; Kishimoto, Hiroshi; Nakayama, Masahiro; Tanaka, Yukichi; Matsuoka, Kentarou; Takahashi, Tsutomu; Noguchi, Mika; Tanaka, Yoko; Masumoto, Kouji; Utsunomiya, Takeshi; Kouzan, Hiroko; Komatsu, Yumiko; Ohashi, Hirofumi; Kurosawa, Kenji; Kosaki, Kenjirou; Ferguson-Smith, Anne C; Ishino, Fumitoshi; Ogata, Tsutomu

2008-02-01

Human chromosome 14q32.2 carries a cluster of imprinted genes including paternally expressed genes (PEGs) such as DLK1 and RTL1 and maternally expressed genes (MEGs) such as MEG3 (also known as GTL2), RTL1as (RTL1 antisense) and MEG8 (refs. 1,2), together with the intergenic differentially methylated region (IG-DMR) and the MEG3-DMR. Consistent with this, paternal and maternal uniparental disomy for chromosome 14 (upd(14)pat and upd(14)mat) cause distinct phenotypes. We studied eight individuals (cases 1-8) with a upd(14)pat-like phenotype and three individuals (cases 9-11) with a upd(14)mat-like phenotype in the absence of upd(14) and identified various deletions and epimutations affecting the imprinted region. The results, together with recent mouse data, imply that the IG-DMR has an important cis-acting regulatory function on the maternally inherited chromosome and that excessive RTL1 expression and decreased DLK1 and RTL1 expression are relevant to upd(14)pat-like and upd(14)mat-like phenotypes, respectively.

A Quantitative Systems Pharmacology Approach to Infer Pathways Involved in Complex Disease Phenotypes.

PubMed

Schurdak, Mark E; Pei, Fen; Lezon, Timothy R; Carlisle, Diane; Friedlander, Robert; Taylor, D Lansing; Stern, Andrew M

2018-01-01

Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression. Quantitative systems pharmacology (QSP) is an approach to drug discovery that integrates computational and experimental methods to understand the molecular pathogenesis of a disease at the systems level more completely. Described here is the chemogenomic component of QSP for the inference of biological pathways involved in the modulation of the disease phenotype. The approach involves testing sets of compounds of diverse mechanisms of action in a disease-relevant phenotypic assay, and using the mechanistic information known for the active compounds, to infer pathways and networks associated with the phenotype. The example used here is for monogenic Huntington's disease (HD), which due to the pleiotropic nature of the mutant phenotype has a complex pathogenesis. The overall approach, however, is applicable to any complex disease.

Modeling continuum of epithelial mesenchymal transition plasticity.

PubMed

Mandal, Mousumi; Ghosh, Biswajoy; Anura, Anji; Mitra, Pabitra; Pathak, Tanmaya; Chatterjee, Jyotirmoy

2016-02-01

Living systems respond to ambient pathophysiological changes by altering their phenotype, a phenomenon called 'phenotypic plasticity'. This program contains information about adaptive biological dynamism. Epithelial-mesenchymal transition (EMT) is one such process found to be crucial in development, wound healing, and cancer wherein the epithelial cells with restricted migratory potential develop motile functions by acquiring mesenchymal characteristics. In the present study, phase contrast microscopy images of EMT induced HaCaT cells were acquired at 24 h intervals for 96 h. The expression study of relevant pivotal molecules viz. F-actin, vimentin, fibronectin and N-cadherin was carried out to confirm the EMT process. Cells were intuitively categorized into five distinct morphological phenotypes. A population of 500 cells for each temporal point was selected to quantify their frequency of occurrence. The plastic interplay of cell phenotypes from the observations was described as a Markovian process. A model was formulated empirically using simple linear algebra, to depict the possible mechanisms of cellular transformation among the five phenotypes. This work employed qualitative, semi-quantitative and quantitative tools towards illustration and establishment of the EMT continuum. Thus, it provides a newer perspective to understand the embedded plasticity across the EMT spectrum.

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

PubMed Central

Rahaman, Md. Matiur; Chen, Dijun; Gillani, Zeeshan; Klukas, Christian; Chen, Ming

2015-01-01

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis. PMID:26322060

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

Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit1[OPEN

PubMed Central

Tamilselvan, Anandhan; Lawas, Lovely M.F.; Quinones, Cherryl; Bahuguna, Rajeev N.; Dingkuhn, Michael

2017-01-01

Elucidating the genetic control of rooting behavior under water-deficit stress is essential to breed climate-robust rice (Oryza sativa) cultivars. Using a diverse panel of 274 indica genotypes grown under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, mostly related to root morphology and anatomy, involving 45,000 root-scanning images and nearly 25,000 cross sections from the root-shoot junction. The phenotypic plasticity of these traits was quantified as the relative change in trait value under water-deficit compared with control conditions. We then carried out a genome-wide association analysis on these traits and their plasticity, using 45,608 high-quality single-nucleotide polymorphisms. One hundred four significant loci were detected for these traits under control conditions, 106 were detected under water-deficit stress, and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress), and 233 (plasticity) a priori candidate genes within linkage disequilibrium blocks for these loci. We identified key a priori candidate genes regulating root growth and development and relevant alleles that, upon validation, can help improve rice adaptation to water-deficit stress. PMID:28600346

Innovative approaches to bipolar disorder and its treatment

PubMed Central

Cipriani, Andrea; Harmer, Catherine J.; Nobre, Anna C.; Saunders, Kate; Goodwin, Guy M.; Geddes, John R.

2016-01-01

All psychiatric disorders have suffered from a dearth of truly novel pharmacological interventions. In bipolar disorder, lithium remains a mainstay of treatment, six decades since its effects were serendipitously discovered. The lack of progress reflects several factors, including ignorance of the disorder's pathophysiology and the complexities of the clinical phenotype. After reviewing the current status, we discuss some ways forward. First, we highlight the need for a richer characterization of the clinical profile, facilitated by novel devices and new forms of data capture and analysis; such data are already promoting a reevaluation of the phenotype, with an emphasis on mood instability rather than on discrete clinical episodes. Second, experimental medicine can provide early indications of target engagement and therapeutic response, reducing the time, cost, and risk involved in evaluating potential mood stabilizers. Third, genomic data can inform target identification and validation, such as the increasing evidence for involvement of calcium channel genes in bipolar disorder. Finally, new methods and models relevant to bipolar disorder, including stem cells and genetically modified mice, are being used to study key pathways and drug effects. A combination of these approaches has real potential to break the impasse and deliver genuinely new treatments. PMID:27111134

FGFR4 signaling couples to Bim and not Bmf to discriminate subsets of alveolar rhabdomyosarcoma cells.

PubMed

Wachtel, Marco; Rakic, Jelena; Okoniewski, Michal; Bode, Peter; Niggli, Felix; Schäfer, Beat W

2014-10-01

Biological heterogeneity represents a major obstacle for cancer treatment. Therefore, characterization of treatment-relevant tumor heterogeneity is necessary to develop more effective therapies in the future. Here, we uncovered population heterogeneity among PAX/FOXO1-positive alveolar rhabdomyosarcoma by characterizing prosurvival networks initiated by FGFR4 signaling. We found that FGFR4 signaling rescues only subgroups of alveolar rhabdomyosarcoma cells from apoptosis induced by compounds targeting the IGF1R-PI3K-mTOR pathway. Differences in both proapoptotic machinery and FGFR4-activated signaling are involved in the different behavior of the phenotypes. Proapoptotic stress induced by the kinase inhibitors is sensed by Bim/Bad in rescue cells and by Bmf in nonrescue cells. Anti-apoptotic ERK1/2 signaling downstream of FGFR4 is long-lasting in rescue and short-termed in most non-rescue cells. Gene expression analysis detected signatures specific for these two groups also in biopsy samples. The different cell phenotypes are present in different ratios in alveolar rhabdomyosarcoma tumors and can be identified by AP2β expression levels. Hence, inhibiting FGFR signaling might represent an important strategy to enhance efficacy of current RMS treatments. © 2014 UICC.

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.

Unraveling the resistance of microbial biofilms: has proteomics been helpful?

PubMed

Seneviratne, C Jayampath; Wang, Yu; Jin, Lijian; Wong, Sarah S W; Herath, Thanuja D K; Samaranayake, Lakshman P

2012-02-01

Biofilms are surface-attached, matrix-encased, structured microbial communities which display phenotypic features that are dramatically different from those of their free-floating, or planktonic, counterparts. Biofilms seem to be the preferred mode of growth of microorganisms in nature, and at least 65% of all human infections are associated with biofilms. The most notable and clinically relevant property of biofilms is their greater resistance to antimicrobials compared with their planktonic counterparts. Although both bacterial and fungal biofilms display this phenotypic feature, the exact mechanisms underlying their increased drug resistance are yet to be determined. Advances in proteomics techniques during the past decade have facilitated in-depth analysis of the possible mechanisms underpinning increased drug resistance in biofilms. These studies have demonstrated the ability of proteomics techniques to unravel new targets for combating microbial biofilms. In this review, we discuss the putative drug resistance mechanisms of microbial biofilms that have been uncovered by proteomics and critically evaluate the possible contribution of the new knowledge to future development in the field. We also summarize strategic uses of novel proteomics technologies in studies related to drug resistance mechanisms of microbial biofilms. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systems Genetic Analyses Highlight a TGFβ-FOXO3 Dependent Striatal Astrocyte Network Conserved across Species and Associated with Stress, Sleep, and Huntington's Disease.

PubMed

Scarpa, Joseph R; Jiang, Peng; Losic, Bojan; Readhead, Ben; Gao, Vance D; Dudley, Joel T; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

2016-07-01

Recent systems-based analyses have demonstrated that sleep and stress traits emerge from shared genetic and transcriptional networks, and clinical work has elucidated the emergence of sleep dysfunction and stress susceptibility as early symptoms of Huntington's disease. Understanding the biological bases of these early non-motor symptoms may reveal therapeutic targets that prevent disease onset or slow disease progression, but the molecular mechanisms underlying this complex clinical presentation remain largely unknown. In the present work, we specifically examine the relationship between these psychiatric traits and Huntington's disease (HD) by identifying striatal transcriptional networks shared by HD, stress, and sleep phenotypes. First, we utilize a systems-based approach to examine a large publicly available human transcriptomic dataset for HD (GSE3790 from GEO) in a novel way. We use weighted gene coexpression network analysis and differential connectivity analyses to identify transcriptional networks dysregulated in HD, and we use an unbiased ranking scheme that leverages both gene- and network-level information to identify a novel astrocyte-specific network as most relevant to HD caudate. We validate this result in an independent HD cohort. Next, we computationally predict FOXO3 as a regulator of this network, and use multiple publicly available in vitro and in vivo experimental datasets to validate that this astrocyte HD network is downstream of a signaling pathway important in adult neurogenesis (TGFβ-FOXO3). We also map this HD-relevant caudate subnetwork to striatal transcriptional networks in a large (n = 100) chronically stressed (B6xA/J)F2 mouse population that has been extensively phenotyped (328 stress- and sleep-related measurements), and we show that this striatal astrocyte network is correlated to sleep and stress traits, many of which are known to be altered in HD cohorts. We identify causal regulators of this network through Bayesian network analysis, and we highlight their relevance to motor, mood, and sleep traits through multiple in silico approaches, including an examination of their protein binding partners. Finally, we show that these causal regulators may be therapeutically viable for HD because their downstream network was partially modulated by deep brain stimulation of the subthalamic nucleus, a medical intervention thought to confer some therapeutic benefit to HD patients. In conclusion, we show that an astrocyte transcriptional network is primarily associated to HD in the caudate and provide evidence for its relationship to molecular mechanisms of neural stem cell homeostasis. Furthermore, we present a unified systems-based framework for identifying gene networks that are associated with complex non-motor traits that manifest in the earliest phases of HD. By analyzing and integrating multiple independent datasets, we identify a point of molecular convergence between sleep, stress, and HD that reflects their phenotypic comorbidity and reveals a molecular pathway involved in HD progression.

Microbial community analysis of field-grown soybeans with different nodulation phenotypes.

PubMed

Ikeda, Seishi; Rallos, Lynn Esther E; Okubo, Takashi; Eda, Shima; Inaba, Shoko; Mitsui, Hisayuki; Minamisawa, Kiwamu

2008-09-01

Microorganisms associated with the stems and roots of nonnodulated (Nod(-)), wild-type nodulated (Nod(+)), and hypernodulated (Nod(++)) soybeans [Glycine max (L.) Merril] were analyzed by ribosomal intergenic transcribed spacer analysis (RISA) and automated RISA (ARISA). RISA of stem samples detected no bands specific to the nodulation phenotype, whereas RISA of root samples revealed differential bands for the nodulation phenotypes. Pseudomonas fluorescens was exclusively associated with Nod(+) soybean roots. Fusarium solani was stably associated with nodulated (Nod(+) and Nod(++)) roots and less abundant in Nod(-) soybeans, whereas the abundance of basidiomycetes was just the opposite. The phylogenetic analyses suggested that these basidiomycetous fungi might represent a root-associated group in the Auriculariales. Principal-component analysis of the ARISA results showed that there was no clear relationship between nodulation phenotype and bacterial community structure in the stem. In contrast, both the bacterial and fungal community structures in the roots were related to nodulation phenotype. The principal-component analysis further suggested that bacterial community structure in roots could be classified into three groups according to the nodulation phenotype (Nod(-), Nod(+), or Nod(++)). The analysis of root samples indicated that the microbial community in Nod(-) soybeans was more similar to that in Nod(++) soybeans than to that in Nod(+) soybeans.

SEE locomotor behavior test discriminates C57BL/6J and DBA/2J mouse inbred strains across laboratories and protocol conditions.

PubMed

Kafkafi, Neri; Lipkind, Dina; Benjamini, Yoav; Mayo, Cheryl L; Elmer, Gregory I; Golani, Ilan

2003-06-01

Conventional tests of behavioral phenotyping frequently have difficulties differentiating certain genotypes and replicating these differences across laboratories and protocol conditions. This study explores the hypothesis that automated tests can be designed to quantify ethologically relevant behavior patterns that more readily characterize heritable and replicable phenotypes. It used SEE (Strategy for the Exploration of Exploration) to phenotype the locomotor behavior of the C57BL/6 and DBA/2 mouse inbred strains across 3 laboratories. The 2 genotypes differed in 15 different measures of behavior, none of which had a significant genotype-laboratory interaction. Within the same laboratory, most of these differences were replicated in additional experiments despite the test photoperiod phase being changed and saline being injected. Results suggest that well-designed tests may considerably enhance replicability across laboratories.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Pheno-phenotypes: a holistic approach to the psychopathology of schizophrenia.

PubMed

Stanghellini, Giovanni; Rossi, Rodolfo

2014-05-01

Mental disorders are mainly characterized via symptom assessment. Symptoms are state-like macroscopic anomalies of behaviour, experience, and expression that are deemed relevant for diagnostic purposes. An alternative approach is based on the concept of endophenotypes, which are physiological or behavioural measures occupying the terrain between symptoms and risk genotypes. We will critically discuss these two approaches, and later focus on the concept of pheno-phenotype as it is revealed by recent phenomenological research on schizophrenia. Several studies have been recently published on the schizophrenic pheno-phenotype mainly addressing self-disorders, as well as disorders of time and bodily experience. The mainstream approach to psychopathological phenotypes is focussed on easy-to-assess operationalizable symptoms. Thinness of phenotypes and simplification of clinical constructs are the consequences of this. Also, this approach has not been successful in investigating the biological causes of mental disorders. An integrative approach is based on the concept of 'endophenotype'. Endophenotypes were conceptualized as a supportive tool for the genetic dissection of psychiatric disorders. The underlying rationale states that disease-specific phenotypes should be the upstream phenotypic manifestation of a smaller genotype than the whole disease-related genotype. Psychopathological phenotypes can also be characterized in terms of pheno-phenotypes. This approach aims at delineating the manifold phenomena experienced by patients in all of their concrete and distinctive features, so that the features of a pathological condition emerge, while preserving their peculiar feel, meaning, and value for the patient. Systematic explorations of anomalies in the patients' experience, for example, of time, space, body, self, and otherness, may provide a useful integration to the symptom-based and endophenotype-based approaches. These abnormal phenomena can be used as pointers to the fundamental alterations of the structure of subjectivity characterizing each mental disorder.

Survey of the human acetylator polymorphism in spontaneous disorders.

PubMed Central

Evans, D A

1984-01-01

There is ample evidence that the human acetylator phenotypes are associated with drug induced phenomena. It is principally the slow acetylators who exhibit toxic adverse effects because of their relative inability to detoxify the original drug compounds. In rare instances, however, it is the rapid acetylators who are at a disadvantage. In the matter of association of spontaneous disease with either acetylator phenotype, there are two groups of disorders to consider. First, disorders in which carcinogenic amines are known to be an aetiological factor. This is because these amines are substrates for the polymorphic N-acetyltransferase activity and hence there is a possible rational basis for searching for an association. Secondly, other disorders where searches for associations are based more on hunches. In the first group there is a definite statistical association between cancer of the bladder and the slow acetylator phenotype. In prevalence studies the slow phenotype is 39% more associated with bladder cancer than is the rapid phenotype. On the basis of the evidence now available it is not possible to say whether this association is because slow acetylators develop the disease more frequently or whether they survive longer. In the second group the relevant studies show (1) a greatly increased prevalence of slow acetylators in Gilbert's disease; (2) a confirmed association between the rapid acetylator phenotype and diabetes; (3) a possible association between the rapid acetylator phenotype and breast cancer; (4) a possible association between the slow acetylator phenotype and leprosy in Chinese patients; (5) an earlier age of onset of thyrotoxicosis (Graves' disease) in slow acetylators than in rapid acetylators; (6) no evidence of an association between either phenotype and spontaneous systemic lupus erythematosus. PMID:6387123

Phenotype-specific CpG island methylation events in a murine model of prostate cancer.

PubMed

Camoriano, Marta; Kinney, Shannon R Morey; Moser, Michael T; Foster, Barbara A; Mohler, James L; Trump, Donald L; Karpf, Adam R; Smiraglia, Dominic J

2008-06-01

Aberrant DNA methylation plays a significant role in nearly all human cancers and may contribute to disease progression to advanced phenotypes. Study of advanced prostate cancer phenotypes in the human disease is hampered by limited availability of tissues. We therefore took advantage of the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model to study whether three different phenotypes of TRAMP tumors (PRIM, late-stage primary tumors; AIP, androgen-independent primary tumors; and MET, metastases) displayed specific patterns of CpG island hypermethylation using Restriction Landmark Genomic Scanning. Each tumor phenotype displayed numerous hypermethylation events, with the most homogeneous methylation pattern in AIP and the most heterogeneous pattern in MET. Several loci displayed a phenotype-specific methylation pattern; the most striking pattern being loci methylated at high frequency in PRIM and AIP but rarely in MET. Examination of the mRNA expression of three genes, BC058385, Goosecoid, and Neurexin 2, which exhibited nonpromoter methylation, revealed increased expression associated with downstream methylation. Only methylated samples showed mRNA expression, in which tumor phenotype was a key factor determining the level of expression. The CpG island in the human orthologue of BC058385 was methylated in human AIP but not in primary androgen-stimulated prostate cancer or benign prostate. The clinical data show a proof-of-principle that the TRAMP model can be used to identify targets of aberrant CpG island methylation relevant to human disease. In conclusion, phenotype-specific hypermethylation events were associated with the overexpression of different genes and may provide new markers of prostate tumorigenesis.

Using network analysis to study behavioural phenotypes: an example using domestic dogs.

PubMed

Goold, Conor; Vas, Judit; Olsen, Christine; Newberry, Ruth C

2016-10-01

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs ( Canis lupus familiaris ). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Clinical Implications of Cluster Analysis-Based Classification of Acute Decompensated Heart Failure and Correlation with Bedside Hemodynamic Profiles.

PubMed

Ahmad, Tariq; Desai, Nihar; Wilson, Francis; Schulte, Phillip; Dunning, Allison; Jacoby, Daniel; Allen, Larry; Fiuzat, Mona; Rogers, Joseph; Felker, G Michael; O'Connor, Christopher; Patel, Chetan B

2016-01-01

Classification of acute decompensated heart failure (ADHF) is based on subjective criteria that crudely capture disease heterogeneity. Improved phenotyping of the syndrome may help improve therapeutic strategies. To derive cluster analysis-based groupings for patients hospitalized with ADHF, and compare their prognostic performance to hemodynamic classifications derived at the bedside. We performed a cluster analysis on baseline clinical variables and PAC measurements of 172 ADHF patients from the ESCAPE trial. Employing regression techniques, we examined associations between clusters and clinically determined hemodynamic profiles (warm/cold/wet/dry). We assessed association with clinical outcomes using Cox proportional hazards models. Likelihood ratio tests were used to compare the prognostic value of cluster data to that of hemodynamic data. We identified four advanced HF clusters: 1) male Caucasians with ischemic cardiomyopathy, multiple comorbidities, lowest B-type natriuretic peptide (BNP) levels; 2) females with non-ischemic cardiomyopathy, few comorbidities, most favorable hemodynamics; 3) young African American males with non-ischemic cardiomyopathy, most adverse hemodynamics, advanced disease; and 4) older Caucasians with ischemic cardiomyopathy, concomitant renal insufficiency, highest BNP levels. There was no association between clusters and bedside-derived hemodynamic profiles (p = 0.70). For all adverse clinical outcomes, Cluster 4 had the highest risk, and Cluster 2, the lowest. Compared to Cluster 4, Clusters 1-3 had 45-70% lower risk of all-cause mortality. Clusters were significantly associated with clinical outcomes, whereas hemodynamic profiles were not. By clustering patients with similar objective variables, we identified four clinically relevant phenotypes of ADHF patients, with no discernable relationship to hemodynamic profiles, but distinct associations with adverse outcomes. Our analysis suggests that ADHF classification using simultaneous considerations of etiology, comorbid conditions, and biomarker levels, may be superior to bedside classifications.

Molecular and clinical profile of von Willebrand disease in Spain (PCM-EVW-ES): comprehensive genetic analysis by next-generation sequencing of 480 patients

PubMed Central

Borràs, Nina; Batlle, Javier; Pérez-Rodríguez, Almudena; López-Fernández, María Fernanda; Rodríguez-Trillo, Ángela; Lourés, Esther; Cid, Ana Rosa; Bonanad, Santiago; Cabrera, Noelia; Moret, Andrés; Parra, Rafael; Mingot-Castellano, María Eva; Balda, Ignacia; Altisent, Carme; Pérez-Montes, Rocío; Fisac, Rosa María; Iruín, Gemma; Herrero, Sonia; Soto, Inmaculada; de Rueda, Beatriz; Jiménez-Yuste, Víctor; Alonso, Nieves; Vilariño, Dolores; Arija, Olga; Campos, Rosa; Paloma, María José; Bermejo, Nuria; Berrueco, Rubén; Mateo, José; Arribalzaga, Karmele; Marco, Pascual; Palomo, Ángeles; Sarmiento, Lizheidy; Iñigo, Belén; Nieto, María del Mar; Vidal, Rosa; Martínez, María Paz; Aguinaco, Reyes; César, Jesús María; Ferreiro, María; García-Frade, Javier; Rodríguez-Huerta, Ana María; Cuesta, Jorge; Rodríguez-González, Ramón; García-Candel, Faustino; Cornudella, Rosa; Aguilar, Carlos; Vidal, Francisco; Corrales, Irene

2017-01-01

Molecular diagnosis of patients with von Willebrand disease is pending in most populations due to the complexity and high cost of conventional molecular analyses. The need for molecular and clinical characterization of von Willebrand disease in Spain prompted the creation of a multicenter project (PCM-EVW-ES) that resulted in the largest prospective cohort study of patients with all types of von Willebrand disease. Molecular analysis of relevant regions of the VWF, including intronic and promoter regions, was achieved in the 556 individuals recruited via the development of a simple, innovative, relatively low-cost protocol based on microfluidic technology and next-generation sequencing. A total of 704 variants (237 different) were identified along VWF, 155 of which had not been previously recorded in the international mutation database. The potential pathogenic effect of these variants was assessed by in silico analysis. Furthermore, four short tandem repeats were analyzed in order to evaluate the ancestral origin of recurrent mutations. The outcome of genetic analysis allowed for the reclassification of 110 patients, identification of 37 asymptomatic carriers (important for genetic counseling) and re-inclusion of 43 patients previously excluded by phenotyping results. In total, 480 patients were definitively diagnosed. Candidate mutations were identified in all patients except 13 type 1 von Willebrand disease, yielding a high genotype-phenotype correlation. Our data reinforce the capital importance and usefulness of genetics in von Willebrand disease diagnostics. The progressive implementation of molecular study as the first-line test for routine diagnosis of this condition will lead to increasingly more personalized and effective care for this patient population. PMID:28971901

Molecular and clinical profile of von Willebrand disease in Spain (PCM-EVW-ES): comprehensive genetic analysis by next-generation sequencing of 480 patients.

PubMed

Borràs, Nina; Batlle, Javier; Pérez-Rodríguez, Almudena; López-Fernández, María Fernanda; Rodríguez-Trillo, Ángela; Lourés, Esther; Cid, Ana Rosa; Bonanad, Santiago; Cabrera, Noelia; Moret, Andrés; Parra, Rafael; Mingot-Castellano, María Eva; Balda, Ignacia; Altisent, Carme; Pérez-Montes, Rocío; Fisac, Rosa María; Iruín, Gemma; Herrero, Sonia; Soto, Inmaculada; de Rueda, Beatriz; Jiménez-Yuste, Víctor; Alonso, Nieves; Vilariño, Dolores; Arija, Olga; Campos, Rosa; Paloma, María José; Bermejo, Nuria; Berrueco, Rubén; Mateo, José; Arribalzaga, Karmele; Marco, Pascual; Palomo, Ángeles; Sarmiento, Lizheidy; Iñigo, Belén; Nieto, María Del Mar; Vidal, Rosa; Martínez, María Paz; Aguinaco, Reyes; César, Jesús María; Ferreiro, María; García-Frade, Javier; Rodríguez-Huerta, Ana María; Cuesta, Jorge; Rodríguez-González, Ramón; García-Candel, Faustino; Cornudella, Rosa; Aguilar, Carlos; Vidal, Francisco; Corrales, Irene

2017-12-01

Molecular diagnosis of patients with von Willebrand disease is pending in most populations due to the complexity and high cost of conventional molecular analyses. The need for molecular and clinical characterization of von Willebrand disease in Spain prompted the creation of a multicenter project (PCM-EVW-ES) that resulted in the largest prospective cohort study of patients with all types of von Willebrand disease. Molecular analysis of relevant regions of the VWF , including intronic and promoter regions, was achieved in the 556 individuals recruited via the development of a simple, innovative, relatively low-cost protocol based on microfluidic technology and next-generation sequencing. A total of 704 variants (237 different) were identified along VWF , 155 of which had not been previously recorded in the international mutation database. The potential pathogenic effect of these variants was assessed by in silico analysis. Furthermore, four short tandem repeats were analyzed in order to evaluate the ancestral origin of recurrent mutations. The outcome of genetic analysis allowed for the reclassification of 110 patients, identification of 37 asymptomatic carriers (important for genetic counseling) and re-inclusion of 43 patients previously excluded by phenotyping results. In total, 480 patients were definitively diagnosed. Candidate mutations were identified in all patients except 13 type 1 von Willebrand disease, yielding a high genotype-phenotype correlation. Our data reinforce the capital importance and usefulness of genetics in von Willebrand disease diagnostics. The progressive implementation of molecular study as the first-line test for routine diagnosis of this condition will lead to increasingly more personalized and effective care for this patient population. Copyright© 2017 Ferrata Storti Foundation.

Evidence-Based Diagnosis and Treatment for Specific Learning Disabilities Involving Impairments in Written and/or Oral Language

ERIC Educational Resources Information Center

Berninger, Virginia W.; May, Maggie O'Malley

2011-01-01

Programmatic, multidisciplinary research provided converging brain, genetic, and developmental support for evidence-based diagnoses of three specific learning disabilities based on hallmark phenotypes (behavioral expression of underlying genotypes) with treatment relevance: dysgraphia (impaired legible automatic letter writing, orthographic…

Relating drug–protein interaction network with drug side effects

PubMed Central

Mizutani, Sayaka; Pauwels, Edouard; Stoven, Véronique; Goto, Susumu; Yamanishi, Yoshihiro

2012-01-01

Motivation: Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system–wide approaches for linking different scales of drug actions; namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs. Results: We performed a large-scale analysis to extract correlated sets of targeted proteins and side effects, based on the co-occurrence of drugs in protein-binding profiles and side effect profiles, using sparse canonical correlation analysis. The analysis of 658 drugs with the two profiles for 1368 proteins and 1339 side effects led to the extraction of 80 correlated sets. Enrichment analyses using KEGG and Gene Ontology showed that most of the correlated sets were significantly enriched with proteins that are involved in the same biological pathways, even if their molecular functions are different. This allowed for a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. The extracted side effects can be regarded as possible phenotypic outcomes by drugs targeting the proteins that appear in the same correlated set. The proposed method is expected to be useful for predicting potential side effects of new drug candidate compounds based on their protein-binding profiles. Supplementary information: Datasets and all results are available at http://web.kuicr.kyoto-u.ac.jp/supp/smizutan/target-effect/. Availability: Software is available at the above supplementary website. Contact: yamanishi@bioreg.kyushu-u.ac.jp, or goto@kuicr.kyoto-u.ac.jp PMID:22962476

Functional polymorphisms in the CYP2C19 gene contribute to digestive system cancer risk: evidence from 11,042 subjects.

PubMed

Zhou, Bo; Song, Zhenshun; Qian, Mingping; Li, Liang; Gong, Jian; Zou, Shaowu

2013-01-01

CYP2C19 belongs to the cytochrome P450 superfamily of enzymes involved in activating and detoxifying many carcinogens and endogenous compounds, which has attracted considerable attention as a candidate gene for digestive system cancer. CYP2C19 has two main point mutation sites (CYP2C19*2, CYP2C19*3) leading to poor metabolizer (PM) phenotype. In the past decade, the relationship between CYP2C19 polymorphism and digestive system cancer has been reported in various ethnic groups; however, these studies have yielded contradictory results. To clarify this inconsistency, we performed this meta-analysis. Databases including Pubmed, EMBASE, Web of Science and China National Knowledge Infrastructure (CNKI) were searched to find relevant studies. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association. In total, 18 studies with 4,414 cases and 6,628 controls were included. Overall, significantly elevated digestive system cancer risk was associated CYP2C19 PM with OR of 1.66 (95%CI: 1.31-2.10, P<10(-5)) when all studies were pooled into the meta-analysis. There was strong evidence of heterogeneity (P = 0.006), which largely disappeared after stratification by cancer type. In the stratified analyses according to cancer type, ethnicity, control source and sample size, significantly increased risks were found. In summary, our meta-analysis suggested that the PM phenotype caused by the variation on CYP2C19 gene is associated with increased risk of digestive system cancer, especially in East Asians.

Gait analysis in a mouse model resembling Leigh disease.

PubMed

de Haas, Ria; Russel, Frans G; Smeitink, Jan A

2016-01-01

Leigh disease (LD) is one of the clinical phenotypes of mitochondrial OXPHOS disorders and also known as sub-acute necrotizing encephalomyelopathy. The disease has an incidence of 1 in 77,000 live births. Symptoms typically begin early in life and prognosis for LD patients is poor. Currently, no clinically effective treatments are available. Suitable animal and cellular models are necessary for the understanding of the neuropathology and the development of successful new therapeutic strategies. In this study we used the Ndufs4 knockout (Ndufs4(-/-)) mouse, a model of mitochondrial complex I deficiency. Ndusf4(-/-) mice exhibit progressive neurodegeneration, which closely resemble the human LD phenotype. When dissecting behavioral abnormalities in animal models it is of great importance to apply translational tools that are clinically relevant. To distinguish gait abnormalities in patients, simple walking tests can be assessed, but in animals this is not easy. This study is the first to demonstrate automated CatWalk gait analysis in the Ndufs4(-/-) mouse model. Marked differences were noted between Ndufs4(-/-) and control mice in dynamic, static, coordination and support parameters. Variation of walking speed was significantly increased in Ndufs4(-/-) mice, suggesting hampered and uncoordinated gait. Furthermore, decreased regularity index, increased base of support and changes in support were noted in the Ndufs4(-/-) mice. Here, we report the ability of the CatWalk system to sensitively assess gait abnormalities in Ndufs4(-/-) mice. This objective gait analysis can be of great value for intervention and drug efficacy studies in animal models for mitochondrial disease. Copyright © 2015 Elsevier B.V. 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

YPD™, PombePD™ and WormPD™: model organism volumes of the BioKnowledge™ Library, an integrated resource for protein information

PubMed Central

Costanzo, Maria C.; Crawford, Matthew E.; Hirschman, Jodi E.; Kranz, Janice E.; Olsen, Philip; Robertson, Laura S.; Skrzypek, Marek S.; Braun, Burkhard R.; Hopkins, Kelley Lennon; Kondu, Pinar; Lengieza, Carey; Lew-Smith, Jodi E.; Tillberg, Michael; Garrels, James I.

2001-01-01

The BioKnowledge Library is a relational database and web site (http://www.proteome.com) composed of protein-specific information collected from the scientific literature. Each Protein Report on the web site summarizes and displays published information about a single protein, including its biochemical function, role in the cell and in the whole organism, localization, mutant phenotype and genetic interactions, regulation, domains and motifs, interactions with other proteins and other relevant data. This report describes four species-specific volumes of the BioKnowledge Library, concerned with the model organisms Saccharo­myces cerevisiae (YPD), Schizosaccharomyces pombe (PombePD) and Caenorhabditis elegans (WormPD), and with the fungal pathogen Candida albicans (CalPD™). Protein Reports of each species are unified in format, easily searchable and extensively cross-referenced between species. The relevance of these comprehensively curated resources to analysis of proteins in other species is discussed, and is illustrated by a survey of model organism proteins that have similarity to human proteins involved in disease. PMID:11125054

Towards an Age-Phenome Knowledge-base

PubMed Central

2011-01-01

Background Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages. Results Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction. Conclusions The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes. PMID:21651792

Autism Spectrum and Obsessive–Compulsive Disorders: OC Behaviors, Phenotypes and Genetics

PubMed Central

Jacob, Suma; Landeros-Weisenberger, Angeli; Leckman, James F.

2014-01-01

Autism spectrum disorders (ASDs) are a phenotypically and etiologically heterogeneous set of disorders that include obsessive–compulsive behaviors (OCB) that partially overlap with symptoms associated with obsessive–compulsive disorder (OCD). The OCB seen in ASD vary depending on the individual’s mental and chronological age as well as the etiology of their ASD. Although progress has been made in the measurement of the OCB associated with ASD, more work is needed including the potential identification of heritable endophenotypes. Likewise, important progress toward the understanding of genetic influences in ASD has been made by greater refinement of relevant phenotypes using a broad range of study designs, including twin and family-genetic studies, parametric and nonparametric linkage analyses, as well as candidate gene studies and the study of rare genetic variants. These genetic analyses could lead to the refinement of the OCB phenotypes as larger samples are studied and specific associations are replicated. Like ASD, OCB are likely to prove to be multidimensional and polygenic. Some of the vulnerability genes may prove to be generalist genes influencing the phenotypic expression of both ASD and OCD while others will be specific to subcomponents of the ASD phenotype. In order to discover molecular and genetic mechanisms, collaborative approaches need to generate shared samples, resources, novel genomic technologies, as well as more refined phenotypes and innovative statistical approaches. There is a growing need to identify the range of molecular pathways involved in OCB related to ASD in order to develop novel treatment interventions. PMID:20029829

The polycystic ovary syndrome: a position statement from the European Society of Endocrinology.

PubMed

Conway, Gerard; Dewailly, Didier; Diamanti-Kandarakis, Evanthia; Escobar-Morreale, Héctor F; Franks, Stephen; Gambineri, Alessandra; Kelestimur, Fahrettin; Macut, Djuro; Micic, Dragan; Pasquali, Renato; Pfeifer, Marija; Pignatelli, Duarte; Pugeat, Michel; Yildiz, Bulent O

2014-10-01

Polycystic ovary syndrome (PCOS) is the most common ovarian disorder associated with androgen excess in women, which justifies the growing interest of endocrinologists. Great efforts have been made in the last 2 decades to define the syndrome. The presence of three different definitions for the diagnosis of PCOS reflects the phenotypic heterogeneity of the syndrome. Major criteria are required for the diagnosis, which in turn identifies different phenotypes according to the combination of different criteria. In addition, the relevant impact of metabolic issues, specifically insulin resistance and obesity, on the pathogenesis of PCOS, and the susceptibility to develop earlier than expected glucose intolerance states, including type 2 diabetes, has supported the notion that these aspects should be considered when defining the PCOS phenotype and planning potential therapeutic strategies in an affected subject. This paper offers a critical endocrine and European perspective on the debate on the definition of PCOS and summarises all major aspects related to aetiological factors, including early life events, potentially involved in the development of the disorder. Diagnostic tools of PCOS are also discussed, with emphasis on the laboratory evaluation of androgens and other potential biomarkers of ovarian and metabolic dysfunctions. We have also paid specific attention to the role of obesity, sleep disorders and neuropsychological aspects of PCOS and on the relevant pathogenetic aspects of cardiovascular risk factors. In addition, we have discussed how to target treatment choices based according to the phenotype and individual patient's needs. Finally, we have suggested potential areas of translational and clinical research for the future with specific emphasis on hormonal and metabolic aspects of PCOS. © 2014 European Society of Endocrinology.

Donor‐Dependent and Other Nondefined Factors Have Greater Influence on the Hepatic Phenotype Than the Starting Cell Type in Induced Pluripotent Stem Cell Derived Hepatocyte‐Like Cells

PubMed Central

Heslop, James A.; Kia, Richard; Pridgeon, Christopher S.; Sison‐Young, Rowena L.; Liloglou, Triantafillos; Elmasry, Mohamed; Fenwick, Stephen W.; Mills, John S.; Kitteringham, Neil R.; Park, Bong K.

2017-01-01

Abstract Drug‐induced liver injury is the greatest cause of post‐marketing drug withdrawal; therefore, substantial resources are directed toward triaging potentially dangerous new compounds at all stages of drug development. One of the major factors preventing effective screening of new compounds is the lack of a predictive in vitro model of hepatotoxicity. Primary human hepatocytes offer a metabolically relevant model for which the molecular initiating events of hepatotoxicity can be examined; however, these cells vary greatly between donors and dedifferentiate rapidly in culture. Induced pluripotent stem cell (iPSC)‐derived hepatocyte‐like cells (HLCs) offer a reproducible, physiologically relevant and genotypically normal model cell; however, current differentiation protocols produce HLCs with a relatively immature phenotype. During the reprogramming of somatic cells, the epigenome undergoes dramatic changes; however, this “resetting” is a gradual process, resulting in an altered differentiation propensity, skewed toward the lineage of origin, particularly in early passage cultures. We, therefore, performed a comparison of human hepatocyte‐ and dermal fibroblast‐derived iPSCs, assessing the impact of epigenetic memory at all stages of HLC differentiation. These results provide the first isogenic assessment of the starting cell type in human iPSC‐derived HLCs. Despite a trend toward improvement in hepatic phenotype in albumin secretion and gene expression, few significant differences in hepatic differentiation capacity were found between hepatocyte and fibroblast‐derived iPSCs. We conclude that the donor and inter‐clonal differences have a greater influence on the hepatocyte phenotypic maturity than the starting cell type. Therefore, it is not necessary to use human hepatocytes for generating iPSC‐derived HLCs. Stem Cells Translational Medicine 2017;6:1321–1331 PMID:28456008

Absence of deficits in social behaviors and ultrasonic vocalizations in later generations of mice lacking neuroligin4.

PubMed

Ey, E; Yang, M; Katz, A M; Woldeyohannes, L; Silverman, J L; Leblond, C S; Faure, P; Torquet, N; Le Sourd, A-M; Bourgeron, T; Crawley, J N

2012-11-01

Mutations in NLGN4X have been identified in individuals with autism spectrum disorders and other neurodevelopmental disorders. A previous study reported that adult male mice lacking neuroligin4 (Nlgn4) displayed social approach deficits in the three-chambered test, altered aggressive behaviors and reduced ultrasonic vocalizations. To replicate and extend these findings, independent comprehensive analyses of autism-relevant behavioral phenotypes were conducted in later generations of the same line of Nlgn4 mutant mice at the National Institute of Mental Health in Bethesda, MD, USA and at the Institut Pasteur in Paris, France. Adult social approach was normal in all three genotypes of Nlgn4 mice tested at both sites. Reciprocal social interactions in juveniles were similarly normal across genotypes. No genotype differences were detected in ultrasonic vocalizations in pups separated from the nest or in adults during reciprocal social interactions. Anxiety-like behaviors, self-grooming, rotarod and open field exploration did not differ across genotypes, and measures of developmental milestones and general health were normal. Our findings indicate an absence of autism-relevant behavioral phenotypes in subsequent generations of Nlgn4 mice tested at two locations. Testing environment and methods differed from the original study in some aspects, although the presence of normal sociability was seen in all genotypes when methods taken from Jamain et al. (2008) were used. The divergent results obtained from this study indicate that phenotypes may not be replicable across breeding generations, and highlight the significant roles of environmental, generational and/or procedural factors on behavioral phenotypes. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

A novel Markov Blanket-based repeated-fishing strategy for capturing phenotype-related biomarkers in big omics data.

PubMed

Li, Hongkai; Yuan, Zhongshang; Ji, Jiadong; Xu, Jing; Zhang, Tao; Zhang, Xiaoshuai; Xue, Fuzhong

2016-03-09

We propose a novel Markov Blanket-based repeated-fishing strategy (MBRFS) in attempt to increase the power of existing Markov Blanket method (DASSO-MB) and maintain its advantages in omic data analysis. Both simulation and real data analysis were conducted to assess its performances by comparing with other methods including χ(2) test with Bonferroni and B-H adjustment, least absolute shrinkage and selection operator (LASSO) and DASSO-MB. A serious of simulation studies showed that the true discovery rate (TDR) of proposed MBRFS was always close to zero under null hypothesis (odds ratio = 1 for each SNPs) with excellent stability in all three scenarios of independent phenotype-related SNPs without linkage disequilibrium (LD) around them, correlated phenotype-related SNPs without LD around them, and phenotype-related SNPs with strong LD around them. As expected, under different odds ratio and minor allel frequency (MAFs), MBRFS always had the best performances in capturing the true phenotype-related biomarkers with higher matthews correlation coefficience (MCC) for all three scenarios above. More importantly, since proposed MBRFS using the repeated fishing strategy, it still captures more phenotype-related SNPs with minor effects when non-significant phenotype-related SNPs emerged under χ(2) test after Bonferroni multiple correction. The various real omics data analysis, including GWAS data, DNA methylation data, gene expression data and metabolites data, indicated that the proposed MBRFS always detected relatively reasonable biomarkers. Our proposed MBRFS can exactly capture the true phenotype-related biomarkers with the reduction of false negative rate when the phenotype-related biomarkers are independent or correlated, as well as the circumstance that phenotype-related biomarkers are associated with non-phenotype-related ones.

Sexual dimorphism of AMBRA1-related autistic features in human and mouse.

PubMed

Mitjans, M; Begemann, M; Ju, A; Dere, E; Wüstefeld, L; Hofer, S; Hassouna, I; Balkenhol, J; Oliveira, B; van der Auwera, S; Tammer, R; Hammerschmidt, K; Völzke, H; Homuth, G; Cecconi, F; Chowdhury, K; Grabe, H; Frahm, J; Boretius, S; Dandekar, T; Ehrenreich, H

2017-10-10

Ambra1 is linked to autophagy and neurodevelopment. Heterozygous Ambra1 deficiency induces autism-like behavior in a sexually dimorphic manner. Extraordinarily, autistic features are seen in female mice only, combined with stronger Ambra1 protein reduction in brain compared to males. However, significance of AMBRA1 for autistic phenotypes in humans and, apart from behavior, for other autism-typical features, namely early brain enlargement or increased seizure propensity, has remained unexplored. Here we show in two independent human samples that a single normal AMBRA1 genotype, the intronic SNP rs3802890-AA, is associated with autistic features in women, who also display lower AMBRA1 mRNA expression in peripheral blood mononuclear cells relative to female GG carriers. Located within a non-coding RNA, likely relevant for mRNA and protein interaction, rs3802890 (A versus G allele) may affect its stability through modification of folding, as predicted by in silico analysis. Searching for further autism-relevant characteristics in Ambra1 +/- mice, we observe reduced interest of female but not male mutants regarding pheromone signals of the respective other gender in the social intellicage set-up. Moreover, altered pentylentetrazol-induced seizure propensity, an in vivo readout of neuronal excitation-inhibition dysbalance, becomes obvious exclusively in female mutants. Magnetic resonance imaging reveals mild prepubertal brain enlargement in both genders, uncoupling enhanced brain dimensions from the primarily female expression of all other autistic phenotypes investigated here. These data support a role of AMBRA1/Ambra1 partial loss-of-function genotypes for female autistic traits. Moreover, they suggest Ambra1 heterozygous mice as a novel multifaceted and construct-valid genetic mouse model for female autism.

Systems Toxicology: Real World Applications and Opportunities.

PubMed

Hartung, Thomas; FitzGerald, Rex E; Jennings, Paul; Mirams, Gary R; Peitsch, Manuel C; Rostami-Hodjegan, Amin; Shah, Imran; Wilks, Martin F; Sturla, Shana J

2017-04-17

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams ("big data"), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity.

Systems Toxicology: Real World Applications and Opportunities

PubMed Central

2017-01-01

Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized from empirical end points to describing modes of action as adverse outcome pathways and perturbed networks. Toward this aim, Systems Toxicology entails the integration of in vitro and in vivo toxicity data with computational modeling. This evolving approach depends critically on data reliability and relevance, which in turn depends on the quality of experimental models and bioanalysis techniques used to generate toxicological data. Systems Toxicology involves the use of large-scale data streams (“big data”), such as those derived from omics measurements that require computational means for obtaining informative results. Thus, integrative analysis of multiple molecular measurements, particularly acquired by omics strategies, is a key approach in Systems Toxicology. In recent years, there have been significant advances centered on in vitro test systems and bioanalytical strategies, yet a frontier challenge concerns linking observed network perturbations to phenotypes, which will require understanding pathways and networks that give rise to adverse responses. This summary perspective from a 2016 Systems Toxicology meeting, an international conference held in the Alps of Switzerland, describes the limitations and opportunities of selected emerging applications in this rapidly advancing field. Systems Toxicology aims to change the basis of how adverse biological effects of xenobiotics are characterized, from empirical end points to pathways of toxicity. This requires the integration of in vitro and in vivo data with computational modeling. Test systems and bioanalytical technologies have made significant advances, but ensuring data reliability and relevance is an ongoing concern. The major challenge facing the new pathway approach is determining how to link observed network perturbations to phenotypic toxicity. PMID:28362102

A Range Finding Protocol to Support Design for Transcriptomics Experimentation: Examples of In-Vitro and In-Vivo Murine UV Exposure

PubMed Central

van Oostrom, Conny T.; Jonker, Martijs J.; de Jong, Mark; Dekker, Rob J.; Rauwerda, Han; Ensink, Wim A.; de Vries, Annemieke; Breit, Timo M.

2014-01-01

In transcriptomics research, design for experimentation by carefully considering biological, technological, practical and statistical aspects is very important, because the experimental design space is essentially limitless. Usually, the ranges of variable biological parameters of the design space are based on common practices and in turn on phenotypic endpoints. However, specific sub-cellular processes might only be partially reflected by phenotypic endpoints or outside the associated parameter range. Here, we provide a generic protocol for range finding in design for transcriptomics experimentation based on small-scale gene-expression experiments to help in the search for the right location in the design space by analyzing the activity of already known genes of relevant molecular mechanisms. Two examples illustrate the applicability: in-vitro UV-C exposure of mouse embryonic fibroblasts and in-vivo UV-B exposure of mouse skin. Our pragmatic approach is based on: framing a specific biological question and associated gene-set, performing a wide-ranged experiment without replication, eliminating potentially non-relevant genes, and determining the experimental ‘sweet spot’ by gene-set enrichment plus dose-response correlation analysis. Examination of many cellular processes that are related to UV response, such as DNA repair and cell-cycle arrest, revealed that basically each cellular (sub-) process is active at its own specific spot(s) in the experimental design space. Hence, the use of range finding, based on an affordable protocol like this, enables researchers to conveniently identify the ‘sweet spot’ for their cellular process of interest in an experimental design space and might have far-reaching implications for experimental standardization. PMID:24823911

Use of Multivariate Linkage Analysis for Dissection of a Complex Cognitive Trait

PubMed Central

Marlow, Angela J.; Fisher, Simon E.; Francks, Clyde; MacPhie, I. Laurence; Cherny, Stacey S.; Richardson, Alex J.; Talcott, Joel B.; Stein, John F.; Monaco, Anthony P.; Cardon, Lon R.

2003-01-01

Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits. PMID:12587094

Bringing in vitro analysis closer to in vivo: Studying doxorubicin toxicity and associated mechanisms in 3D human microtissues with PBPK-based dose modelling.

PubMed

Verheijen, Marcha; Schrooders, Yannick; Gmuender, Hans; Nudischer, Ramona; Clayton, Olivia; Hynes, James; Niederer, Steven; Cordes, Henrik; Kuepfer, Lars; Kleinjans, Jos; Caiment, Florian

2018-05-24

Doxorubicin (DOX) is a chemotherapeutic agent of which the medical use is limited due to cardiotoxicity. While acute cardiotoxicity is reversible, chronic cardiotoxicity is persistent or progressive, dose-dependent and irreversible. While DOX mechanisms of action are not fully understood yet, 3 toxicity processes are known to occur in vivo: cardiomyocyte dysfunction, mitochondrial dysfunction and cell death. We present an in vitro experimental design aimed at detecting DOX-induced cardiotoxicity by obtaining a global view of the induced molecular mechanisms through RNA-sequencing. To better reflect the in vivo situation, human 3D cardiac microtissues were exposed to physiologically-based pharmacokinetic (PBPK) relevant doses of DOX for 2 weeks. We analysed a therapeutic and a toxic dosing profile. Transcriptomics analysis revealed significant gene expression changes in pathways related to "striated muscle contraction" and "respiratory electron transport", thus suggesting mitochondrial dysfunction as an underlying mechanism for cardiotoxicity. Furthermore, expression changes in mitochondrial processes differed significantly between the doses. Therapeutic dose reflects processes resembling the phenotype of delayed chronic cardiotoxicity, while toxic doses resembled acute cardiotoxicity. Overall, these results demonstrate the capability of our innovative in vitro approach to detect the three known mechanisms of DOX leading to toxicity, thus suggesting its potential relevance for reflecting the patient situation. Our study also demonstrated the importance of applying physiologically relevant doses during toxicological research, since mechanisms of acute and chronic toxicity differ. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

PubMed

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Simultaneous Analysis of the Behavioural Phenotype, Physical Factors, and Parenting Stress in People with Cornelia De Lange Syndrome

ERIC Educational Resources Information Center

Wulffaert, J.; van Berckelaer-Onnes, I.; Kroonenberg, P.; Scholte, E.; Bhuiyan, Z.; Hennekam, R.

2009-01-01

Background: Studies into the phenotype of rare genetic syndromes largely rely on bivariate analysis. The aim of this study was to describe the phenotype of Cornelia de Lange syndrome (CdLS) in depth by examining a large number of variables with varying measurement levels. Virtually the only suitable multivariate technique for this is categorical…

A custom multi-modal sensor suite and data analysis pipeline for aerial field phenotyping

NASA Astrophysics Data System (ADS)

Bartlett, Paul W.; Coblenz, Lauren; Sherwin, Gary; Stambler, Adam; van der Meer, Andries

2017-05-01

Our group has developed a custom, multi-modal sensor suite and data analysis pipeline to phenotype crops in the field using unpiloted aircraft systems (UAS). This approach to high-throughput field phenotyping is part of a research initiative intending to markedly accelerate the breeding process for refined energy sorghum varieties. To date, single rotor and multirotor helicopters, roughly 14 kg in total weight, are being employed to provide sensor coverage over multiple hectaresized fields in tens of minutes. The quick, autonomous operations allow for complete field coverage at consistent plant and lighting conditions, with low operating costs. The sensor suite collects data simultaneously from six sensors and registers it for fusion and analysis. High resolution color imagery targets color and geometric phenotypes, along with lidar measurements. Long-wave infrared imagery targets temperature phenomena and plant stress. Hyperspectral visible and near-infrared imagery targets phenotypes such as biomass and chlorophyll content, as well as novel, predictive spectral signatures. Onboard spectrometers and careful laboratory and in-field calibration techniques aim to increase the physical validity of the sensor data throughout and across growing seasons. Off-line processing of data creates basic products such as image maps and digital elevation models. Derived data products include phenotype charts, statistics, and trends. The outcome of this work is a set of commercially available phenotyping technologies, including sensor suites, a fully integrated phenotyping UAS, and data analysis software. Effort is also underway to transition these technologies to farm management users by way of streamlined, lower cost sensor packages and intuitive software interfaces.

Asthma management: A new phenotype-based approach using presence of eosinophilia and allergy.

PubMed

Terl, M; Sedlák, V; Cap, P; Dvořáková, R; Kašák, V; Kočí, T; Novotna, B; Seberova, E; Panzner, P; Zindr, V

2017-09-01

Asthma is a heterogeneous disease. The Czech Pneumology and Allergology Societies commissioned 10 experts to review the literature and create joint national guidelines for managing asthma, reflecting this heterogeneity. The aim was to develop an easy-to-use diagnostic strategy as a rational approach to the widening opportunities for the use of phenotype-targeted therapy. The guidelines were presented on websites for public comments by members of both the societies. The reviewers' comments contributed to creating the final version of the guidelines. The key hallmark of the diagnostic approach is the pragmatic concept, which assesses the presence of allergy and eosinophilia in each asthmatic patient. The guidelines define three clinically relevant asthma phenotypes: eosinophilic allergic asthma, eosinophilic nonallergic asthma and noneosinophilic nonallergic asthma. The resulting multifunctional classification describing the severity, level of control and phenotype is the starting point for a comprehensive treatment strategy. The level of control is constantly confronted with the intensity of the common stepwise pharmacotherapy, and the concurrently included phenotyping is essential for phenotype-specific therapy. The concept of the asthma approach with assessing the presence of eosinophilia and allergy provides a way for more precise diagnosis, which is a prerequisite for using widening options of personalized therapy. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

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

PubMed

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

2012-09-01

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

Neurocarta: aggregating and sharing disease-gene relations for the neurosciences.

PubMed

Portales-Casamar, Elodie; Ch'ng, Carolyn; Lui, Frances; St-Georges, Nicolas; Zoubarev, Anton; Lai, Artemis Y; Lee, Mark; Kwok, Cathy; Kwok, Willie; Tseng, Luchia; Pavlidis, Paul

2013-02-26

Understanding the genetic basis of diseases is key to the development of better diagnoses and treatments. Unfortunately, only a small fraction of the existing data linking genes to phenotypes is available through online public resources and, when available, it is scattered across multiple access tools. Neurocarta is a knowledgebase that consolidates information on genes and phenotypes across multiple resources and allows tracking and exploring of the associations. The system enables automatic and manual curation of evidence supporting each association, as well as user-enabled entry of their own annotations. Phenotypes are recorded using controlled vocabularies such as the Disease Ontology to facilitate computational inference and linking to external data sources. The gene-to-phenotype associations are filtered by stringent criteria to focus on the annotations most likely to be relevant. Neurocarta is constantly growing and currently holds more than 30,000 lines of evidence linking over 7,000 genes to 2,000 different phenotypes. Neurocarta is a one-stop shop for researchers looking for candidate genes for any disorder of interest. In Neurocarta, they can review the evidence linking genes to phenotypes and filter out the evidence they're not interested in. In addition, researchers can enter their own annotations from their experiments and analyze them in the context of existing public annotations. Neurocarta's in-depth annotation of neurodevelopmental disorders makes it a unique resource for neuroscientists working on brain development.

Species-specific differences in adaptive phenotypic plasticity in an ecologically relevant trophic trait: hypertrophic lips in Midas cichlid fishes.

PubMed

Machado-Schiaffino, Gonzalo; Henning, Frederico; Meyer, Axel

2014-07-01

The spectacular species richness of cichlids and their diversity in morphology, coloration, and behavior have made them an ideal model for the study of speciation and adaptive evolution. Hypertrophic lips evolved repeatedly and independently in African and Neotropical cichlid radiations. Cichlids with hypertrophic lips forage predominantly in rocky crevices and it has been hypothesized that mechanical stress caused by friction could result in larger lips through phenotypic plasticity. To test the influence of the environment on the size and development of lips, we conducted a series of breeding and feeding experiments on Midas cichlids. Full-sibs of Amphilophus labiatus (thick-lipped) and Amphilophus citrinellus (thin-lipped) each were split into a control group which was fed food from the water column and a treatment group whose food was fixed to substrates. We found strong evidence for phenotypic plasticity on lip area in the thick-lipped species, but not in the thin-lipped species. Intermediate phenotypic values were observed in hybrids from thick- and thin-lipped species reared under "control" conditions. Thus, both a genetic, but also a phenotypic plastic component is involved in the development of hypertrophic lips in Neotropical cichlids. Moreover, species-specific adaptive phenotypic plasticity was found, suggesting that plasticity is selected for in recent thick-lipped species. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Trans-generational inheritance of herbivory-induced phenotypic changes in Brassica rapa

USDA-ARS?s Scientific Manuscript database

Biotic stress can induce plastic changes in fitness-relevant plant traits. Recently, it has been shown that such changes can be transmitted to subsequent generations. However, the occurrence and extent of transmission across different types of traits is still unexplored. Here, we assessed the emerge...

An Internet-Accessible DNA Sequence Database for Identifying Fusaria from Human and Animal Infections

USDA-ARS?s Scientific Manuscript database

Because less than one-third of clinically relevant fusaria can be accurately identified to species level using phenotypic data (i.e., morphological species recognition), we constructed a three-locus DNA sequence database to facilitate molecular identification of the 69 Fusarium species associated wi...

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases

NASA Astrophysics Data System (ADS)

Hoehndorf, Robert; Schofield, Paul N.; Gkoutos, Georgios V.

2015-06-01

Phenotypes are the observable characteristics of an organism arising from its response to the environment. Phenotypes associated with engineered and natural genetic variation are widely recorded using phenotype ontologies in model organisms, as are signs and symptoms of human Mendelian diseases in databases such as OMIM and Orphanet. Exploiting these resources, several computational methods have been developed for integration and analysis of phenotype data to identify the genetic etiology of diseases or suggest plausible interventions. A similar resource would be highly useful not only for rare and Mendelian diseases, but also for common, complex and infectious diseases. We apply a semantic text-mining approach to identify the phenotypes (signs and symptoms) associated with over 6,000 diseases. We evaluate our text-mined phenotypes by demonstrating that they can correctly identify known disease-associated genes in mice and humans with high accuracy. Using a phenotypic similarity measure, we generate a human disease network in which diseases that have similar signs and symptoms cluster together, and we use this network to identify closely related diseases based on common etiological, anatomical as well as physiological underpinnings.

PCAN: phenotype consensus analysis to support disease-gene association.

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

Phenotype detection in morphological mutant mice using deformation features.

PubMed

Roy, Sharmili; Liang, Xi; Kitamoto, Asanobu; Tamura, Masaru; Shiroishi, Toshihiko; Brown, Michael S

2013-01-01

Large-scale global efforts are underway to knockout each of the approximately 25,000 mouse genes and interpret their roles in shaping the mammalian embryo. Given the tremendous amount of data generated by imaging mutated prenatal mice, high-throughput image analysis systems are inevitable to characterize mammalian development and diseases. Current state-of-the-art computational systems offer only differential volumetric analysis of pre-defined anatomical structures between various gene-knockout mice strains. For subtle anatomical phenotypes, embryo phenotyping still relies on the laborious histological techniques that are clearly unsuitable in such big data environment. This paper presents a system that automatically detects known phenotypes and assists in discovering novel phenotypes in muCT images of mutant mice. Deformation features obtained from non-linear registration of mutant embryo to a normal consensus average image are extracted and analyzed to compute phenotypic and candidate phenotypic areas. The presented system is evaluated using C57BL/10 embryo images. All cases of ventricular septum defect and polydactyly, well-known to be present in this strain, are successfully detected. The system predicts potential phenotypic areas in the liver that are under active histological evaluation for possible phenotype of this mouse line.

Long-term phenotypic evolution of bacteria.

PubMed

Plata, Germán; Henry, Christopher S; Vitkup, Dennis

2015-01-15

For many decades comparative analyses of protein sequences and structures have been used to investigate fundamental principles of molecular evolution. In contrast, relatively little is known about the long-term evolution of species' phenotypic and genetic properties. This represents an important gap in our understanding of evolution, as exactly these proprieties play key roles in natural selection and adaptation to diverse environments. Here we perform a comparative analysis of bacterial growth and gene deletion phenotypes using hundreds of genome-scale metabolic models. Overall, bacterial phenotypic evolution can be described by a two-stage process with a rapid initial phenotypic diversification followed by a slow long-term exponential divergence. The observed average divergence trend, with approximately similar fractions of phenotypic properties changing per unit time, continues for billions of years. We experimentally confirm the predicted divergence trend using the phenotypic profiles of 40 diverse bacterial species across more than 60 growth conditions. Our analysis suggests that, at long evolutionary distances, gene essentiality is significantly more conserved than the ability to utilize different nutrients, while synthetic lethality is significantly less conserved. We also find that although a rapid phenotypic evolution is sometimes observed within the same species, a transition from high to low phenotypic similarity occurs primarily at the genus level.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays.

PubMed

Guyon, Laurent; Lajaunie, Christian; Fer, Frédéric; Bhajun, Ricky; Sulpice, Eric; Pinna, Guillaume; Campalans, Anna; Radicella, J Pablo; Rouillier, Philippe; Mary, Mélissa; Combe, Stéphanie; Obeid, Patricia; Vert, Jean-Philippe; Gidrol, Xavier

2015-09-18

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays

PubMed Central

Guyon, Laurent; Lajaunie, Christian; fer, Frédéric; bhajun, Ricky; sulpice, Eric; pinna, Guillaume; campalans, Anna; radicella, J. Pablo; rouillier, Philippe; mary, Mélissa; combe, Stéphanie; obeid, Patricia; vert, Jean-Philippe; gidrol, Xavier

2015-01-01

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection. PMID:26382112

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

Asthma in Latin America: the dawn of a new epidemic.

PubMed

Pitrez, Paulo M; Stein, Renato T

2008-10-01

Asthma is a heterogeneous disease with high morbidity worldwide. Unlike the low prevalence of asthma and allergy found in many developing countries, especially in rural settings, its prevalence in Latin America is high. In these sites, nonatopic asthma seems to be the most common phenotype observed among school-age children. Therefore, it seems that asthma in Latin America has some particular characteristics that will be presented and discussed in this article. The prevalence of asthma-like symptoms in childhood is high in many populations studied in Latin America with similar frequencies to those reported in more developed countries. However, the mechanisms and risk factors associated with nonatopic asthma, which is the most prevalent phenotype in this region, have been scarcely studied. The better understanding of asthma phenotypes that prevail in Latin America and the investigation of determining factor studies may help establish new diagnostic and therapeutic approaches. These findings should affect public health policies for this new asthma epidemic through the combination of the atopic and nonatopic phenotypes. We hope that this article sheds some new light into these important and most relevant questions.

Protein Interactome of Muscle Invasive Bladder Cancer

PubMed Central

Bhat, Akshay; Heinzel, Andreas; Mayer, Bernd; Perco, Paul; Mühlberger, Irmgard; Husi, Holger; Merseburger, Axel S.; Zoidakis, Jerome; Vlahou, Antonia; Schanstra, Joost P.; Mischak, Harald; Jankowski, Vera

2015-01-01

Muscle invasive bladder carcinoma is a complex, multifactorial disease caused by disruptions and alterations of several molecular pathways that result in heterogeneous phenotypes and variable disease outcome. Combining this disparate knowledge may offer insights for deciphering relevant molecular processes regarding targeted therapeutic approaches guided by molecular signatures allowing improved phenotype profiling. The aim of the study is to characterize muscle invasive bladder carcinoma on a molecular level by incorporating scientific literature screening and signatures from omics profiling. Public domain omics signatures together with molecular features associated with muscle invasive bladder cancer were derived from literature mining to provide 286 unique protein-coding genes. These were integrated in a protein-interaction network to obtain a molecular functional map of the phenotype. This feature map educated on three novel disease-associated pathways with plausible involvement in bladder cancer, namely Regulation of actin cytoskeleton, Neurotrophin signalling pathway and Endocytosis. Systematic integration approaches allow to study the molecular context of individual features reported as associated with a clinical phenotype and could potentially help to improve the molecular mechanistic description of the disorder. PMID:25569276

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.

Opportunities for collaborative phenotyping for disease resistance traits in a large beef cattle resource population.

PubMed

Thallman, R M; Kuehn, L A; Allan, M F; Bennett, G L; Koohmaraie, M

2008-01-01

The Germplasm Evaluation (GPE) Project at the US Meat Animal Research Center (USMARC) is planned to produce about 3,000 calves per year in support of the following objectives: identification and validation of genetic polymorphisms related to economically relevant traits (ERT), estimation of breed and heterosis effects among 16 breeds for ERT, and estimation of genetic correlations among ERT and physiological indicator traits (PIT). Opportunities exist for collaboration in the development and collection of PIT phenotypes for disease resistance. Other areas of potential collaboration include detailed diagnosis (identification of disease causing organisms, etc.) of treated animals, collaborative development of epidemiological statistical models that would extract more information from the records of diagnoses and treatments, or pharmacogenetics. Concentrating a variety of different phenotypes and research approaches on the same population makes each component much more valuable than it would be individually.

Activation of IRF1 in Human Adipocytes Leads to Phenotypes Associated with Metabolic Disease.

PubMed

Friesen, Max; Camahort, Raymond; Lee, Youn-Kyoung; Xia, Fang; Gerszten, Robert E; Rhee, Eugene P; Deo, Rahul C; Cowan, Chad A

2017-05-09

The striking rise of obesity-related metabolic disorders has focused attention on adipocytes as critical mediators of disease phenotypes. To better understand the role played by excess adipose in metabolic dysfunction it is crucial to decipher the transcriptional underpinnings of the low-grade adipose inflammation characteristic of diseases such as type 2 diabetes. Through employing a comparative transcriptomics approach, we identified IRF1 as differentially regulated between primary and in vitro-derived genetically matched adipocytes. This suggests a role as a mediator of adipocyte inflammatory phenotypes, similar to its function in other tissues. Utilizing adipose-derived mesenchymal progenitors we subsequently demonstrated that expression of IRF1 in adipocytes indeed contributes to upregulation of inflammatory processes, both in vitro and in vivo. This highlights IRF1's relevance to obesity-related inflammation and the resultant metabolic dysregulation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

The Emergence of Pan-Cancer CIMP and Its Elusive Interpretation

PubMed Central

Miller, Brendan F.; Sánchez-Vega, Francisco; Elnitski, Laura

2016-01-01

Epigenetic dysregulation is recognized as a hallmark of cancer. In the last 16 years, a CpG island methylator phenotype (CIMP) has been documented in tumors originating from different tissues. However, a looming question in the field is whether or not CIMP is a pan-cancer phenomenon or a tissue-specific event. Here, we give a synopsis of the history of CIMP and describe the pattern of DNA methylation that defines the CIMP phenotype in different cancer types. We highlight new conceptual approaches of classifying tumors based on CIMP in a cancer type-agnostic way that reveal the presence of distinct CIMP tumors in a multitude of The Cancer Genome Atlas (TCGA) datasets, suggesting that this phenotype may transcend tissue-type specificity. Lastly, we show evidence supporting the clinical relevance of CIMP-positive tumors and suggest that a common CIMP etiology may define new mechanistic targets in cancer treatment. PMID:27879658

The Emergence of Pan-Cancer CIMP and Its Elusive Interpretation.

PubMed

Miller, Brendan F; Sánchez-Vega, Francisco; Elnitski, Laura

2016-11-22

Epigenetic dysregulation is recognized as a hallmark of cancer. In the last 16 years, a CpG island methylator phenotype (CIMP) has been documented in tumors originating from different tissues. However, a looming question in the field is whether or not CIMP is a pan-cancer phenomenon or a tissue-specific event. Here, we give a synopsis of the history of CIMP and describe the pattern of DNA methylation that defines the CIMP phenotype in different cancer types. We highlight new conceptual approaches of classifying tumors based on CIMP in a cancer type-agnostic way that reveal the presence of distinct CIMP tumors in a multitude of The Cancer Genome Atlas (TCGA) datasets, suggesting that this phenotype may transcend tissue-type specificity. Lastly, we show evidence supporting the clinical relevance of CIMP-positive tumors and suggest that a common CIMP etiology may define new mechanistic targets in cancer treatment.

Mannosyltransferase is required for cell wall biosynthesis, morphology and control of asexual development in Neurospora crassa.

PubMed

Bowman, Shaun M; Piwowar, Amy; Ciocca, Maria; Free, Stephen J

2005-01-01

Two Neurospora mutants with a phenotype that includes a tight colonial growth pattern, an inability to form conidia and an inability to form protoperithecia have been isolated and characterized. The relevant mutations were mapped to the same locus on the sequenced Neurospora genome. The mutations responsible for the mutant phenotype then were identified by examining likely candidate genes from the mutant genomes at the mapped locus with PCR amplification and a sequencing assay. The results demonstrate that a map and sequence strategy is a feasible way to identify mutant genes in Neurospora. The gene responsible for the phenotype is a putative alpha-1,2-mannosyltransferase gene. The mutant cell wall has an altered composition demonstrating that the gene functions in cell wall biosynthesis. The results demonstrate that the mnt-1 gene is required for normal cell wall biosynthesis, morphology and for the regulation of asexual development.

Polymorphic Evolutionary Games.

PubMed

Fishman, Michael A

2016-06-07

In this paper, I present an analytical framework for polymorphic evolutionary games suitable for explicitly modeling evolutionary processes in diploid populations with sexual reproduction. The principal aspect of the proposed approach is adding diploid genetics cum sexual recombination to a traditional evolutionary game, and switching from phenotypes to haplotypes as the new game׳s pure strategies. Here, the relevant pure strategy׳s payoffs derived by summing the payoffs of all the phenotypes capable of producing gametes containing that particular haplotype weighted by the pertinent probabilities. The resulting game is structurally identical to the familiar Evolutionary Games with non-linear pure strategy payoffs (Hofbauer and Sigmund, 1998. Cambridge University Press), and can be analyzed in terms of an established analytical framework for such games. And these results can be translated into the terms of genotypic, and whence, phenotypic evolutionary stability pertinent to the original game. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring Genetic, Genomic, and Phenotypic Data at the Rat Genome Database

PubMed Central

Laulederkind, Stanley J. F.; Hayman, G. Thomas; Wang, Shur-Jen; Lowry, Timothy F.; Nigam, Rajni; Petri, Victoria; Smith, Jennifer R.; Dwinell, Melinda R.; Jacob, Howard J.; Shimoyama, Mary

2013-01-01

The laboratory rat, Rattus norvegicus, is an important model of human health and disease, and experimental findings in the rat have relevance to human physiology and disease. The Rat Genome Database (RGD, http://rgd.mcw.edu) is a model organism database that provides access to a wide variety of curated rat data including disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components for genes, quantitative trait loci, and strains. We present an overview of the database followed by specific examples that can be used to gain experience in employing RGD to explore the wealth of functional data available for the rat. PMID:23255149

[Current genetic issues and phenotypic variants in Kallmann syndrome].

PubMed

Gutiérrez-Amavizca, Bianca Ethel; Figuera, Luis E; Orozco-Castellanos, Ricardo

2012-01-01

Kallmann syndrome is characterized by hypogonadotropic hypogonadism and anosmia/hyposmia. The hypogonadotropic hypogonadism is due to deficiency of gonadotropin-releasing hormone, caused by a defect in the migration of neurons synthesizing gonadotropin-releasing hormone, and anosmia/hyposmia is related to the absence or hypoplasia of the olfactory bulb and tracts. Some patients may have other associated abnormalities such as renal agenesis, cleft palate, dental agenesis, synkinesis, shortening of metacarpal, sensory neural hearing loss and seizures. The aim of this paper is to present an updated review of the clinical and molecular basis, highlighting the relevance of knowledge of phenotypic variants in Kallmann syndrome.

Phenotypic landscape of non-conventional yeast species for different stress tolerance traits desirable in bioethanol fermentation.

PubMed

Mukherjee, Vaskar; Radecka, Dorota; Aerts, Guido; Verstrepen, Kevin J; Lievens, Bart; Thevelein, Johan M

2017-01-01

Non-conventional yeasts present a huge, yet barely exploited, resource of yeast biodiversity for industrial applications. This presents a great opportunity to explore alternative ethanol-fermenting yeasts that are more adapted to some of the stress factors present in the harsh environmental conditions in second-generation (2G) bioethanol fermentation. Extremely tolerant yeast species are interesting candidates to investigate the underlying tolerance mechanisms and to identify genes that when transferred to existing industrial strains could help to design more stress-tolerant cell factories. For this purpose, we performed a high-throughput phenotypic evaluation of a large collection of non-conventional yeast species to identify the tolerance limits of the different yeast species for desirable stress tolerance traits in 2G bioethanol production. Next, 12 multi-tolerant strains were selected and used in fermentations under different stressful conditions. Five strains out of which, showing desirable fermentation characteristics, were then evaluated in small-scale, semi-anaerobic fermentations with lignocellulose hydrolysates. Our results revealed the phenotypic landscape of many non-conventional yeast species which have not been previously characterized for tolerance to stress conditions relevant for bioethanol production. This has identified for each stress condition evaluated several extremely tolerant non- Saccharomyces yeasts. It also revealed multi-tolerance in several yeast species, which makes those species good candidates to investigate the molecular basis of a robust general stress tolerance. The results showed that some non-conventional yeast species have similar or even better fermentation efficiency compared to S. cerevisiae in the presence of certain stressful conditions. Prior to this study, our knowledge on extreme stress-tolerant phenotypes in non-conventional yeasts was limited to only few species. Our work has now revealed in a systematic way the potential of non- Saccharomyces species to emerge either as alternative host species or as a source of valuable genetic information for construction of more robust industrial S. serevisiae bioethanol production yeasts. Striking examples include yeast species like Pichia kudriavzevii and Wickerhamomyces anomalus that show very high tolerance to diverse stress factors. This large-scale phenotypic analysis has yielded a detailed database useful as a resource for future studies to understand and benefit from the molecular mechanisms underlying the extreme phenotypes of non-conventional yeast species.

Knock-down of pantothenate kinase 2 severely affects the development of the nervous and vascular system in zebrafish, providing new insights into PKAN disease

PubMed Central

Zizioli, Daniela; Tiso, Natascia; Guglielmi, Adele; Saraceno, Claudia; Busolin, Giorgia; Giuliani, Roberta; Khatri, Deepak; Monti, Eugenio; Borsani, Giuseppe; Argenton, Francesco; Finazzi, Dario

2016-01-01

Pantothenate Kinase Associated Neurodegeneration (PKAN) is an autosomal recessive disorder with mutations in the pantothenate kinase 2 gene (PANK2), encoding an essential enzyme for Coenzyme A (CoA) biosynthesis. The molecular connection between defects in this enzyme and the neurodegenerative phenotype observed in PKAN patients is still poorly understood. We exploited the zebrafish model to study the role played by the pank2 gene during embryonic development and get new insight into PKAN pathogenesis. The zebrafish orthologue of hPANK2 lies on chromosome 13, is a maternal gene expressed in all development stages and, in adult animals, is highly abundant in CNS, dorsal aorta and caudal vein. The injection of a splice-inhibiting morpholino induced a clear phenotype with perturbed brain morphology and hydrocephalus; edema was present in the heart region and caudal plexus, where hemorrhages with reduction of blood circulation velocity were detected. We characterized the CNS phenotype by studying the expression pattern of wnt1 and neurog1 neural markers and by use of the Tg(neurod:EGFP/sox10:dsRed) transgenic line. The results evidenced that downregulation of pank2 severely impairs neuronal development, particularly in the anterior part of CNS (telencephalon). Whole-mount in situ hybridization analysis of the endothelial markers cadherin-5 and fli1a, and use of Tg(fli1a:EGFP/gata1a:dsRed) transgenic line, confirmed the essential role of pank2 in the formation of the vascular system. The specificity of the morpholino-induced phenotype was proved by the restoration of a normal development in a high percentage of embryos co-injected with pank2 mRNA. Also, addition of pantethine or CoA, but not of vitamin B5, to pank2 morpholino-injected embryos rescued the phenotype with high efficiency. The zebrafish model indicates the relevance of pank2 activity and CoA homeostasis for normal neuronal development and functioning and provides evidence of an unsuspected role for this enzyme and its product in vascular development. PMID:26476142

Ab initio genotype–phenotype association reveals intrinsic modularity in genetic networks

PubMed Central

Slonim, Noam; Elemento, Olivier; Tavazoie, Saeed

2006-01-01

Microbial species express an astonishing diversity of phenotypic traits, behaviors, and metabolic capacities. However, our molecular understanding of these phenotypes is based almost entirely on studies in a handful of model organisms that together represent only a small fraction of this phenotypic diversity. Furthermore, many microbial species are not amenable to traditional laboratory analysis because of their exotic lifestyles and/or lack of suitable molecular genetic techniques. As an adjunct to experimental analysis, we have developed a computational information-theoretic framework that produces high-confidence gene–phenotype predictions using cross-species distributions of genes and phenotypes across 202 fully sequenced archaea and eubacteria. In addition to identifying the genetic basis of complex traits, our approach reveals the organization of these genes into generic preferentially co-inherited modules, many of which correspond directly to known enzymatic pathways, molecular complexes, signaling pathways, and molecular machines. PMID:16732191

In silico analysis of a disease-causing mutation in PCDH15 gene in a consanguineous Pakistani family with Usher phenotype.

PubMed

Saleha, Shamim; Ajmal, Muhammad; Jamil, Muhammad; Nasir, Muhammad; Hameed, Abdul

2016-01-01

To map Usher phenotype in a consanguineous Pakistani family and identify disease-associated mutation in a causative gene to establish phenotype-genotype correlation. A consanguineous Pakistani family in which Usher phenotype was segregating as an autosomal recessive trait was ascertained. On the basis of results of clinical investigations of affected members of this family disease was diagnosed as Usher syndrome (USH). To identify the locus responsible for the Usher phenotype in this family, genomic DNA from blood sample of each individual was genotyped using microsatellite Short Tandem Repeat (STR) markers for the known Usher syndrome loci. Then direct sequencing was performed to find out disease associated mutations in the candidate gene. By genetic linkage analysis, the USH phenotype of this family was mapped to PCDH15 locus on chromosome 10q21.1. Three different point mutations in exon 11 of PCDH15 were identified and one of them, c.1304A>C was found to be segregating with the disease phenotype in Pakistani family with Usher phenotype. This, c.1304A>C transversion mutation predicts an amino-acid substitution of aspartic acid with an alanine at residue number 435 (p.D435A) of its protein product. Moreover, in silico analysis revealed conservation of aspartic acid at position 435 and predicated this change as pathogenic. The identification of c.1304A>C pathogenic mutation in PCDH15 gene and its association with Usher syndrome in a consanguineous Pakistani family is the first example of a missense mutation of PCDH15 causing USH1 phenotype. In previous reports, it was hypothesized that severe mutations such as truncated protein of PCDH15 led to the Usher I phenotype and that missense variants are mainly responsible for non-syndromic hearing impairment.

Diagnostic Value of SLC26A4 Mutation Status in Hereditary Hearing Loss With EVA: A PRISMA-Compliant Meta-Analysis.

PubMed

Lu, Ya-Jie; Yao, Jun; Wei, Qin-Jun; Xing, Guang-Qian; Cao, Xin

2015-12-01

Many SLC26A4 mutations have been identified in patients with nonsyndromic enlarged vestibular aqueduct (EVA). However, the roles of SLC26A4 genotypes and phenotypes in hereditary deafness remain unexplained. This study aims to perform a meta-analysis based on the PRISMA statement to evaluate the diagnostic value of SLC26A4 mutant alleles and their correlations with multiethnic hearing phenotypes in EVA patients. The systematic literature search of the PubMed, Wiley Online Library, EMBASE, Web of Science, and Science Direct databases was conducted in English for articles published before July 15, 2015. Two investigators independently reviewed retrieved literature and evaluated eligibility. Discrepancy was resolved by discussion and a third investigator. Quality of included studies was evaluated using Newcastle-Ottawa Quality Assessment Scale. Data were synthesized using random-effect or fixed-effect models. The effect sizes were estimated by measuring odds ratios (ORs) with 95% confidence interval (CI). Twenty-five eligible studies involved 2294 cases with EVA data. A total of 272 SLC26A4 variations were found in deafness with EVA and 26 mutations of SCL26A4 had higher frequency. The overall OR was 646.71 (95% CI: 383.30-1091.15, P = 0.000). A total of 22 mutants were considered statistically significant in all ethnicities (ORs >1, P < 0.05). In particular, 8 mutants were specificity of EVA phenotypes in mutations of SLC26A4 for Asia deafness populations (ORs >1, P < 0.05), 4 mutants for Europe and North America (ORs >1, P < 0.05), and the IVS7-2A>G mutations in SLC26A4 were found to have the highest frequency in deafness individuals with EVA phenotype (62.42%). Moreover, subgroups for studies limited to cases with EVA phenotype, 11 mutants relevant risks (RRs) were P < 0.05, especially for IVS7-2A>G bi-allelic mutants assayed in a deafness population (RR = 0.880, P = 0.000). Diagnostic accuracy of SLC26A4 mutation results also identified the significant association of IVS7-2A>G (AUC = 0.99, 95% CI: 0.97-0.99) and p.H723R (AUC = 0.99, 95% CI: 0.98-1.00) detecting deafness with EVA. To conclude, the IVS7-2A>G and H723R in SLC26A4 present a significant predicting value and discriminatory ability for clinical use on diagnosis of EVA within a deafness population.

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data.

PubMed

Fan, Jean; Lee, Hae-Ock; Lee, Soohyun; Ryu, Da-Eun; Lee, Semin; Xue, Catherine; Kim, Seok Jin; Kim, Kihyun; Barkas, Nikolas; Park, Peter J; Park, Woong-Yang; Kharchenko, Peter V

2018-06-13

Characterization of intratumoral heterogeneity is critical to cancer therapy, as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct underlying subclonal architecture. Examining several tumor types, we show that HoneyBADGER is effective at identifying deletion, amplifications, and copy-neutral loss-of-heterozygosity events, and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Surprisingly, other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure, and were likely driven by alternative, non-clonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer. Published by Cold Spring Harbor Laboratory Press.

The Andean Adaptive Toolkit to Counteract High Altitude Maladaptation: Genome-Wide and Phenotypic Analysis of the Collas

PubMed Central

Eichstaedt, Christina A.; Antão, Tiago; Pagani, Luca; Cardona, Alexia; Kivisild, Toomas; Mormina, Maru

2014-01-01

During their migrations out of Africa, humans successfully colonised and adapted to a wide range of habitats, including extreme high altitude environments, where reduced atmospheric oxygen (hypoxia) imposes a number of physiological challenges. This study evaluates genetic and phenotypic variation in the Colla population living in the Argentinean Andes above 3500 m and compares it to the nearby lowland Wichí group in an attempt to pinpoint evolutionary mechanisms underlying adaptation to high altitude hypoxia. We genotyped 730,525 SNPs in 25 individuals from each population. In genome-wide scans of extended haplotype homozygosity Collas showed the strongest signal around VEGFB, which plays an essential role in the ischemic heart, and ELTD1, another gene crucial for heart development and prevention of cardiac hypertrophy. Moreover, pathway enrichment analysis showed an overrepresentation of pathways associated with cardiac morphology. Taken together, these findings suggest that Colla highlanders may have evolved a toolkit of adaptative mechanisms resulting in cardiac reinforcement, most likely to counteract the adverse effects of the permanently increased haematocrit and associated shear forces that characterise the Andean response to hypoxia. Regulation of cerebral vascular flow also appears to be part of the adaptive response in Collas. These findings are not only relevant to understand the evolution of hypoxia protection in high altitude populations but may also suggest new avenues for medical research into conditions where hypoxia constitutes a detrimental factor. PMID:24686296

Quantitative NMR Metabolite Profiling of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus Discriminates between Biofilm and Planktonic Phenotypes

PubMed Central

2015-01-01

Wound bioburden in the form of colonizing biofilms is a major contributor to nonhealing wounds. Staphylococcus aureus is a Gram-positive, facultative anaerobe commonly found in chronic wounds; however, much remains unknown about the basic physiology of this opportunistic pathogen, especially with regard to the biofilm phenotype. Transcriptomic and proteomic analysis of S. aureus biofilms have suggested that S. aureus biofilms exhibit an altered metabolic state relative to the planktonic phenotype. Herein, comparisons of extracellular and intracellular metabolite profiles detected by 1H NMR were conducted for methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) S. aureus strains grown as biofilm and planktonic cultures. Principal component analysis distinguished the biofilm phenotype from the planktonic phenotype, and factor loadings analysis identified metabolites that contributed to the statistical separation of the biofilm from the planktonic phenotype, suggesting that key features distinguishing biofilm from planktonic growth include selective amino acid uptake, lipid catabolism, butanediol fermentation, and a shift in metabolism from energy production to assembly of cell-wall components and matrix deposition. These metabolite profiles provide a basis for the development of metabolite biomarkers that distinguish between biofilm and planktonic phenotypes in S. aureus and have the potential for improved diagnostic and therapeutic use in chronic wounds. PMID:24809402

The Nutritional Phenotype in the Age of Metabolomics

PubMed Central

Zeisel, S. H.; Freake, H. C.; Bauman, D. E.; Bier, D. M.; Burrin, D. G.; German, J. B.; Klein, S.; Marquis, G. S.; Milner, J. A.; Pelto, G. H.; Rasmussen, K. M.

2008-01-01

The concept of the nutritional phenotype is proposed as a defined and integrated set of genetic, proteomic, metabolomic, functional, and behavioral factors that, when measured, form the basis for assessment of human nutritional status. The nutritional phenotype integrates the effects of diet on disease/wellness and is the quantitative indication of the paths by which genes and environment exert their effects on health. Advances in technology and in fundamental biological knowledge make it possible to define and measure the nutritional phenotype accurately in a cross section of individuals with various states of health and disease. This growing base of data and knowledge could serve as a resource for all scientific disciplines involved in human health. Nutritional sciences should be a prime mover in making key decisions that include: what environmental inputs (in addition to diet) are needed; what genes/proteins/metabolites should be measured; what end-point phenotypes should be included; and what informatics tools are available to ask nutritionally relevant questions. Nutrition should be the major discipline establishing how the elements of the nutritional phenotype vary as a function of diet. Nutritional sciences should also be instrumental in linking the elements that are responsive to diet with the functional outcomes in organisms that derive from them. As the first step in this initiative, a prioritized list of genomic, proteomic, and metabolomic as well as functional and behavioral measures that defines a practically useful subset of the nutritional phenotype for use in clinical and epidemiological investigations must be developed. From this list, analytic platforms must then be identified that are capable of delivering highly quantitative data on these endpoints. This conceptualization of a nutritional phenotype provides a concrete form and substance to the recognized future of nutritional sciences as a field addressing diet, integrated metabolism, and health. PMID:15987837

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness.

PubMed

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations ( R 2 = 0.61-0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis ( R 2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design.

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness

PubMed Central

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations (R2 = 0.61–0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis (R2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design. PMID:29163629

Automated interpretation of 3D laserscanned point clouds for plant organ segmentation.

PubMed

Wahabzada, Mirwaes; Paulus, Stefan; Kersting, Kristian; Mahlein, Anne-Katrin

2015-08-08

Plant organ segmentation from 3D point clouds is a relevant task for plant phenotyping and plant growth observation. Automated solutions are required to increase the efficiency of recent high-throughput plant phenotyping pipelines. However, plant geometrical properties vary with time, among observation scales and different plant types. The main objective of the present research is to develop a fully automated, fast and reliable data driven approach for plant organ segmentation. The automated segmentation of plant organs using unsupervised, clustering methods is crucial in cases where the goal is to get fast insights into the data or no labeled data is available or costly to achieve. For this we propose and compare data driven approaches that are easy-to-realize and make the use of standard algorithms possible. Since normalized histograms, acquired from 3D point clouds, can be seen as samples from a probability simplex, we propose to map the data from the simplex space into Euclidean space using Aitchisons log ratio transformation, or into the positive quadrant of the unit sphere using square root transformation. This, in turn, paves the way to a wide range of commonly used analysis techniques that are based on measuring the similarities between data points using Euclidean distance. We investigate the performance of the resulting approaches in the practical context of grouping 3D point clouds and demonstrate empirically that they lead to clustering results with high accuracy for monocotyledonous and dicotyledonous plant species with diverse shoot architecture. An automated segmentation of 3D point clouds is demonstrated in the present work. Within seconds first insights into plant data can be deviated - even from non-labelled data. This approach is applicable to different plant species with high accuracy. The analysis cascade can be implemented in future high-throughput phenotyping scenarios and will support the evaluation of the performance of different plant genotypes exposed to stress or in different environmental scenarios.

Identification of Differentially Methylated Sites with Weak Methylation Effects

PubMed Central

Tran, Hong; Zhu, Hongxiao; Wu, Xiaowei; Kim, Gunjune; Clarke, Christopher R.; Larose, Hailey; Haak, David C.; Westwood, James H.; Zhang, Liqing

2018-01-01

Deoxyribonucleic acid (DNA) methylation is an epigenetic alteration crucial for regulating stress responses. Identifying large-scale DNA methylation at single nucleotide resolution is made possible by whole genome bisulfite sequencing. An essential task following the generation of bisulfite sequencing data is to detect differentially methylated cytosines (DMCs) among treatments. Most statistical methods for DMC detection do not consider the dependency of methylation patterns across the genome, thus possibly inflating type I error. Furthermore, small sample sizes and weak methylation effects among different phenotype categories make it difficult for these statistical methods to accurately detect DMCs. To address these issues, the wavelet-based functional mixed model (WFMM) was introduced to detect DMCs. To further examine the performance of WFMM in detecting weak differential methylation events, we used both simulated and empirical data and compare WFMM performance to a popular DMC detection tool methylKit. Analyses of simulated data that replicated the effects of the herbicide glyphosate on DNA methylation in Arabidopsis thaliana show that WFMM results in higher sensitivity and specificity in detecting DMCs compared to methylKit, especially when the methylation differences among phenotype groups are small. Moreover, the performance of WFMM is robust with respect to small sample sizes, making it particularly attractive considering the current high costs of bisulfite sequencing. Analysis of empirical Arabidopsis thaliana data under varying glyphosate dosages, and the analysis of monozygotic (MZ) twins who have different pain sensitivities—both datasets have weak methylation effects of <1%—show that WFMM can identify more relevant DMCs related to the phenotype of interest than methylKit. Differentially methylated regions (DMRs) are genomic regions with different DNA methylation status across biological samples. DMRs and DMCs are essentially the same concepts, with the only difference being how methylation information across the genome is summarized. If methylation levels are determined by grouping neighboring cytosine sites, then they are DMRs; if methylation levels are calculated based on single cytosines, they are DMCs. PMID:29419727

The Versatile Mutational Resistome of Pseudomonas aeruginosa

PubMed Central

López-Causapé, Carla; Cabot, Gabriel; del Barrio-Tofiño, Ester; Oliver, Antonio

2018-01-01

One of the most striking features of Pseudomonas aeruginosa is its outstanding capacity for developing antimicrobial resistance to nearly all available antipseudomonal agents through the selection of chromosomal mutations, leading to the failure of the treatment of severe hospital-acquired or chronic infections. Recent whole-genome sequencing (WGS) data obtained from in vitro assays on the evolution of antibiotic resistance, in vivo monitoring of antimicrobial resistance development, analysis of sequential cystic fibrosis isolates, and characterization of widespread epidemic high-risk clones have provided new insights into the evolutionary dynamics and mechanisms of P. aeruginosa antibiotic resistance, thus motivating this review. Indeed, the analysis of the WGS mutational resistome has proven to be useful for understanding the evolutionary dynamics of classical resistance pathways and to describe new mechanisms for the majority of antipseudomonal classes, including β-lactams, aminoglycosides, fluoroquinolones, or polymixins. Beyond addressing a relevant scientific question, the analysis of the P. aeruginosa mutational resistome is expected to be useful, together with the analysis of the horizontally-acquired resistance determinants, for establishing the antibiotic resistance genotype, which should correlate with the antibiotic resistance phenotype and as such, it should be useful for the design of therapeutic strategies and for monitoring the efficacy of administered antibiotic treatments. However, further experimental research and new bioinformatics tools are still needed to overcome the interpretation limitations imposed by the complex interactions (including those leading to collateral resistance or susceptibility) between the 100s of genes involved in the mutational resistome, as well as the frequent difficulties for differentiating relevant mutations from simple natural polymorphisms. PMID:29681898

The Versatile Mutational Resistome of Pseudomonas aeruginosa.

PubMed

López-Causapé, Carla; Cabot, Gabriel; Del Barrio-Tofiño, Ester; Oliver, Antonio

2018-01-01

One of the most striking features of Pseudomonas aeruginosa is its outstanding capacity for developing antimicrobial resistance to nearly all available antipseudomonal agents through the selection of chromosomal mutations, leading to the failure of the treatment of severe hospital-acquired or chronic infections. Recent whole-genome sequencing (WGS) data obtained from in vitro assays on the evolution of antibiotic resistance, in vivo monitoring of antimicrobial resistance development, analysis of sequential cystic fibrosis isolates, and characterization of widespread epidemic high-risk clones have provided new insights into the evolutionary dynamics and mechanisms of P. aeruginosa antibiotic resistance, thus motivating this review. Indeed, the analysis of the WGS mutational resistome has proven to be useful for understanding the evolutionary dynamics of classical resistance pathways and to describe new mechanisms for the majority of antipseudomonal classes, including β-lactams, aminoglycosides, fluoroquinolones, or polymixins. Beyond addressing a relevant scientific question, the analysis of the P. aeruginosa mutational resistome is expected to be useful, together with the analysis of the horizontally-acquired resistance determinants, for establishing the antibiotic resistance genotype, which should correlate with the antibiotic resistance phenotype and as such, it should be useful for the design of therapeutic strategies and for monitoring the efficacy of administered antibiotic treatments. However, further experimental research and new bioinformatics tools are still needed to overcome the interpretation limitations imposed by the complex interactions (including those leading to collateral resistance or susceptibility) between the 100s of genes involved in the mutational resistome, as well as the frequent difficulties for differentiating relevant mutations from simple natural polymorphisms.

Exploring DSM-5 ADHD criteria beyond young adulthood: phenomenology, psychometric properties and prevalence in a large three-decade birth cohort.

PubMed

Vitola, E S; Bau, C H D; Salum, G A; Horta, B L; Quevedo, L; Barros, F C; Pinheiro, R T; Kieling, C; Rohde, L A; Grevet, E H

2017-03-01

There are still uncertainties on the psychometric validity of the DSM-5 attention deficit hyperactivity disorder (ADHD) criteria for its use in the adult population. We aim to describe the adult ADHD phenotype, to test the psychometric properties of the DSM-5 ADHD criteria, and to calculate the resulting prevalence in a population-based sample in their thirties. A cross-sectional evaluation using the DSM-5 ADHD criteria was carried out in 3574 individuals from the 1982 Pelotas Birth Cohort. Through receiver operator curve, latent and regression analyses, we obtained parameters on construct and discriminant validity. Still, prevalence rates were calculated for different sets of criteria. The latent analysis suggested that the adult ADHD phenotype is constituted mainly by inattentive symptoms. Also, inattention symptoms were the symptoms most associated with impairment. The best cut-off for diagnosis was four symptoms, but sensitivity and specificity for this cut-off was low. ADHD prevalence rates were 2.1% for DSM-5 ADHD criteria and 5.8% for ADHD disregarding age-of-onset criterion. The bi-dimensional ADHD structure proposed by the DSM demonstrated both construct and discriminant validity problems when used in the adult population, since inattention is a much more relevant feature in the adult phenotype. The use of the DSM-5 criteria results in a higher prevalence of ADHD when compared to those obtained by DSM-IV, and prevalence would increase almost threefold when considering current ADHD syndrome. These findings suggest a need for further refinement of the criteria for its use in the adult population.

[Molecular and clinical characterization of Colombian patients suffering from type III glycogen storage disease].

PubMed

Mantilla, Carolina; Toro, Mónica; Sepúlveda, María Elsy; Insuasty, Margarita; Di Filippo, Diana; López, Juan Álvaro; Baquero, Carolina; Navas, María Cristina; Arias, Andrés Augusto

2018-05-01

Type III glycogen storage disease (GSD III) is an autosomal recessive disorder in which a mutation in the AGL gene causes deficiency of the glycogen debranching enzyme. The disease is characterized by fasting hypoglycemia, hepatomegaly and progressive myopathy. Molecular analyses of AGL have indicated heterogeneity depending on ethnic groups. The full spectrum of AGL mutations in Colombia remains unclear. To describe the clinical and molecular characteristics of ten Colombian patients diagnosed with GSD III. We recruited ten Colombian children with a clinical and biochemical diagnosis of GSD III to undergo genetic testing. The full coding exons and the relevant exon-intron boundaries of the AGL underwent Sanger sequencing to identify mutation. All patients had the classic phenotype of the GSD III. Genetic analysis revealed a mutation p.Arg910X in two patients. One patient had the mutation p.Glu1072AspfsX36, and one case showed a compound heterozygosity with p.Arg910X and p.Glu1072AspfsX36 mutations. We also detected the deletion of AGL gene 3, 4, 5, and 6 exons in three patients. The in silico studies predicted that these defects are pathogenic. No mutations were detected in the amplified regions in three patients. We found mutations and deletions that explain the clinical phenotype of GSD III patients. This is the first report with a description of the clinical phenotype and the spectrum of AGL mutations in Colombian patients. This is important to provide appropriate prognosis and genetic counseling to the patient and their relatives.

TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities

PubMed Central

Carey, Allison F.; Rock, Jeremy M.; Krieger, Inna V.; Gagneux, Sebastien; Sacchettini, James C.; Fortune, Sarah M.

2018-01-01

Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains. PMID:29505613

Ram locus is a key regulator to trigger multidrug resistance in Enterobacter aerogenes.

PubMed

Molitor, Alexander; James, Chloë E; Fanning, Séamus; Pagès, Jean-Marie; Davin-Regli, Anne

2018-02-01

Several genetic regulators belonging to AraC family are involved in the emergence of MDR isolates of E. aerogenes due to alterations in membrane permeability. Compared with the genetic regulator Mar, RamA may be more relevant towards the emergence of antibiotic resistance. Focusing on the global regulators, Mar and Ram, we compared the amino acid sequences of the Ram repressor in 59 clinical isolates and laboratory strains of E. aerogenes. Sequence types were associated with their corresponding multi-drug resistance phenotypes and membrane protein expression profiles using MIC and immunoblot assays. Quantitative gene expression analysis of the different regulators and their targets (porins and efflux pump components) were performed. In the majority of the MDR isolates tested, ramR and a region upstream of ramA were mutated but marR or marA were unchanged. Expression and cloning experiments highlighted the involvement of the ram locus in the modification of membrane permeability. Overexpression of RamA lead to decreased porin production and increased expression of efflux pump components, whereas overexpression of RamR had the opposite effects. Mutations or deletions in ramR, leading to the overexpression of RamA predominated in clinical MDR E. aerogenes isolates and were associated with a higher-level of expression of efflux pump components. It was hypothesised that mutations in ramR, and the self-regulating region proximal to ramA, probably altered the binding properties of the RamR repressor; thereby producing the MDR phenotype. Consequently, mutability of RamR may play a key role in predisposing E. aerogenes towards the emergence of a MDR phenotype.

Genotype-Phenotype Correlation of Hereditary Erythrocytosis Mutations, a single center experience.

PubMed

Oliveira, Jennifer L; Coon, Lea M; Frederick, Lori A; Hein, Molly; Swanson, Kenneth C; Savedra, Michelle E; Porter, Tavanna R; Patnaik, Mrinal M; Tefferi, Ayalew; Pardanani, Animesh; Grebe, Stefan K; Viswanatha, David S; Hoyer, James D

2018-05-23

Hereditary erythrocytosis is associated with high oxygen affinity hemoglobin variants (HOAs), 2,3-bisphosphoglycerate deficiency and abnormalities in EPOR and the oxygen-sensing pathway proteins PHD, HIF2α, and VHL. Our laboratory has 40 years of experience with hemoglobin disorder testing and we have characterized HOAs using varied protein and molecular techniques including functional assessment by p50 analysis. In addition, we have more recently commenced adding the assessment of clinically relevant regions of the VHL, BPGM, EPOR, EGLN1 (PHD2), and EPAS1 (HIF2A) genes in a more comprehensive hereditary erythrocytosis panel of tests. Review of our experience confirms a wide spectrum of alterations associated with erythrocytosis which we have correlated with phenotypic and clinical features. Through generic hemoglobinopathy testing we have identified 762 patients with 81 distinct HOA Hb variants (61 β, 20 α), including 12 that were first identified by our laboratory. Of the 1192 cases received for an evaluation specific for hereditary erythrocytosis, approximately 12% had reportable alterations: 85 pathogenic/likely pathogenic mutations and 58 variants of unknown significance. Many have not been previously reported. Correlation with clinical and phenotypic data supports an algorithmic approach to guide economical evaluation; although, testing is expanded if the suspected causes are negative or of uncertain significance. Clinical features are similar and range from asymptomatic to recurrent headaches, fatigue, restless legs, chest pain, exertional dyspnea and thrombotic episodes. Many patients were chronically phlebotomized with reported relief of symptoms. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Hanseniaspora uvarum from Winemaking Environments Show Spatial and Temporal Genetic Clustering

PubMed Central

Albertin, Warren; Setati, Mathabatha E.; Miot-Sertier, Cécile; Mostert, Talitha T.; Colonna-Ceccaldi, Benoit; Coulon, Joana; Girard, Patrick; Moine, Virginie; Pillet, Myriam; Salin, Franck; Bely, Marina; Divol, Benoit; Masneuf-Pomarede, Isabelle

2016-01-01

Hanseniaspora uvarum is one of the most abundant yeast species found on grapes and in grape must, at least before the onset of alcoholic fermentation (AF) which is usually performed by Saccharomyces species. The aim of this study was to characterize the genetic and phenotypic variability within the H. uvarum species. One hundred and fifteen strains isolated from winemaking environments in different geographical origins were analyzed using 11 microsatellite markers and a subset of 47 strains were analyzed by AFLP. H. uvarum isolates clustered mainly on the basis of their geographical localization as revealed by microsatellites. In addition, a strong clustering based on year of isolation was evidenced, indicating that the genetic diversity of H. uvarum isolates was related to both spatial and temporal variations. Conversely, clustering analysis based on AFLP data provided a different picture with groups showing no particular characteristics, but provided higher strain discrimination. This result indicated that AFLP approaches are inadequate to establish the genetic relationship between individuals, but allowed good strain discrimination. At the phenotypic level, several extracellular enzymatic activities of enological relevance (pectinase, chitinase, protease, β-glucosidase) were measured but showed low diversity. The impact of environmental factors of enological interest (temperature, anaerobia, and copper addition) on growth was also assessed and showed poor variation. Altogether, this work provided both new analytical tool (microsatellites) and new insights into the genetic and phenotypic diversity of H. uvarum, a yeast species that has previously been identified as a potential candidate for co-inoculation in grape must, but whose intraspecific variability had never been fully assessed. PMID:26834719

Pearson syndrome.

PubMed

Farruggia, Piero; Di Marco, Floriana; Dufour, Carlo

2018-03-01

Pearson syndrome (PS) is a sporadic and very rare syndrome classically associated with single large-scale deletions of mitochondrial DNA and characterized by refractory sideroblastic anemia during infancy. Areas covered: This review presents an analysis and interpretation of the published data that forms the basis for our understanding of PS. PubMed, Google Scholarand Thompson ISI Web of Knowledge were searched for relevant data. Expert commentary: PS is a very rare mitochodrial disease that involves different organs and systems. Clinical phenotype is extremely variable and may change over the course of disease itself with the possibility both of worsenings and improvements. Outcome is invariably lethal and at the moment no cure is available. Accurate supportive treatment and follow up program in centres with experience in mitochondrial diseases and marrow failure may positively influence quality and duration of life.

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.

Exercise resistance across the prediabetes phenotypes: Impact on insulin sensitivity and substrate metabolism.

PubMed

Malin, Steven K; Liu, Zhenqi; Barrett, Eugene J; Weltman, Arthur

2016-03-01

Prediabetes is a heterogeneous term that encompasses different origins of insulin resistance and insulin secretion that contribute to distinct patterns of hyperglycemia. In fact, prediabetes is an umbrella term that characterizes individuals at high risk for developing type 2 diabetes (T2D) and/or cardiovascular disease (CVD). Based on current definitions there are at least 3 distinct phenotypes of prediabetes: impaired fasting glucose (IFG), impaired glucose tolerant (IGT), or the combination of both (IFG + IGT). Each phenotype is clinically relevant as they are uniquely recognized as having different levels of risk for progressing to T2D and CVD. Herein, we discuss the underlying pathophysiology that characterizes IFG, IGT and the combination, as well as examine how some of these phenotypes appear resistant to traditional exercise interventions. We propose that substrate metabolism differences between the prediabetes phenotypes may be a unifying mechanism that explains the inter-subject variation in response to exercise seen across obese, metabolic syndrome, pre-diabetic and T2D patients in the current literature. Ultimately, a better understanding of the pathophysiologic mechanisms that govern disturbances responsible for fasting vs. postprandial hyperglycemia and the combination of both is important for designing optimal and personalized exercise treatment strategies that treat and prevent hyperglycemia and CVD risk.

Selection on skewed characters and the paradox of stasis.

PubMed

Bonamour, Suzanne; Teplitsky, Céline; Charmantier, Anne; Crochet, Pierre-André; Chevin, Luis-Miguel

2017-11-01

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modeling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold's (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson-Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate sample sizes. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date - repeatedly described as more evolutionarily stable than expected - so this skewness should be accounted for when investigating evolutionary dynamics in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Stress reactivity links childhood trauma exposure to an admixture of depressive, anxiety, and psychosis symptoms.

PubMed

van Nierop, Martine; Lecei, Aleksandra; Myin-Germeys, Inez; Collip, Dina; Viechtbauer, Wolfgang; Jacobs, Nele; Derom, Catherine; Thiery, Evert; van Os, Jim; van Winkel, Ruud

2017-12-09

Childhood trauma exposure has been associated with a clinically relevant mixed phenotype of psychopathology composed of depressive, anxiety, and psychosis symptoms, across healthy and clinical samples. Altered stress-reactivity after exposure to childhood trauma may be a plausible underlying mechanism explaining this association. In a general population sample of female twins (T0 = 564; T1 = 483), associations between childhood trauma exposure and symptom profile (no symptoms, isolated symptoms, or a mixed phenotype) on the one hand, and daily life stress reactivity on the other were investigated. Daily life stress reactivity was measured using the Experience Sampling Method (ESM), and was defined as negative affect reactivity to minor daily life stressors. Individuals exposed to childhood trauma who reported a mixed phenotype of psychopathology showed a significant increase in emotional reactivity to daily life stress (activity and social stress), compared with trauma-exposed individuals without a mixed phenotype. In the trauma-exposed mixed phenotype group, increased emotional reactivity to event-stress predicted more severe symptoms at ± 14 month follow-up. This study found evidence that may link heightened emotional reactivity to stress in individuals with a trauma history to the risk for later comorbid psychopathology. Copyright © 2017 Elsevier B.V. All rights reserved.

Constructing Adverse Outcome Pathways: a Demonstration of ...

EPA Pesticide Factsheets

Adverse outcome pathway (AOP) provides a conceptual framework to evaluate and integrate chemical toxicity and its effects across the levels of biological organization. As such, it is essential to develop a resource-efficient and effective approach to extend molecular initiating events (MIEs) of chemicals to their downstream phenotypes of a greater regulatory relevance. A number of ongoing public phenomics (high throughput phenotyping) efforts have been generating abundant phenotypic data annotated with ontology terms. These phenotypes can be analyzed semantically and linked to MIEs of interest, all in the context of a knowledge base integrated from a variety of ontologies for various species and knowledge domains. In such analyses, two phenotypic profiles (PPs; anchored by genes or diseases) each characterized by multiple ontology terms are compared for their semantic similarities within a common ontology graph, but across boundaries of species and knowledge domains. Taking advantage of publicly available ontologies and software tool kits, we have implemented an OS-Mapping (Ontology-based Semantics Mapping) approach as a Java application, and constructed a network of 19383 PPs as nodes with edges weighed by their pairwise semantic similarity scores. Individual PPs were assembled from public phenomics data. Out of possible 1.87×108 pairwise connections among these nodes, about 71% of them have similarity scores between 0.2 and the maximum possible of 1.0.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

Multivariate Analysis of Genotype-Phenotype Association.

PubMed

Mitteroecker, Philipp; Cheverud, James M; Pavlicev, Mihaela

2016-04-01

With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated-in terms of effect size-with patterns of phenotypic variation (phenotypic latent variables). This multivariate genotype-phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype-phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype-phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for >70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype-phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3-the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype-phenotype map has important consequences for gene identification and may shed light on the evolvability of organisms. Copyright © 2016 by the Genetics Society of America.

Genomic scan as a tool for assessing the genetic component of phenotypic variance in wild populations.

PubMed

Herrera, Carlos M

2012-01-01

Methods for estimating quantitative trait heritability in wild populations have been developed in recent years which take advantage of the increased availability of genetic markers to reconstruct pedigrees or estimate relatedness between individuals, but their application to real-world data is not exempt from difficulties. This chapter describes a recent marker-based technique which, by adopting a genomic scan approach and focusing on the relationship between phenotypes and genotypes at the individual level, avoids the problems inherent to marker-based estimators of relatedness. This method allows the quantification of the genetic component of phenotypic variance ("degree of genetic determination" or "heritability in the broad sense") in wild populations and is applicable whenever phenotypic trait values and multilocus data for a large number of genetic markers (e.g., amplified fragment length polymorphisms, AFLPs) are simultaneously available for a sample of individuals from the same population. The method proceeds by first identifying those markers whose variation across individuals is significantly correlated with individual phenotypic differences ("adaptive loci"). The proportion of phenotypic variance in the sample that is statistically accounted for by individual differences in adaptive loci is then estimated by fitting a linear model to the data, with trait value as the dependent variable and scores of adaptive loci as independent ones. The method can be easily extended to accommodate quantitative or qualitative information on biologically relevant features of the environment experienced by each sampled individual, in which case estimates of the environmental and genotype × environment components of phenotypic variance can also be obtained.

Human Paraoxonase1 Hydrolysis of Nanomolar Chlorpyrifos-oxon Concentrations is Unaffected by Phenotype or Q192R Genotype

PubMed Central

Coombes, R. Hunter; Meek, Edward C.; Dail, Mary Beth; Chambers, Howard W.; Chambers, Janice E.

2016-01-01

The organophosphorus insecticide chlorpyrifos has been widely used. Its active metabolite chlorpyrifos-oxon (CPO) is a potent anticholinesterase and is detoxified by paraoxonase-1 (PON1). PON1 activity is influenced by numerous factors including a Q192R polymorphism. Using forty human blood samples bearing homozygous genotypes and either high or low activity phenotypes (as determined by high concentration assays of paraoxon and diazoxon hydrolysis) the serum PON1 hydrolysis of high (320 μM) and low (178 nM) CPO concentrations was assessed using direct or indirect spectrophotometric methods, respectively. PON1 activity at high CPO concentration reflected the phenotype and genotype differences; subjects with the high activity phenotype and homozygous for the PON1R192 alloform hydrolyzed significantly more CPO than subjects with the low activity phenotype and/or PON1Q192 alloform (High RR=11023±722, Low RR=9467±798, High QQ=8809±672, Low QQ=6030±1015 μmoles CPO hydrolyzed/min/L serum). However, PON1 hydrolysis of CPO at the lower, more environmentally relevant concentration showed no significant differences between the PON1192 genotypes and/or between high and low activity phenotypes (High RR=231±27, Low RR=219±52, High QQ=193±59, Low QQ=185±43 nmoles CPO/min/L serum). Low CPO concentrations were probably not saturating, so PON1 did not display maximal velocity and the PON1 genotype/phenotype might not influence the extent of metabolism at environmental exposures. PMID:25093614

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.

PubMed

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G; Helland, Aslaug; Rye, Inga H; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-02-13

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of cellular diversity for genetic and phenotypic features

PubMed Central

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G.; Helland, Åslaug; Rye, Inga H.; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L.; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-01-01

SUMMARY Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype-specific and it did not change during treatment in tumors with partial or no response. However, lower pre-treatment genetic diversity was significantly associated with complete pathologic response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. PMID:24462293

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

DOE PAGES

Almendro, Vanessa; Cheng, Yu -Kang; Randles, Amanda; ...

2014-02-01

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatialmore » distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.« less

Analysis of the Catecholaminergic Phenotype in Human SH-SY5Y and BE(2)-M17 Neuroblastoma Cell Lines upon Differentiation

PubMed Central

Filograna, Roberta; Civiero, Laura; Ferrari, Vanni; Codolo, Gaia; Greggio, Elisa; Bubacco, Luigi; Beltramini, Mariano; Bisaglia, Marco

2015-01-01

Human cell lines are often used to investigate cellular pathways relevant for physiological or pathological processes or to evaluate cell toxicity or protection induced by different compounds, including potential drugs. In this study, we analyzed and compared the differentiating activities of three agents (retinoic acid, staurosporine and 12-O-tetradecanoylphorbol-13-acetate) on the human neuroblastoma SH-SY5Y and BE(2)-M17 cell lines; the first cell line is largely used in the field of neuroscience, while the second is still poorly characterized. After evaluating their effects in terms of cell proliferation and morphology, we investigated their catecholaminergic properties by assessing the expression profiles of the major genes involved in catecholamine synthesis and storage and the cellular concentrations of the neurotransmitters dopamine and noradrenaline. Our results demonstrate that the two cell lines possess similar abilities to differentiate and acquire a neuron-like morphology. The most evident effects in SH-SY5Y cells were observed in the presence of staurosporine, while in BE(2)-M17 cells, retinoic acid induced the strongest effects. Undifferentiated SH-SY5Y and BE(2)-M17 cells are characterized by the production of both NA and DA, but their levels are considerably higher in BE(2)-M17 cells. Moreover, the NAergic phenotype appears to be more pronounced in SH-SY5Y cells, while BE(2)-M17 cells have a more prominent DAergic phenotype. Finally, the catecholamine concentration strongly increases upon differentiation induced by staurosporine in both cell lines. In conclusion, in this work the catecholaminergic phenotype of the human BE(2)-M17 cell line upon differentiation was characterized for the first time. Our data suggest that SH-SY5Y and BE(2)-M17 represent two alternative cell models for the neuroscience field. PMID:26317353

Analysis of the Catecholaminergic Phenotype in Human SH-SY5Y and BE(2)-M17 Neuroblastoma Cell Lines upon Differentiation.

PubMed

Filograna, Roberta; Civiero, Laura; Ferrari, Vanni; Codolo, Gaia; Greggio, Elisa; Bubacco, Luigi; Beltramini, Mariano; Bisaglia, Marco

2015-01-01

Human cell lines are often used to investigate cellular pathways relevant for physiological or pathological processes or to evaluate cell toxicity or protection induced by different compounds, including potential drugs. In this study, we analyzed and compared the differentiating activities of three agents (retinoic acid, staurosporine and 12-O-tetradecanoylphorbol-13-acetate) on the human neuroblastoma SH-SY5Y and BE(2)-M17 cell lines; the first cell line is largely used in the field of neuroscience, while the second is still poorly characterized. After evaluating their effects in terms of cell proliferation and morphology, we investigated their catecholaminergic properties by assessing the expression profiles of the major genes involved in catecholamine synthesis and storage and the cellular concentrations of the neurotransmitters dopamine and noradrenaline. Our results demonstrate that the two cell lines possess similar abilities to differentiate and acquire a neuron-like morphology. The most evident effects in SH-SY5Y cells were observed in the presence of staurosporine, while in BE(2)-M17 cells, retinoic acid induced the strongest effects. Undifferentiated SH-SY5Y and BE(2)-M17 cells are characterized by the production of both NA and DA, but their levels are considerably higher in BE(2)-M17 cells. Moreover, the NAergic phenotype appears to be more pronounced in SH-SY5Y cells, while BE(2)-M17 cells have a more prominent DAergic phenotype. Finally, the catecholamine concentration strongly increases upon differentiation induced by staurosporine in both cell lines. In conclusion, in this work the catecholaminergic phenotype of the human BE(2)-M17 cell line upon differentiation was characterized for the first time. Our data suggest that SH-SY5Y and BE(2)-M17 represent two alternative cell models for the neuroscience field.

Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation.

PubMed

Morley, Katherine I; Wallace, Joshua; Denaxas, Spiros C; Hunter, Ross J; Patel, Riyaz S; Perel, Pablo; Shah, Anoop D; Timmis, Adam D; Schilling, Richard J; Hemingway, Harry

2014-01-01

National electronic health records (EHR) are increasingly used for research but identifying disease cases is challenging due to differences in information captured between sources (e.g. primary and secondary care). Our objective was to provide a transparent, reproducible model for integrating these data using atrial fibrillation (AF), a chronic condition diagnosed and managed in multiple ways in different healthcare settings, as a case study. Potentially relevant codes for AF screening, diagnosis, and management were identified in four coding systems: Read (primary care diagnoses and procedures), British National Formulary (BNF; primary care prescriptions), ICD-10 (secondary care diagnoses) and OPCS-4 (secondary care procedures). From these we developed a phenotype algorithm via expert review and analysis of linked EHR data from 1998 to 2010 for a cohort of 2.14 million UK patients aged ≥ 30 years. The cohort was also used to evaluate the phenotype by examining associations between incident AF and known risk factors. The phenotype algorithm incorporated 286 codes: 201 Read, 63 BNF, 18 ICD-10, and four OPCS-4. Incident AF diagnoses were recorded for 72,793 patients, but only 39.6% (N = 28,795) were recorded in primary care and secondary care. An additional 7,468 potential cases were inferred from data on treatment and pre-existing conditions. The proportion of cases identified from each source differed by diagnosis age; inferred diagnoses contributed a greater proportion of younger cases (≤ 60 years), while older patients (≥ 80 years) were mainly diagnosed in SC. Associations of risk factors (hypertension, myocardial infarction, heart failure) with incident AF defined using different EHR sources were comparable in magnitude to those from traditional consented cohorts. A single EHR source is not sufficient to identify all patients, nor will it provide a representative sample. Combining multiple data sources and integrating information on treatment and comorbid conditions can substantially improve case identification.

Natural variation in stomatal abundance of Arabidopsis thaliana includes cryptic diversity for different developmental processes

PubMed Central

Delgado, Dolores; Alonso-Blanco, Carlos; Fenoll, Carmen; Mena, Montaña

2011-01-01

Background and Aims Current understanding of stomatal development in Arabidopsis thaliana is based on mutations producing aberrant, often lethal phenotypes. The aim was to discover if naturally occurring viable phenotypes would be useful for studying stomatal development in a species that enables further molecular analysis. Methods Natural variation in stomatal abundance of A. thaliana was explored in two collections comprising 62 wild accessions by surveying adaxial epidermal cell-type proportion (stomatal index) and density (stomatal and pavement cell density) traits in cotyledons and first leaves. Organ size variation was studied in a subset of accessions. For all traits, maternal effects derived from different laboratory environments were evaluated. In four selected accessions, distinct stomatal initiation processes were quantitatively analysed. Key Results and Conclusions Substantial genetic variation was found for all six stomatal abundance-related traits, which were weakly or not affected by laboratory maternal environments. Correlation analyses revealed overall relationships among all traits. Within each organ, stomatal density highly correlated with the other traits, suggesting common genetic bases. Each trait correlated between organs, supporting supra-organ control of stomatal abundance. Clustering analyses identified accessions with uncommon phenotypic patterns, suggesting differences among genetic programmes controlling the various traits. Variation was also found in organ size, which negatively correlated with cell densities in both organs and with stomatal index in the cotyledon. Relative proportions of primary and satellite lineages varied among the accessions analysed, indicating that distinct developmental components contribute to natural diversity in stomatal abundance. Accessions with similar stomatal indices showed different lineage class ratios, revealing hidden developmental phenotypes and showing that genetic determinants of primary and satellite lineage initiation combine in several ways. This first systematic, comprehensive natural variation survey for stomatal abundance in A. thaliana reveals cryptic developmental genetic variation, and provides relevant relationships amongst stomatal traits and extreme or uncommon accessions as resources for the genetic dissection of stomatal development. PMID:21447490

External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses.

PubMed

Waldman, Irwin D; Poore, Holly E; van Hulle, Carol; Rathouz, Paul J; Lahey, Benjamin B

2016-11-01

Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Serum Biochemical Phenotypes in the Domestic Dog

PubMed Central

Chang, Yu-Mei; Hadox, Erin; Szladovits, Balazs; Garden, Oliver A.

2016-01-01

The serum or plasma biochemical profile is essential in the diagnosis and monitoring of systemic disease in veterinary medicine, but current reference intervals typically take no account of breed-specific differences. Breed-specific hematological phenotypes have been documented in the domestic dog, but little has been published on serum biochemical phenotypes in this species. Serum biochemical profiles of dogs in which all measurements fell within the existing reference intervals were retrieved from a large veterinary database. Serum biochemical profiles from 3045 dogs were retrieved, of which 1495 had an accompanying normal glucose concentration. Sixty pure breeds plus a mixed breed control group were represented by at least 10 individuals. All analytes, except for sodium, chloride and glucose, showed variation with age. Total protein, globulin, potassium, chloride, creatinine, cholesterol, total bilirubin, ALT, CK, amylase, and lipase varied between sexes. Neutering status significantly impacted all analytes except albumin, sodium, calcium, urea, and glucose. Principal component analysis of serum biochemical data revealed 36 pure breeds with distinctive phenotypes. Furthermore, comparative analysis identified 23 breeds with significant differences from the mixed breed group in all biochemical analytes except urea and glucose. Eighteen breeds were identified by both principal component and comparative analysis. Tentative reference intervals were generated for breeds with a distinctive phenotype identified by comparative analysis and represented by at least 120 individuals. This is the first large-scale analysis of breed-specific serum biochemical phenotypes in the domestic dog and highlights potential genetic components of biochemical traits in this species. PMID:26919479

Development of computationally predicted Adverse Outcome Pathway (AOP) networks through data mining and integration of publicly available in vivo, in vitro, phenotype, and biological pathway data

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework is increasingly being adopted as a tool for organizing and summarizing the mechanistic information connecting molecular perturbations by environmental stressors with adverse outcomes relevant for ecological and human health outcomes. Ho...

Looking at Movies and Cartoons: Eye-Tracking Evidence from Williams Syndrome and Autism

ERIC Educational Resources Information Center

Riby, D.; Hancock, P. J. B.

2009-01-01

Background: Autism and Williams syndrome (WS) are neuro-developmental disorders associated with distinct social phenotypes. While individuals with autism show a lack of interest in socially important cues, individuals with WS often show increased interest in socially relevant information. Methods: The current eye-tracking study explores how…

A Discrepancy in Comprehension and Production in Early Language Development in ASD: Is It Clinically Relevant?

ERIC Educational Resources Information Center

Davidson, Meghan M.; Ellis Weismer, Susan

2017-01-01

This study examined the extent to which a discrepant comprehension-production profile (i.e., relatively more delayed comprehension than production) is characteristic of the early language phenotype in autism spectrum disorders (ASD) and tracked the developmental progression of the profile. Our findings indicated that a discrepant…

Difficult‐to‐control asthma management through the use of a specific protocol

PubMed Central

Giavina‐Bianchi, Pedro; Aun, Marcelo Vivolo; Bisaccioni, Carla; Agondi, Rosana; Kalil, Jorge

2010-01-01

The present study is a critical review of difficult‐to‐control asthma, highlighting the characteristics and severity of the disease. It also presents a protocol for the management of patients with this asthma phenotype. The protocol, which was based on relevant studies in the literature, is described and analyzed. PMID:21049219

Human Facial Expressions as Adaptations:Evolutionary Questions in Facial Expression Research

PubMed Central

SCHMIDT, KAREN L.; COHN, JEFFREY F.

2007-01-01

The importance of the face in social interaction and social intelligence is widely recognized in anthropology. Yet the adaptive functions of human facial expression remain largely unknown. An evolutionary model of human facial expression as behavioral adaptation can be constructed, given the current knowledge of the phenotypic variation, ecological contexts, and fitness consequences of facial behavior. Studies of facial expression are available, but results are not typically framed in an evolutionary perspective. This review identifies the relevant physical phenomena of facial expression and integrates the study of this behavior with the anthropological study of communication and sociality in general. Anthropological issues with relevance to the evolutionary study of facial expression include: facial expressions as coordinated, stereotyped behavioral phenotypes, the unique contexts and functions of different facial expressions, the relationship of facial expression to speech, the value of facial expressions as signals, and the relationship of facial expression to social intelligence in humans and in nonhuman primates. Human smiling is used as an example of adaptation, and testable hypotheses concerning the human smile, as well as other expressions, are proposed. PMID:11786989

Shifting the focus toward rare variants in schizophrenia to close the gap from genotype to phenotype.

PubMed

Bustamante, M Leonor; Herrera, Luisa; Gaspar, Pablo A; Nieto, Rodrigo; Maturana, Alejandro; Villar, María José; Salinas, Valeria; Silva, Hernán

2017-10-01

Schizophrenia (SZ) is a disorder with a high heritability and a complex architecture. Several dozen genetic variants have been identified as risk factors through genome-wide association studies including large population-based samples. However, the bulk of the risk cannot be accounted for by the genes associated to date. Rare mutations have been historically seen as relevant only for some infrequent, Mendelian forms of psychosis. Recent findings, however, show that the subset of patients that present a mutation with major effect is larger than expected. We discuss some of the molecular findings of these studies. SZ is clinically and genetically heterogeneous. To identify the genetic variation underlying the disorder, research should be focused on features that are more likely a product of genetic heterogeneity. Based on the phenotypical correlations with rare variants, cognition emerges as a relevant domain to study. Cognitive disturbances could be useful in selecting cases that have a higher probability of carrying deleterious mutations, as well as on the correct ascertainment of sporadic cases for the identification of de novo variants. © 2017 Wiley Periodicals, Inc.

Completing the cycle: maternal effects as the missing link in plant life histories.

PubMed

Donohue, Kathleen

2009-04-27

Maternal effects on seed traits such as germination are important components of the life histories of plants because they represent the pathway from adult to offspring: the pathway that completes the life cycle. Maternal environmental effects on germination influence basic life-history expression, natural selection on germination, the expression of genetic variation for germination and even the genes involved in germination. Maternal effects on seed traits can even influence generation time and projected population growth rates. Whether these maternal environmental effects are imposed by the maternal genotype, the endosperm genotype or the embryonic genotype, however, is as yet unknown. Patterns of gene expression and protein synthesis in seeds indicate that the maternal genotype has the opportunity to influence its progeny's germination behaviour. Investigation of the phenotypic consequences of maternal environmental effects, regardless of its genetic determination, is relevant for understanding the variation in plant life cycles. Distinguishing the genotype(s) that control them is relevant for predicting the evolutionary trajectories and patterns of selection on progeny phenotypes and the genes underlying them.

Animal models of speech and vocal communication deficits associated with psychiatric disorders

PubMed Central

Konopka, Genevieve; Roberts, Todd F.

2015-01-01

Disruptions in speech, language and vocal communication are hallmarks of several neuropsychiatric disorders, most notably autism spectrum disorders. Historically, the use of animal models to dissect molecular pathways and connect them to behavioral endophenotypes in cognitive disorders has proven to be an effective approach for developing and testing disease-relevant therapeutics. The unique aspects of human language when compared to vocal behaviors in other animals make such an approach potentially more challenging. However, the study of vocal learning in species with analogous brain circuits to humans may provide entry points for understanding this human-specific phenotype and diseases. Here, we review animal models of vocal learning and vocal communication, and specifically link phenotypes of psychiatric disorders to relevant model systems. Evolutionary constraints in the organization of neural circuits and synaptic plasticity result in similarities in the brain mechanisms for vocal learning and vocal communication. Comparative approaches and careful consideration of the behavioral limitations among different animal models can provide critical avenues for dissecting the molecular pathways underlying cognitive disorders that disrupt speech, language and vocal communication. PMID:26232298

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

Mitochondrial Disease Sequence Data Resource (MSeqDR): a global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities.

PubMed

Falk, Marni J; Shen, Lishuang; Gonzalez, Michael; Leipzig, Jeremy; Lott, Marie T; Stassen, Alphons P M; Diroma, Maria Angela; Navarro-Gomez, Daniel; Yeske, Philip; Bai, Renkui; Boles, Richard G; Brilhante, Virginia; Ralph, David; DaRe, Jeana T; Shelton, Robert; Terry, Sharon F; Zhang, Zhe; Copeland, William C; van Oven, Mannis; Prokisch, Holger; Wallace, Douglas C; Attimonelli, Marcella; Krotoski, Danuta; Zuchner, Stephan; Gai, Xiaowu

2015-03-01

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The "Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium" is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through the use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial diseases. Copyright © 2014 Elsevier Inc. All rights reserved.

Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

PubMed Central

Falk, Marni J.; Shen, Lishuang; Gonzalez, Michael; Leipzig, Jeremy; Lott, Marie T.; Stassen, Alphons P.M.; Diroma, Maria Angela; Navarro-Gomez, Daniel; Yeske, Philip; Bai, Renkui; Boles, Richard G.; Brilhante, Virginia; Ralph, David; DaRe, Jeana T.; Shelton, Robert; Terry, Sharon; Zhang, Zhe; Copeland, William C.; van Oven, Mannis; Prokisch, Holger; Wallace, Douglas C.; Attimonelli, Marcella; Krotoski, Danuta; Zuchner, Stephan; Gai, Xiaowu

2014-01-01

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The “Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium” is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1,300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial disease. PMID:25542617

Phenotype of postural instability/gait difficulty in Parkinson disease: relevance to cognitive impairment and mechanism relating pathological proteins and neurotransmitters

PubMed Central

Zuo, Li-Jun; Piao, Ying-Shan; Li, Li-Xia; Yu, Shu-Yang; Guo, Peng; Hu, Yang; Lian, Teng-Hong; Wang, Rui-Dan; Yu, Qiu-Jin; Jin, Zhao; Wang, Ya-Jie; Wang, Xiao-Min; Chan, Piu; Chen, Sheng-Di; Wang, Yong-Jun; Zhang, Wei

2017-01-01

Parkinson disease (PD) is identified as tremor-dominant (TD) and postural instability and gait difficulty (PIGD) phenotypes. The relationships between motor phenotypes and cognitive impairment and the underlying mechanisms relating pathological proteins and neurotransmitters in cerebrospinal fluid (CSF) are unknown. We evaluated the motor symptoms and cognitive function by scales, and detected the levels of pathological proteins and neurotransmitters in CSF. TD group and PIGD group had significantly higher levels of total tau, tau phosphorylated at the position of threonine 181(P-tau181t), threonine 231, serine 396, serine 199 and lower β amyloid (Aβ)1–42 level in CSF than those in control group; PIGD group had significantly higher P-tau181t level and lower Aβ1–42 level than those in TD group. In PD group, PIGD severity was negatively correlated with MoCA score and Aβ1–42 level in CSF, and positively correlated with Hoehn-Yahr stage and P-tau181t level in CSF. In PIGD group, PIGD severity was negatively correlated with homovanillic acid (HVA) level in CSF, and HVA level was positively correlated with Aβ1–42 level in CSF. PIGD was significantly correlated with cognitive impairment, which underlying mechanism might be involved in Aβ1–42 aggregation in brain and relevant neurochemical disturbance featured by the depletion of HVA in CSF. PMID:28332604

Muscle dysfunction in chronic obstructive pulmonary disease: update on causes and biological findings

PubMed Central

Pascual, Sergi; Casadevall, Carme; Orozco-Levi, Mauricio; Barreiro, Esther

2015-01-01

Respiratory and/or limb muscle dysfunction, which are frequently observed in chronic obstructive pulmonary disease (COPD) patients, contribute to their disease prognosis irrespective of the lung function. Muscle dysfunction is caused by the interaction of local and systemic factors. The key deleterious etiologic factors are pulmonary hyperinflation for the respiratory muscles and deconditioning secondary to reduced physical activity for limb muscles. Nonetheless, cigarette smoke, systemic inflammation, nutritional abnormalities, exercise, exacerbations, anabolic insufficiency, drugs and comorbidities also seem to play a relevant role. All these factors modify the phenotype of the muscles, through the induction of several biological phenomena in patients with COPD. While respiratory muscles improve their aerobic phenotype (percentage of oxidative fibers, capillarization, mitochondrial density, enzyme activity in the aerobic pathways, etc.), limb muscles exhibit the opposite phenotype. In addition, both muscle groups show oxidative stress, signs of damage and epigenetic changes. However, fiber atrophy, increased number of inflammatory cells, altered regenerative capacity; signs of apoptosis and autophagy, and an imbalance between protein synthesis and breakdown are rather characteristic features of the limb muscles, mostly in patients with reduced body weight. Despite that significant progress has been achieved in the last decades, full elucidation of the specific roles of the target biological mechanisms involved in COPD muscle dysfunction is still required. Such an achievement will be crucial to adequately tackle with this relevant clinical problem of COPD patients in the near-future. PMID:26623119

Humans display a reduced set of consistent behavioral phenotypes in dyadic games.

PubMed

Poncela-Casasnovas, Julia; Gutiérrez-Roig, Mario; Gracia-Lázaro, Carlos; Vicens, Julian; Gómez-Gardeñes, Jesús; Perelló, Josep; Moreno, Yamir; Duch, Jordi; Sánchez, Angel

2016-08-01

Socially relevant situations that involve strategic interactions are widespread among animals and humans alike. To study these situations, theoretical and experimental research has adopted a game theoretical perspective, generating valuable insights about human behavior. However, most of the results reported so far have been obtained from a population perspective and considered one specific conflicting situation at a time. This makes it difficult to extract conclusions about the consistency of individuals' behavior when facing different situations and to define a comprehensive classification of the strategies underlying the observed behaviors. We present the results of a lab-in-the-field experiment in which subjects face four different dyadic games, with the aim of establishing general behavioral rules dictating individuals' actions. By analyzing our data with an unsupervised clustering algorithm, we find that all the subjects conform, with a large degree of consistency, to a limited number of behavioral phenotypes (envious, optimist, pessimist, and trustful), with only a small fraction of undefined subjects. We also discuss the possible connections to existing interpretations based on a priori theoretical approaches. Our findings provide a relevant contribution to the experimental and theoretical efforts toward the identification of basic behavioral phenotypes in a wider set of contexts without aprioristic assumptions regarding the rules or strategies behind actions. From this perspective, our work contributes to a fact-based approach to the study of human behavior in strategic situations, which could be applied to simulating societies, policy-making scenario building, and even a variety of business applications.

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

MUTZ-3 derived Langerhans cells in human skin equivalents show differential migration and phenotypic plasticity after allergen or irritant exposure

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

Kosten, Ilona J.; Spiekstra, Sander W.; Gruijl, Tanja D. de

After allergen or irritant exposure, Langerhans cells (LC) undergo phenotypic changes and exit the epidermis. In this study we describe the unique ability of MUTZ-3 derived Langerhans cells (MUTZ-LC) to display similar phenotypic plasticity as their primary counterparts when incorporated into a physiologically relevant full-thickness skin equivalent model (SE-LC). We describe differences and similarities in the mechanisms regulating LC migration and plasticity upon allergen or irritant exposure. The skin equivalent consisted of a reconstructed epidermis containing primary differentiated keratinocytes and CD1a{sup +} MUTZ-LC on a primary fibroblast-populated dermis. Skin equivalents were exposed to a panel of allergens and irritants. Topicalmore » exposure to sub-toxic concentrations of allergens (nickel sulfate, resorcinol, cinnamaldehyde) and irritants (Triton X-100, SDS, Tween 80) resulted in LC migration out of the epidermis and into the dermis. Neutralizing antibody to CXCL12 blocked allergen-induced migration, whereas anti-CCL5 blocked irritant-induced migration. In contrast to allergen exposure, irritant exposure resulted in cells within the dermis becoming CD1a{sup −}/CD14{sup +}/CD68{sup +} which is characteristic of a phenotypic switch of MUTZ-LC to a macrophage-like cell in the dermis. This phenotypic switch was blocked with anti-IL-10. Mechanisms previously identified as being involved in LC activation and migration in native human skin could thus be reproduced in the in vitro constructed skin equivalent model containing functional LC. This model therefore provides a unique and relevant research tool to study human LC biology in situ under controlled in vitro conditions, and will provide a powerful tool for hazard identification, testing novel therapeutics and identifying new drug targets. - Highlights: • MUTZ-3 derived Langerhans cells integrated into skin equivalents are fully functional. • Anti-CXCL12 blocks allergen-induced MUTZ-LC migration. • Anti-CCL5 blocks irritant-induced MUTZ-LC migration. • Irritant mediated MUTZ-LC trans-differentiation to macrophage-like cell in dermis. • Trans-differentiation of MUTZ-LC is IL-10 dependent.« less

Identification and characterization of near-fatal asthma phenotypes by cluster analysis.

PubMed

Serrano-Pariente, J; Rodrigo, G; Fiz, J A; Crespo, A; Plaza, V

2015-09-01

Near-fatal asthma (NFA) is a heterogeneous clinical entity and several profiles of patients have been described according to different clinical, pathophysiological and histological features. However, there are no previous studies that identify in a unbiased way--using statistical methods such as clusters analysis--different phenotypes of NFA. Therefore, the aim of the present study was to identify and to characterize phenotypes of near fatal asthma using a cluster analysis. Over a period of 2 years, 33 Spanish hospitals enrolled 179 asthmatics admitted for an episode of NFA. A cluster analysis using two-steps algorithm was performed from data of 84 of these cases. The analysis defined three clusters of patients with NFA: cluster 1, the largest, including older patients with clinical and therapeutic criteria of severe asthma; cluster 2, with an high proportion of respiratory arrest (68%), impaired consciousness level (82%) and mechanical ventilation (93%); and cluster 3, which included younger patients, characterized by an insufficient anti-inflammatory treatment and frequent sensitization to Alternaria alternata and soybean. These results identify specific asthma phenotypes involved in NFA, confirming in part previous findings observed in studies with a clinical approach. The identification of patients with a specific NFA phenotype could suggest interventions to prevent future severe asthma exacerbations. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Microbial Community Analysis of Field-Grown Soybeans with Different Nodulation Phenotypes▿

PubMed Central

Ikeda, Seishi; Rallos, Lynn Esther E.; Okubo, Takashi; Eda, Shima; Inaba, Shoko; Mitsui, Hisayuki; Minamisawa, Kiwamu

2008-01-01

Microorganisms associated with the stems and roots of nonnodulated (Nod−), wild-type nodulated (Nod+), and hypernodulated (Nod++) soybeans [Glycine max (L.) Merril] were analyzed by ribosomal intergenic transcribed spacer analysis (RISA) and automated RISA (ARISA). RISA of stem samples detected no bands specific to the nodulation phenotype, whereas RISA of root samples revealed differential bands for the nodulation phenotypes. Pseudomonas fluorescens was exclusively associated with Nod+ soybean roots. Fusarium solani was stably associated with nodulated (Nod+ and Nod++) roots and less abundant in Nod− soybeans, whereas the abundance of basidiomycetes was just the opposite. The phylogenetic analyses suggested that these basidiomycetous fungi might represent a root-associated group in the Auriculariales. Principal-component analysis of the ARISA results showed that there was no clear relationship between nodulation phenotype and bacterial community structure in the stem. In contrast, both the bacterial and fungal community structures in the roots were related to nodulation phenotype. The principal-component analysis further suggested that bacterial community structure in roots could be classified into three groups according to the nodulation phenotype (Nod−, Nod+, or Nod++). The analysis of root samples indicated that the microbial community in Nod− soybeans was more similar to that in Nod++ soybeans than to that in Nod+ soybeans. PMID:18658280

Genetic basis of Bartter syndrome in Korea.

PubMed

Lee, Beom Hee; Cho, Hee Yeon; Lee, HyunKyung; Han, Kyoung Hee; Kang, Hee Gyung; Ha, Il Soo; Lee, Joo Hoon; Park, Young Seo; Shin, Jae Il; Lee, Dae-Yeol; Kim, Su-Yung; Choi, Yong; Cheong, Hae Il

2012-04-01

Bartter syndrome (BS) is clinically classified into antenatal or neonatal BS (aBS) and classic BS (cBS) as well as five subtypes based on the underlying mutant gene; SLC12A1 (BS I), KCNJ1 (BS II), CLCNKB (BS III), BSND (BS IV) and CASR (BS V). Clinico-genetic features of a nationwide cohort of 26 Korean children with BS were investigated. The clinical diagnosis was aBS in 8 (30.8%), cBS in 15 (57.7%) and mixed Bartter-Gitelman phenotype in 3 cases (11.5%). Five of eight patients with aBS and all 18 patients with either cBS or mixed Bartter-Gitelman phenotype had CLCNKB mutations. Among the 23 patients (46 alleles) with CLCNKB mutations, p.W610X and large deletions were detected in 25 (54.3%) and 10 (21.7%) alleles, respectively. There was no genotype-phenotype correlation in patients with CLCNKB mutations. Twenty-three (88.5%) of the 26 BS patients involved in this study had CLCNKB mutations. The p.W610X mutation and large deletion were two common types of mutations in CLCNKB. The clinical manifestations of BS III were heterogeneous without a genotype-phenotype correlation, typically manifesting cBS phenotype but also aBS or mixed Bartter-Gitelman phenotypes. The molecular diagnostic steps for patients with BS in our population should be designed taking these peculiar genotype distributions into consideration, and a new more clinically relevant classification including BS and Gitelman syndrome is required.

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.

Using a Stem Cell-Based Signature to Guide Therapeutic Selection in Cancer

PubMed Central

Shats, Igor; Gatza, Michael L.; Chang, Jeffrey T.; Mori, Seiichi; Wang, Jialiang; Rich, Jeremy; Nevins, Joseph R.

2010-01-01

Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. PMID:21169407

Combining Genotype, Phenotype, and Environment to Infer Potential Candidate Genes.

PubMed

Talbot, Benoit; Chen, Ting-Wen; Zimmerman, Shawna; Joost, Stéphane; Eckert, Andrew J; Crow, Taylor M; Semizer-Cuming, Devrim; Seshadri, Chitra; Manel, Stéphanie

2017-03-01

Population genomic analysis can be an important tool in understanding local adaptation. Identification of potential adaptive loci in such analyses is usually based on the survey of a large genomic dataset in combination with environmental variables. Phenotypic data are less commonly incorporated into such studies, although combining a genome scan analysis with a phenotypic trait analysis can greatly improve the insights obtained from each analysis individually. Here, we aimed to identify loci potentially involved in adaptation to climate in 283 Loblolly pine (Pinus taeda) samples from throughout the species' range in the southeastern United States. We analyzed associations between phenotypic, molecular, and environmental variables from datasets of 3082 single nucleotide polymorphism (SNP) loci and 3 categories of phenotypic traits (gene expression, metabolites, and whole-plant traits). We found only 6 SNP loci that displayed potential signals of local adaptation. Five of the 6 identified SNPs are linked to gene expression traits for lignin development, and 1 is linked with whole-plant traits. We subsequently compared the 6 candidate genes with environmental variables and found a high correlation in only 3 of them (R2 > 0.2). Our study highlights the need for a combination of genotypes, phenotypes, and environmental variables, and for an appropriate sampling scheme and study design, to improve confidence in the identification of potential candidate genes. © The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.