PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

Linking genotype to phenotype in a changing ocean: inferring the genomic architecture of a blue mussel stress response with genome-wide association.

PubMed

Kingston, S E; Martino, P; Melendy, M; Reed, F A; Carlon, D B

2018-03-01

A key component to understanding the evolutionary response to a changing climate is linking underlying genetic variation to phenotypic variation in stress response. Here, we use a genome-wide association approach (GWAS) to understand the genetic architecture of calcification rates under simulated climate stress. We take advantage of the genomic gradient across the blue mussel hybrid zone (Mytilus edulis and Mytilus trossulus) in the Gulf of Maine (GOM) to link genetic variation with variance in calcification rates in response to simulated climate change. Falling calcium carbonate saturation states are predicted to negatively impact many marine organisms that build calcium carbonate shells - like blue mussels. We sampled wild mussels and measured net calcification phenotypes after exposing mussels to a 'climate change' common garden, where we raised temperature by 3°C, decreased pH by 0.2 units and limited food supply by filtering out planktonic particles >5 μm, compared to ambient GOM conditions in the summer. This climate change exposure greatly increased phenotypic variation in net calcification rates compared to ambient conditions. We then used regression models to link the phenotypic variation with over 170 000 single nucleotide polymorphism loci (SNPs) generated by genotype by sequencing to identify genomic locations associated with calcification phenotype, and estimate heritability and architecture of the trait. We identified at least one of potentially 2-10 genomic regions responsible for 30% of the phenotypic variation in calcification rates that are potential targets of natural selection by climate change. Our simulations suggest a power of 13.7% with our study's average effective sample size of 118 individuals and rare alleles, but a power of >90% when effective sample size is 900. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

X-linked juvenile retinoschisis in a consanguineous family: phenotypic variability and report of a homozygous female patient.

PubMed

Gliem, Martin; Holz, Frank G; Stöhr, Heidi; Weber, Bernhard H F; Charbel Issa, Peter

2014-12-01

To describe the phenotypic variability in a consanguineous family with genetically confirmed X-linked retinoschisis. Five patients, including one homozygous female, were characterized by clinical examination, optical coherence tomography, fundus autofluorescence, mapping of macular pigment optical density, electroretinography, and DNA testing. The 36-year-old male index patient showed a ring of enhanced autofluorescence and outer retinal atrophy on optical coherence tomography. Electroretinography testing revealed a reduced a/b ratio. His mother presented with a central atrophic retina with markedly reduced autofluorescence signal and a surrounding ring of enhanced autofluorescence. The 40-year-old brother of the index patient and his 2 sons showed characteristic signs for X-linked retinoschisis, including retinal schisis and a reduced a/b ratio. Genetic testing revealed a c.293C>A mutation in the RS1 gene in all affected family members while the mother of the index patient was homozygous for this mutation. X-linked retinoschisis can present with a wide phenotypic variability. Here, detailed family history and genetic testing established the diagnosis of X-linked retinoschisis despite striking differences in phenotypic presentation in affected subjects, homozygosity of one affected female, and seemingly dominant inheritance in three subsequent generations because of multiple consanguinity.

A prenatal nicotine exposure mouse model of methylphenidate responsive ADHD-associated cognitive phenotypes.

PubMed

Zhu, Jinmin; Fan, Fangfang; McCarthy, Deirdre M; Zhang, Lin; Cannon, Elisa N; Spencer, Thomas J; Biederman, Joseph; Bhide, Pradeep G

2017-05-01

Prenatal exposure to nicotine via cigarette smoke or other forms of tobacco use is a significant environmental risk factor for attention deficit hyperactivity disorder (ADHD). The neurobiological mechanisms underlying the link between prenatal nicotine exposure (PNE) and ADHD are not well understood. Animal models, especially rodent models, are beginning to bridge this gap in knowledge. Although ADHD is characterized by hyperactivity, inattention, impulsivity and working memory deficits, the majority of the animal models are based on only one or two ADHD associated phenotypes, in particular, hyperactivity or inattention. We report a PNE mouse model that displays the full range of ADHD associated behavioral phenotypes including working memory deficit, attention deficit and impulsive-like behavior. All of the ADHD-associated phenotypes respond to a single administration of a therapeutic equivalent dose of methylphenidate. In an earlier study, we showed that PNE produces hyperactivity, frontal cortical hypodopaminergic state and thinning of the cingulate cortex. Collectively, these data suggest that the PNE mouse model recapitulates key features of ADHD and may be a suitable preclinical model for ADHD research. Copyright © 2017 ISDN. Published by Elsevier Ltd. All rights reserved.

Concept mapping One-Carbon Metabolism to model future ontologies for nutrient-gene-phenotype interactions.

PubMed

Joslin, A C; Green, R; German, J B; Lange, M C

2014-09-01

Advances in the development of bioinformatic tools continue to improve investigators' ability to interrogate, organize, and derive knowledge from large amounts of heterogeneous information. These tools often require advanced technical skills not possessed by life scientists. User-friendly, low-barrier-to-entry methods of visualizing nutrigenomics information are yet to be developed. We utilized concept mapping software from the Institute for Human and Machine Cognition to create a conceptual model of diet and health-related data that provides a foundation for future nutrigenomics ontologies describing published nutrient-gene/polymorphism-phenotype data. In this model, maps containing phenotype, nutrient, gene product, and genetic polymorphism interactions are visualized as triples of two concepts linked together by a linking phrase. These triples, or "knowledge propositions," contextualize aggregated data and information into easy-to-read knowledge maps. Maps of these triples enable visualization of genes spanning the One-Carbon Metabolism (OCM) pathway, their sequence variants, and multiple literature-mined associations including concepts relevant to nutrition, phenotypes, and health. The concept map development process documents the incongruity of information derived from pathway databases versus literature resources. This conceptual model highlights the importance of incorporating information about genes in upstream pathways that provide substrates, as well as downstream pathways that utilize products of the pathway under investigation, in this case OCM. Other genes and their polymorphisms, such as TCN2 and FUT2, although not directly involved in OCM, potentially alter OCM pathway functionality. These upstream gene products regulate substrates such as B12. Constellations of polymorphisms affecting the functionality of genes along OCM, together with substrate and cofactor availability, may impact resultant phenotypes. These conceptual maps provide a foundational

Centrosome Linker-induced Tetraploid Segregation Errors Link Rhabdoid Phenotypes and Lethal Colorectal Cancers.

PubMed

Remo, Andrea; Manfrin, Erminia; Parcesepe, Pietro; Ferrarini, Alberto; Han, Hye Seung; Ugnius, Mickys; Laudanna, Carmelo; Simbolo, Michele; Malanga, Donatella; Mendes Oliveira, Duarte; Baritono, Elisabetta; Colangelo, Tommaso; Sabatino, Lina; Giuliani, Jacopo; Molinari, Enrico; Garonzi, Marianna; Xumerle, Luciano; Delledonne, Massimo; Giordano, Guido; Ghimenton, Claudio; Lonardo, Fortunato; D'angelo, Fulvio; Grillo, Federica; Mastracci, Luca; Viglietto, Giuseppe; Ceccarelli, Michele; Colantuoni, Vittorio; Scarpa, Aldo; Pancione, Massimo

2018-05-21

Centrosome anomalies contribute to tumorigenesis but it remains unclear how they are generated in lethal cancer phenotypes. Here, it is demonstrated that human microsatellite instable (MSI) and BRAF(V600E) mutant colorectal cancers with a lethal rhabdoid phenotype are characterized by inactivation of centrosomal functions. A splice site mutation that causes an unbalanced dosage of rootletin (CROCC), a centrosomal-linker component required for centrosome cohesion and separation at the chromosome 1p36.13 locus, resulted in abnormally shaped centrosomes in rhabdoid cells from human colon tissues. Notably, deleterious deletions at 1p36.13 were recurrent in a subgroup of BRAF(V600E) mutant and microsatellite stable (MSS) rhabdoid colorectal cancers but not in classical colorectal cancer or pediatric rhabdoid tumors. Interfering with CROCC expression in near-diploid BRAF(V600E) mutant/MSI colon cancer cells disrupts bipolar mitotic spindle architecture, promotes tetraploid segregation errors resulting in a highly aggressive rhabdoid-like phenotype in vitro. Restoring near-wild-type levels of CROCC in a metastatic model harboring 1p36.13 deletion results in correction of centrosome segregation errors and cell death, revealing a mechanism of tolerance to mitotic errors and tetraploidization promoted by deleterious 1p36.13 loss. Accordingly, cancer cells lacking 1p36.13 display far greater sensitivity to centrosome spindle pole stabilizing agents in vitro. These data shed light on a previously unknown link between centrosome cohesion defects and lethal cancer phenotypes providing new insight into pathways underlying genome instability. Mis-segregation of chromosomes is a prominent feature of chromosome instability and intra-tumoral heterogeneity recurrent in metastatic tumors for which the molecular basis is unknown. The present study provides insight into the mechanism by which defects in rootletin, a centrosome linker component causes tetraploid segregation errors and

Stargardt disease: towards developing a model to predict phenotype.

PubMed

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

2013-10-01

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

Stargardt Disease: towards developing a model to predict phenotype

PubMed Central

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

2013-01-01

Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype–phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype–phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families. PMID:23695285

Genetic localization and phenotypic expression of X-linked cataract (Xcat) in Mus musculus.

PubMed

Favor, J; Pretsch, W

1990-01-01

Linkage data relative to the markers tabby and glucose-6-phosphate dehydrogenase are presented to locate X-linked cataract (Xcat) in the distal portion of the mouse X-chromosome between jimpy and hypophosphatemia. The human X-linked cataract-dental syndrome, Nance-Horan Syndrome, also maps closely to human hypophosphatemia and would suggest homology between mouse Xcat and human Nance-Horan Syndrome genes. In hemizygous males and homozygous females penetrance is complete with only slight variation in the degree of expression. Phenotypic expression in Xcat heterozygous females ranges from totally clear to totally opaque lenses. The phenotypic expression between the two lenses of a heterozygous individual could also vary between totally clear and totally opaque lenses. However, a correlation in the degree of expression between the eyes of an individual was observed. A variegated pattern of lens opacity was evident in female heterozygotes. Based on these observations, the site of gene action for the Xcat locus is suggested to be endogenous to the lens cells and the precursor cell population of the lens is concluded to be small. The identification of an X-linked cataract locus is an important contribution to the estimate of the number of mutable loci resulting in cataract, an estimate required so that dominant cataract mutagenesis results may be expressed on a per locus basis. The Xcat mutation may be a useful marker for a distal region of the mouse X-chromosome which is relatively sparsely marked and the X-linked cataract mutation may be employed in gene expression and lens development studies.

X-chromosomal inactivation directly influences the phenotypic manifestation of X-linked protoporphyria

PubMed Central

Brancaleoni, V.; Balwani, M.; Granata, F.; Graziadei, G.; Missineo, P.; Fiorentino, V.; Fustinoni, S.; Cappellini, M.D.; Naik, H.; Desnick, R.J.; Di Pierro, E.

2015-01-01

X-linked protoporphyria (XLP), a rare erythropoietic porphyria, results from terminal exon gain-of-function mutations in the ALAS2 gene causing increased ALAS2 activity and markedly increased erythrocyte protoporphyrin levels. Patients present with severe cutaneous photosensitivity and may develop liver dysfunction. XLP was originally reported as X-linked dominant with 100% penetrance in males and females. We characterized 11 heterozygous females from six unrelated XLP families and show markedly varying phenotypic and biochemical heterogeneity, reflecting the degree of X-chromsomal inactivation of the mutant gene. ALAS2 sequencing identified the specific mutation and confirmed heterozygosity among the females. Clinical history, plasma and erythrocyte protoporphyrin levels were determined. Methylation assays of the androgen receptor and zinc-finger MYM type 3 short tandem repeat polymorphisms estimated each heterozygotes X-chromosomal inactivation pattern. Heterozygotes with equal or increased skewing, favoring expression of the wild-type allele had no clinical symptoms and only slightly increased erythrocyte protoporphyrin concentrations and/or frequency of protoporphyrin-containing peripheral blood fluorocytes. When the wild-type allele was preferentially inactivated, heterozygous females manifested the disease phenotype and had both higher erythrocyte protoporphyrin levels and circulating fluorocytes. These findings confirm that the previous dominant classification of XLP is inappropriate and genetically misleading, as the disorder is more appropriately designated XLP. PMID:25615817

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

PubMed

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

2011-04-01

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

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

PubMed Central

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

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

Linking Plasma Cortisol Levels to Phenotypic Heterogeneity of Posttraumatic Stress Symptomatology

PubMed Central

Horn, Charlotte A.C.; Pietrzak, Robert H.; Corsi-Travali, Stefani; Neumeister, Alexander

2013-01-01

Introduction Recent confirmatory factor analytic studies of the dimensional structure of posttraumatic stress disorder (PTSD) suggest that this disorder may be best characterized by five symptom dimensions—re-experiencing, avoidance, numbing, dysphoric arousal, and anxious arousal. Hypothalamic-pituitary-adrenal (HPA) axis dysregulation in PTSD and has been attributed to enhanced glucocorticoid responsiveness. However, little is known about how altered HPA-axis function is related to this contemporary phenotypic model of PTSD. Methods We compared morning plasma cortisol levels of drug-free civilian adults with PTSD (N=29) to trauma-exposed (TC; N=12) and non trauma-exposed healthy controls (HC; N=23). We then examined the relation between cortisol levels and a contemporary 5-factor ‘dysphoric arousal’ model of PTSD symptoms among individuals with PTSD. Results After adjustment for white race/ethnicity, education, lifetime alcohol use disorder, and current smoking status, the PTSD (Cohen’s d=1.1) and TC (Cohen’s d=1.3) groups had significantly lower cortisol levels than the HC group; cortisol levels did not differ between the TC and PTSD groups. Except for age (r=−.46), none of the other demographic, trauma-related, or clinical variables, including lifetime mood/anxiety disorder and severity of current depressive and anxiety symptoms, were associated with cortisol levels. In a stepwise linear regression analysis, age (β= −.44) and severity of emotional numbing symptoms (β= −.35) were independently associated with cortisol levels in the PTSD group; none of the other PTSD symptom clusters or depression symptoms were significant. Post-hoc analyses revealed that severity of the emotional numbing symptom of restricted range of affect (i.e., unable to have loving feelings) was independently related to cortisol levels (β= −.35). Conclusion These results suggest that trauma-exposed civilian adults with and without PTSD have significantly lower cortisol

Sexual variation in assimilation efficiency: its link to phenotype and potential role in sexual dimorphism.

PubMed

Stahlschmidt, Zachary R; Davis, Jon R; Denardo, Dale F

2011-04-01

Sex-specific variation in morphology (sexual dimorphism) is a prevalent phenomenon among animals, and both dietary intake and resource allocation strategies influence sexually dimorphic traits (e.g., body size or composition). However, we investigated whether assimilation efficiency (AE), an intermediate step between dietary intake and allocation, can also vary between the sexes. Specifically, we tested whether sex-based differences in AE can explain variation in phenotypic traits. We measured morphometric characteristics (i.e., body length, mass, condition, and musculature) and AE of total energy, crude protein, and crude fat in post-reproductive adult Children's pythons (which exhibit a limited female-biased sexual size dimorphism) fed both low and high dietary intakes. Meal size was negatively related to AE of energy. Notably, male snakes absorbed crude protein more efficiently and increased epaxial (dorsal) musculature faster than females, which demonstrates a link between AE and phenotype. However, females grew in body length faster but did not absorb any nutrient more efficiently than males. Although our results do not provide a direct link between AE and sexual size dimorphism, they demonstrate that sexual variation in nutrient absorption exists and can contribute to other types of sex-based differences in phenotype (i.e., sexual dimorphism in growth of musculature). Hence, testing the broader applicability of AE's role in sexually dimorphic traits among other species is warranted.

Unusual phenotypic expression of an XLRS1 mutation in X-linked juvenile retinoschisis.

PubMed

Dodds, Jodi A; Srivastava, Anand K; Holden, Kenton R

2006-04-01

X-linked juvenile retinoschisis is a rare progressive vitreoretinal degenerative process that appears in early childhood, results in decreased visual acuity and blindness (if severe), and is caused by various mutations within the XLRS1 gene at Xp22.2. We report an affected family of Western European ancestry with X-linked juvenile retinoschisis. The family was found to carry a 304C-->T substitution in exon 4 of the XLRS1 gene, resulting in an Arg102Trp amino acid substitution. Two of the four available clinical cases in this family were found to carry the mutation. All available mothers of affected males were found to be unaffected carriers of the mutation, a typical feature of X-linked diseases. Two new female carriers, sisters of affected males, were identified and counseled accordingly. Questionnaires on visual functioning were given to the affected family members to examine the psychologic and sociologic impact of X-linked juvenile retinoschisis, which documented an associated stigma even when affected with a "mild" phenotype.

Correlation between connexin 32 gene mutations and clinical phenotype in X-linked dominant Charcot-Marie-Tooth neuropathy

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

Ionasescu, V.; Ionasescu, R.; Searby, C.

1996-06-14

We studied the relationship between the genotype and clinical phenotype in 27 families with dominant X-linked Charcot-Marie-Tooth (CMTX1) neuropathy. Twenty-two families showed mutations in the coding region of the connexin32 (cx32) gene. The mutations include four nonsense mutations, eight missense mutations, two medium size deletions, and one insertion. Most missense mutations showed a mild clinical phenotype (five out of eight), whereas all nonsense mutations, the larger of the two deletions, and the insertion that produced frameshifts showed severe phenotypes. Five CMTX1 families with mild clinical phenotype showed no point mutations of the cx32 gene coding region. Three of these familiesmore » showed positive genetic linkage with the markers of the Xq13.1 region. The genetic linkage of the remaining two families could not be evaluated because of their small size. 25 refs., 1 fig., 1 tab.« less

Interval singing links to phenotypic quality in a songbird

PubMed Central

2016-01-01

Darwin was fascinated by melodic performances of insects, fish, birds, mammals, and men. He considered the ability to produce musical notes without direct use the most mysterious endowment of mankind. Bird song is attributed to sexual selection, but it remains unknown how the expected relationship between melodic performance and phenotypic quality arises. Melodies consist of sequences of notes, and both Pythagoras and music theorists in the Middle Ages found that their tonal frequencies form simple ratios that correspond to small-integer proportions derived from the harmonic series. Harmonics are acoustically predictable, and thus form the basis of the natural, just tuning system in music. Here I analyze the songs of the great tit (Parus major), a bird with a stereotyped song of typically two notes, and test the prediction that the deviations of the intervals from small-integer frequency ratios based on the harmonic series are related to the quality of the singer. I show that the birds with the smallest deviations from small-integer ratios possess the largest melanin-based black ventral tie, a signal that has been demonstrated to indicate social status and dominance, past exposure to parasites, and reproductive potential. The singing of notes with exact frequency relationships requires high levels of motor control and auditory sensory feedback. The finding provides a missing link between melodic precision and phenotypic quality of individuals, which is key for understanding the evolution of vocal melodic expression in animals, and elucidates pathways for the evolution of melodic expression in music. PMID:27791124

Metabolomic phenotyping of a cloned pig model

PubMed Central

2011-01-01

Background Pigs are widely used as models for human physiological changes in intervention studies, because of the close resemblance between human and porcine physiology and the high degree of experimental control when using an animal model. Cloned animals have, in principle, identical genotypes and possibly also phenotypes and this offer an extra level of experimental control which could possibly make them a desirable tool for intervention studies. Therefore, in the present study, we address how phenotype and phenotypic variation is affected by cloning, through comparison of cloned pigs and normal outbred pigs. Results The metabolic phenotype of cloned pigs (n = 5) was for the first time elucidated by nuclear magnetic resonance (NMR)-based metabolomic analysis of multiple bio-fluids including plasma, bile and urine. The metabolic phenotype of the cloned pigs was compared with normal outbred pigs (n = 6) by multivariate data analysis, which revealed differences in the metabolic phenotypes. Plasma lactate was higher for cloned vs control pigs, while multiple metabolites were altered in the bile. However a lower inter-individual variability for cloned pigs compared with control pigs could not be established. Conclusions From the present study we conclude that cloned and normal outbred pigs are phenotypically different. However, it cannot be concluded that the use of cloned animals will reduce the inter-individual variation in intervention studies, though this is based on a limited number of animals. PMID:21859467

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

PubMed Central

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

2004-01-01

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

Monogenic Mouse Models of Autism Spectrum Disorders: Common Mechanisms and Missing Links

PubMed Central

Hulbert, Samuel W.; Jiang, Yong-hui

2016-01-01

Autism Spectrum Disorders (ASDs) present unique challenges in the fields of genetics and neurobiology because of the clinical and molecular heterogeneity underlying these disorders. Genetic mutations found in ASD patients provide opportunities to dissect the molecular and circuit mechanisms underlying autistic behaviors using animal models. Ongoing studies of genetically modified models have offered critical insight into possible common mechanisms arising from different mutations, but links between molecular abnormalities and behavioral phenotypes remain elusive. The challenges encountered in modeling autism in mice demand a new analytic paradigm that integrates behavioral analysis with circuit-level analysis in genetically modified models with strong construct validity. PMID:26733386

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688

Classifying compound mechanism of action for linking whole cell phenotypes to molecular targets

PubMed Central

Bourne, Christina R.; Wakeham, Nancy; Bunce, Richard A.; Berlin, K. Darrell; Barrow, William W.

2013-01-01

Drug development programs have proven successful when performed at a whole cell level, thus incorporating solubility and permeability into the primary screen. However, linking those results to the target within the cell has been a major set-back. The Phenotype Microarray system, marketed and sold by Biolog, seeks to address this need by assessing the phenotype in combination with a variety of chemicals with known mechanism of action (MOA). We have evaluated this system for usefulness in deducing the MOA for three test compounds. To achieve this, we constructed a database with 21 known antimicrobials, which served as a comparison for grouping our unknown MOA compounds. Pearson correlation and Ward linkage calculations were used to generate a dendrogram that produced clustering largely by known MOA, although there were exceptions. Of the three unknown compounds, one was definitively placed as an anti-folate. The second and third compounds’ MOA were not clearly identified, likely due to unique MOA not represented within the commercial database. The availability of the database generated in this report for S. aureus ATCC 29213 will increase the accessibility of this technique to other investigators. From our analysis, the Phenotype Microarray system can group compounds with clear MOA, but distinction of unique or broadly acting MOA at this time is less clear. PMID:22434711

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

PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.

PubMed

Glueck, Michael; Naeini, Mahdi Pakdaman; Doshi-Velez, Finale; Chevalier, Fanny; Khan, Azam; Wigdor, Daniel; Brudno, Michael

2018-01-01

PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving prevalence and co-occurrence of phenotypes-without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.

Modularity of nitrogen-oxide reducing soil bacteria: linking phenotype to genotype.

PubMed

Roco, Constance A; Bergaust, Linda L; Bakken, Lars R; Yavitt, Joseph B; Shapleigh, James P

2017-06-01

Model denitrifiers convert NO3- to N 2 , but it appears that a significant fraction of natural populations are truncated, conducting only one or two steps of the pathway. To better understand the diversity of partial denitrifiers in soil and whether discrepancies arise between the presence of known N-oxide reductase genes and phenotypic features, bacteria able to reduce NO3- to NO2- were isolated from soil, N-oxide gas products were measured for eight isolates, and six were genome sequenced. Gas phase analyses revealed that two were complete denitrifiers, which genome sequencing corroborated. The remaining six accumulated NO and N 2 O to varying degrees and genome sequencing of four indicated that two isolates held genes encoding nitrate reductase as the only dissimilatory N-oxide reductase, one contained genes for both nitrate and nitric oxide reductase, and one had nitrate and nitrite reductase. The results demonstrated that N-oxide production was not always predicted by the genetic potential and suggested that partial denitrifiers could be readily isolated among soil bacteria. This supported the hypothesis that each N-oxide reductase could provide a selectable benefit on its own, and therefore, reduction of nitrate to dinitrogen may not be obligatorily linked to complete denitrifiers but instead a consequence of a functionally diverse community. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

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.

Validation and discovery of genotype-phenotype associations in chronic diseases using linked data.

PubMed

Pathak, Jyotishman; Kiefer, Richard; Freimuth, Robert; Chute, Christopher

2012-01-01

This study investigates federated SPARQL queries over Linked Open Data (LOD) in the Semantic Web to validate existing, and potentially discover new genotype-phenotype associations from public datasets. In particular, we report our preliminary findings for identifying such associations for commonly occurring chronic diseases using the Online Mendelian Inheritance in Man (OMIM) and Database for SNPs (dbSNP) within the LOD knowledgebase and compare them with Gene Wiki for coverage and completeness. Our results indicate that Semantic Web technologies can play an important role for in-silico identification of novel disease-gene-SNP associations, although additional verification is required before such information can be applied and used effectively.

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

PubMed Central

Lomnitz, Jason G.; Savageau, Michael A.

2016-01-01

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

Airway disease phenotypes in animal models of cystic fibrosis.

PubMed

McCarron, Alexandra; Donnelley, Martin; Parsons, David

2018-04-02

In humans, cystic fibrosis (CF) lung disease is characterised by chronic infection, inflammation, airway remodelling, and mucus obstruction. A lack of pulmonary manifestations in CF mouse models has hindered investigations of airway disease pathogenesis, as well as the development and testing of potential therapeutics. However, recently generated CF animal models including rat, ferret and pig models demonstrate a range of well characterised lung disease phenotypes with varying degrees of severity. This review discusses the airway phenotypes of currently available CF animal models and presents potential applications of each model in airway-related CF research.

Phenotypic characterization of X-linked retinoschisis: Clinical, electroretinography, and optical coherence tomography variables

PubMed Central

Neriyanuri, Srividya; Dhandayuthapani, Sudha; Arunachalam, Jayamuruga Pandian; Raman, Rajiv

2016-01-01

Aims: To study the phenotypic characteristics of X-linked retinoschisis (XLRS) and report the clinical, electroretinogram (ERG), and optical coherence tomography (OCT) variables in Indian eyes. Design: A retrospective study. Materials and Methods: Medical records of 21 patients with retinoschisis who were genetically confirmed to have RS1 mutation were reviewed. The phenotype characterization included the age of onset, best-corrected visual acuity, refractive error, fundus findings, OCT, and ERG. Statistical Analysis Used: Data from both the eyes were used for analysis. A P < 0.05 was set as statistical significance. Data were not normally distributed (P < 0.05, Shapiro wilk); hence, nonparametric tests were used for statistical analysis. Results: All were males whose mean age of presentation was 9 years. Visual acuity was moderately impaired (median 0.6 logMAR, interquartile range: 0.47, 1) in these eyes with a hyperopic refractive error of median +1.75 Ds (interquartile range: +0.50 Ds, +4.25 Ds). About 54.7% of the eyes had both foveal and peripheral schisis, isolated foveal schisis was seen in 28.5% of the eyes, and schisis with retinal detachment was seen in 16.6% of the eyes. The inner nuclear layer was found to be commonly involved in the schisis, followed by outer nuclear and plexiform layers as evident on OCT. On ERG, a- and b-wave amplitudes were significantly reduced in eyes with foveal and peripheral schisis when compared to the eyes with only foveal schisis (P < 0.05). Conclusions: XLRS has phenotypic heterogeneity as evident on OCT, ERG, and clinical findings. PMID:27609164

Open loop model for WDM links

NASA Astrophysics Data System (ADS)

D, Meena; Francis, Fredy; T, Sarath K.; E, Dipin; Srinivas, T.; K, Jayasree V.

2014-10-01

Wavelength Division Multiplexing (WDM) techniques overfibrelinks helps to exploit the high bandwidth capacity of single mode fibres. A typical WDM link consisting of laser source, multiplexer/demultiplexer, amplifier and detectoris considered for obtaining the open loop gain model of the link. The methodology used here is to obtain individual component models using mathematical and different curve fitting techniques. These individual models are then combined to obtain the WDM link model. The objective is to deduce a single variable model for the WDM link in terms of input current to system. Thus it provides a black box solution for a link. The Root Mean Square Error (RMSE) associated with each of the approximated models is given for comparison. This will help the designer to select the suitable WDM link model during a complex link design.

Mutation in a locus linked to penB-nmp causes suppression of the Mtr phenotype of Neisseria gonorrhoeae.

PubMed Central

Shinners, E N; Catlin, B W

1988-01-01

The chromosomal locus mtr, which encodes low-level resistance to multiple antibacterial agents in Neisseria gonorrhoeae, is subject to phenotypic suppression by env mutations that increase the permeability of the envelope. We have identified a new locus, mom (for modifier of Mtr), which is located on the chromosome very close to penB and nmp, loci known to be linked to each other and to spc. Phenotypic suppression of Mtr was recognized by reductions of resistance to benzylpenicillin and also to oxacillin and the hydrophobic agents novobiocin and erythromycin. The resistance to each of these antibiotics returned to the Mtr levels in mom+ transformants isolated by selection for increased resistance to either novobiocin or erythromycin; the accompanying change of the outer membrane protein I seroreactions confirmed the proximity of nmp and mom. Thus, some mutant gonococci display wild-type antibiotic susceptibilities but can express multiple resistance following a mom+ mutation that releases the suppressed Mtr phenotype. PMID:3142343

Genotype-phenotype correlation in boys with X-linked hypohidrotic ectodermal dysplasia.

PubMed

Burger, Kristin; Schneider, Anne-Theres; Wohlfart, Sigrun; Kiesewetter, Franklin; Huttner, Kenneth; Johnson, Ramsey; Schneider, Holm

2014-10-01

X-linked hypohidrotic ectodermal dysplasia (XLHED), the most frequent form of ectodermal dysplasia, is a genetic disorder of ectoderm development characterized by malformation of multiple ectodermal structures such as skin, hair, sweat and sebaceous glands, and teeth. The disease is caused by a broad spectrum of mutations in the gene EDA. Although XLHED symptoms show inter-familial and intra-familial variability, genotype-phenotype correlation has been demonstrated with respect to sweat gland function. In this study, we investigated to which extent the EDA genotype correlates with the severity of XLHED-related skin and hair signs. Nineteen male children with XLHED (age range 3-14 years) and seven controls (aged 6-14 years) were examined by confocal microscopy of the skin, quantification of pilocarpine-induced sweating, semi-quantitative evaluation of full facial photographs with respect to XLHED-related skin issues, and phototrichogram analysis. All eight boys with known hypomorphic EDA mutations were able to produce at least some sweat and showed less severe cutaneous signs of XLHED than the anhidrotic XLHED patients (e.g., perioral and periorbital eczema or hyperpigmentation, regional hyperkeratosis, characteristic wrinkles under the eyes). As expected, individuals with XLHED had significantly less and thinner hair than healthy controls. However, there were also significant differences in hair number, diameter, and other hair characteristics between the group with hypomorphic EDA mutations and the anhidrotic patients. In summary, this study indicated a remarkable genotype-phenotype correlation of skin and hair findings in prepubescent males with XLHED. © 2014 Wiley Periodicals, Inc.

Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.

PubMed

Martin, Guillaume

2014-05-01

Models relating phenotype space to fitness (phenotype-fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher's geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model "from first principles" is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher's model's assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.

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

PubMed

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

2016-12-01

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

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.

Cookie-Ases: Interactive Models for Teaching Genotype-Phenotype Relationships

ERIC Educational Resources Information Center

Seipelt, Rebecca L.

2006-01-01

Several hands-on and wet laboratory activities have been proposed to model the genetic concepts of genotypes and phenotypes and their relationship. The exercise presented in this article is a novel, time effective, student-centered, role-playing activity in which students learn about the intricate connection between genotype and phenotype by…

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

Mutations in the gene for X-linked adrenoleukodystrophy in patients with different clinical phenotypes

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

Braun, A.; Ambach, H.; Kammerer, S.

Recently, the gene for the most common peroxisomal disorder, X-linked adrenoleukodystrophy (X-ALD), has been described encoding a peroxisomal membrane transporter protein. We analyzed the entire protein-coding sequence of this gene by reverse-transcription PCR, SSCP, and DNA sequencing in five patients with different clinical expressions were cerebral childhood ALD, adrenomyecloneuropathy (AMN), and {open_quotes}Addison disease only{close_quotes} (AD) phenotype. In the three patients exhibiting the classical picture of severe childhood ALD we identified in the 5{prime} portion of the X-ALD gene a 38-bp deletion that causes a frameshift mutation, a 3-bp deletion leading to a deletion of an amino acid in the ATP-bindingmore » domain of the ALD protein, and a missense mutation. In the patient with the clinical phenotype of AMN, a nonsense mutation in codon 212, along with a second site mutation at codon 178, was observed. Analysis of the patient with the ADO phenotype revealed a further missense mutation at a highly conserved position in the ALDP/PMP70 comparison. The disruptive nature of two mutations (i.e., the frameshift and the nonsense mutation) in patients with biochemically proved childhood ALD and AMN further strongly supports the hypothesis that alterations in this gene play a crucial role in the pathogenesis of X-ALD. Since the current biochemical techniques for X-ALD carrier detection in affected families lack sufficient reliability, our procedure described for systematic mutation scanning is also capable of improving genetic counseling and prenatal diagnosis. 19 refs., 6 figs., 3 tabs.« less

Psoriasis and polycystic ovary syndrome: a new link in different phenotypes.

PubMed

Moro, Francesca; Tropea, Anna; Scarinci, Elisa; Federico, Alex; De Simone, Clara; Caldarola, Giacomo; Leoncini, Emanuele; Boccia, Stefania; Lanzone, Antonio; Apa, Rosanna

2015-08-01

Women affected by PCOS and psoriasis are more likely to have insulin-resistance, hyperinsulinemia, reduced HDL cholesterol levels and a more severe degree of skin disease than those with psoriasis alone. The mechanism underlying this association between PCOS and psoriasis is currently unknown. The aim of the present study was to evaluate the features of psoriasis and the psoriasis severity scores in the different PCOS phenotypes and in age and body mass index (BMI)-matched psoriatic control patients. A cross-sectional study was performed on 150 psoriatic patients: 94 PCOS and 56 age- and BMI-matched controls. PCOS patients were diagnosed and divided into four phenotypes according to Rotterdam criteria: A - patients with complete phenotype with hyperandrogenism (H) plus oligoamenorrhea (O) plus polycystic ovary (PCO) on ultrasound examination; B - patients with H plus O (without PCO); C - patients with H plus PCO (ovulatory phenotype); D - patients with O plus PCO (without H). The patient's Psoriasis Area and Severity Index (PASI) as well as the Physician's Global Assessment (PGA) were calculated. A PASI score ≥10 was correlated with common indicator of severe disease. A PGA ≥4 was considered as a condition of moderate to severe disease. Among the four phenotypes investigated, the group with complete phenotype (H plus O plus PCO) had a higher prevalence of patients with patient's PASI ≥10 compared to controls (Odds Ratio (OR) 4.71, 95% confidence intervals (CI) 1.59-13.95). The group with O plus PCO had a higher prevalence of patients with PGA ≥4 compared to controls (OR 26.79, 95% CI 3.40-211.02) while the ovulatory group had a lower prevalence of patients with PGA ≥4 (OR 0.06, 95% CI 0.01-0.51). The ovulatory phenotype displays a milder psoriasis form than other phenotypes while the phenotypes with oligoamenorrhea presented higher severity scores of disease than other phenotypes and control group. Copyright © 2015 Elsevier Ireland Ltd. All rights

Characterization of X-linked Hypohidrotic Ectodermal Dysplasia (XL-HED) Hair and Sweat Gland Phenotypes Using Phototrichogram Analysis and Live Confocal Imaging

PubMed Central

Jones, Kyle B.; Goodwin, Alice F.; Landan, Maya; Seidel, Kerstin; Tran, Dong-Kha; Hogue, Jacob; Chavez, Miquella; Fete, Mary; Yu, Wenli; Hussein, Tarek; Johnson, Ramsey; Huttner, Kenneth; Jheon, Andrew H.; Klein, Ophir D.

2015-01-01

Hypohidrotic ectodermal dysplasia (HED) is the most common type of ectodermal dysplasia (ED), which encompasses a large group of syndromes that share several phenotypic features such as missing or malformed ectodermal structures, including skin, hair, sweat glands, and teeth. X-linked hypohidrotic ectodermal dysplasia (XL-HED) is associated with mutations in ectodysplasin (EDA1). Hypohidrosis due to hypoplastic sweat glands and thin, sparse hair are phenotypic features that significantly affect the daily lives of XL-HED individuals and therefore require systematic analysis. We sought to determine the quality of life of individuals with XL-HED and to quantify sweat duct and hair phenotypes using confocal imaging, pilocarpine iontophoresis, and phototrichogram analysis. Using these highly sensitive and non-invasive techniques, we demonstrated that 11/12 XL-HED individuals presented with a complete absence of sweat ducts and that none produced sweat. We determined that the thin hair phenotype observed in XL-HED was due to multiple factors, such as fewer terminal hairs with decreased thickness and slower growth rate, as well as fewer follicular units and fewer hairs per unit. The precise characterization of XL-HED phenotypes using sensitive and non-invasive techniques presented in our study will improve upon larger genotype-phenotype studies and in the assessment of future therapies in XL-HED. PMID:23687000

Novel Phenotypic and Genotypic Findings in X-Linked Retinoschisis

PubMed Central

Tsang, Stephen H.; Vaclavik, Veronika; Bird, Alan C.; Robson, Anthony G.; Holder, Graham E.

2009-01-01

Objective To describe atypical phenotypes associated with the retinoschisis (X-linked, juvenile) 1 mutation (RS1). Methods Seven patients with multiple fine white dots at the macula and reduced visual acuity were evaluated. Six patients underwent pattern and full-field electroretinography (ERG). On-off ERG, optical coherence tomography, and fundus autofluorescence imaging were performed in some patients. Mutational screening of RS1 was prompted by the ERG findings. Results Fine white dots resembling drusenlike deposits and sometimes associated with retinal pigment epithelial abnormalities were present in the maculae. An electronegative bright-flash ERG configuration was present in all patients tested, and abnormal pattern ERG findings confirmed macular dysfunction. A parafoveal ring of high-density autofluorescence was present in 3 eyes; 1 patient showed high-density foci concordant with the white dots. Optical coherence tomography did not show foveal schisis in 3 of 4 eyes. All patients carried mutations in RS1, including 1 with a novel 206T→C mutation in exon 4. Conclusions Multiple fine white dots at the macula may be the initial fundus feature in RS1 mutation. Electrophysiologic findings suggest dysfunction after phototransduction and enable focused mutational screening. Autofluorescence imaging results suggest early retinal pigment epithelium involvement; a parafoveal ring of high-density autofluorescence has not previously been described in this disorder. PMID:17296904

Warped linear mixed models for the genetic analysis of transformed phenotypes

PubMed Central

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

2014-01-01

Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a requirement that rarely holds in practice. Violations of this assumption can lead to false conclusions and loss in power. To mitigate this problem, it is common practice to pre-process the phenotypic values to make them as Gaussian as possible, for instance by applying logarithmic or other nonlinear transformations. Unfortunately, different phenotypes require different transformations, and choosing an appropriate transformation is challenging and subjective. Here we present an extension of the LMM that estimates an optimal transformation from the observed data. In simulations and applications to real data from human, mouse and yeast, we show that using transformations inferred by our model increases power in genome-wide association studies and increases the accuracy of heritability estimation and phenotype prediction. PMID:25234577

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

PubMed

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

2014-09-19

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

Ion Mobility-Mass Spectrometry Analysis of Serum N-linked Glycans from Esophageal Adenocarcinoma Phenotypes

PubMed Central

Gaye, M. M.; Valentine, S. J.; Hu, Y.; Mirjankar, N.; Hammoud, Z. T.; Mechref, Y.; Lavine, B. K.; Clemmer, D. E.

2012-01-01

Three disease phenotypes, Barrett’s esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS) and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including: 7 characterized as BE, 12 as HGD, 56 as EAC and 61 as NC. In typical datasets it was possible to assign ~20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for eleven N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution. PMID:23126309

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

PubMed

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

2014-09-01

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

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

Efficacy of the highly selective focal adhesion kinase inhibitor BI 853520 in adenocarcinoma xenograft models is linked to a mesenchymal tumor phenotype.

PubMed

Hirt, Ulrich A; Waizenegger, Irene C; Schweifer, Norbert; Haslinger, Christian; Gerlach, Daniel; Braunger, Jürgen; Weyer-Czernilofsky, Ulrike; Stadtmüller, Heinz; Sapountzis, Ioannis; Bader, Gerd; Zoephel, Andreas; Bister, Bojan; Baum, Anke; Quant, Jens; Kraut, Norbert; Garin-Chesa, Pilar; Adolf, Günther R

2018-02-23

Focal adhesion kinase (FAK), a non-receptor tyrosine kinase, has attracted interest as a target for pharmacological intervention in malignant diseases. Here, we describe BI 853520, a novel ATP-competitive inhibitor distinguished by high potency and selectivity. In vitro, the compound inhibits FAK autophosphorylation in PC-3 prostate carcinoma cells with an IC 50 of 1 nmol/L and blocks anchorage-independent proliferation of PC-3 cells with an EC 50 of 3 nmol/L, whereas cells grown in conventional surface culture are 1000-fold less sensitive. In mice, the compound shows long half-life, high volume of distribution and high oral bioavailability; oral dosing of immunodeficient mice bearing subcutaneous PC-3 prostate adenocarcinoma xenografts resulted in rapid, long-lasting repression of FAK autophosphorylation in tumor tissue. Daily oral administration of BI 853520 to nude mice at doses of 50 mg/kg was well tolerated for prolonged periods of time. In a diverse panel of 16 subcutaneous adenocarcinoma xenograft models in nude mice, drug treatment resulted in a broad spectrum of outcomes, ranging from group median tumor growth inhibition values >100% and tumor regression in subsets of animals to complete lack of sensitivity. Biomarker analysis indicated that high sensitivity is linked to a mesenchymal tumor phenotype, initially defined by loss of E-cadherin expression and subsequently substantiated by gene set enrichment analysis. Further, we obtained microRNA expression profiles for 13 models and observed that hsa-miR-200c-3p expression is strongly correlated with efficacy (R 2  = 0.889). BI 853520 is undergoing evaluation in early clinical trials.

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

Leaky phenotype of X-linked agammaglobulinaemia in a Japanese family

PubMed Central

Kaneko, H; Kawamoto, N; Asano, T; Mabuchi, Y; Horikoshi, H; Teramoto, T; JIN-RONG; Matsui, E; Kondo, M; Fukao, T; Kasahara, K; Kondo, N

2005-01-01

X-linked agammaglobulinaemia (XLA) is an inherited immunodeficiency that is caused by a block in early B-cell differentiation. Whereas early B precursors in the bone marrow are present in substantial numbers, XLA-affected individuals have dramatically reduced numbers of circulating mature B cells, plasma cells and immunoglobulins of all isotypes. We report on a Japanese family with 3 XLA patients, in whom the serum immunoglobulin levels and number of B cells showed a significant difference among them in spite of harbouring the same splice donor site mutation in the BTK gene. We developed concise method for detection of this mutation, which is helpful for discovering the carrier. Patient 2 showed a significant serum immunoglobulin levels of all isotypes, including allergen-specific IgE. Expression of a normal and truncated size BTK gene was detected in patient 2′s peripheral blood mononuclear cells (PBMCs). Expression of BTK protein was also detected in some B cells. These results suggest that the leaky phenotype in patient 2 was caused in part by the expression of a normal BTK gene transcript. The increased frequency of infection with age expanded the number of B cells with normal BTK gene expression and produced the serum immunoglobulin, including IgE. PMID:15932514

Cell and small animal models for phenotypic drug discovery.

PubMed

Szabo, Mihaly; Svensson Akusjärvi, Sara; Saxena, Ankur; Liu, Jianping; Chandrasekar, Gayathri; Kitambi, Satish S

2017-01-01

The phenotype-based drug discovery (PDD) approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s) or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery.

Alterations in muscle mass and contractile phenotype in response to unloading models: role of transcriptional/pretranslational mechanisms

PubMed Central

Baldwin, Kenneth M.; Haddad, Fadia; Pandorf, Clay E.; Roy, Roland R.; Edgerton, V. Reggie

2013-01-01

Skeletal muscle is the largest organ system in mammalian organisms providing postural control and movement patterns of varying intensity. Through evolution, skeletal muscle fibers have evolved into three phenotype clusters defined as a motor unit which consists of all muscle fibers innervated by a single motoneuron linking varying numbers of fibers of similar phenotype. This fundamental organization of the motor unit reflects the fact that there is a remarkable interdependence of gene regulation between the motoneurons and the muscle mainly via activity-dependent mechanisms. These fiber types can be classified via the primary type of myosin heavy chain (MHC) gene expressed in the motor unit. Four MHC gene encoded proteins have been identified in striated muscle: slow type I MHC and three fast MHC types, IIa, IIx, and IIb. These MHCs dictate the intrinsic contraction speed of the myofiber with the type I generating the slowest and IIb the fastest contractile speed. Over the last ~35 years, a large body of knowledge suggests that altered loading state cause both fiber atrophy/wasting and a slow to fast shift in the contractile phenotype in the target muscle(s). Hence, this review will examine findings from three different animal models of unloading: (1) space flight (SF), i.e., microgravity; (2) hindlimb suspension (HS), a procedure that chronically eliminates weight bearing of the lower limbs; and (3) spinal cord isolation (SI), a surgical procedure that eliminates neural activation of the motoneurons and associated muscles while maintaining neurotrophic motoneuron-muscle connectivity. The collective findings demonstrate: (1) all three models show a similar pattern of fiber atrophy with differences mainly in the magnitude and kinetics of alteration; (2) transcriptional/pretranslational processes play a major role in both the atrophy process and phenotype shifts; and (3) signaling pathways impacting these alterations appear to be similar in each of the models

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.

Structural Modeling Insights into Human VKORC1 Phenotypes

PubMed Central

Czogalla, Katrin J.; Watzka, Matthias; Oldenburg, Johannes

2015-01-01

Vitamin K 2,3-epoxide reductase complex subunit 1 (VKORC1) catalyses the reduction of vitamin K and its 2,3-epoxide essential to sustain γ-carboxylation of vitamin K-dependent proteins. Two different phenotypes are associated with mutations in human VKORC1. The majority of mutations cause resistance to 4-hydroxycoumarin- and indandione-based vitamin K antagonists (VKA) used in the prevention and therapy of thromboembolism. Patients with these mutations require greater doses of VKA for stable anticoagulation than patients without mutations. The second phenotype, a very rare autosomal-recessive bleeding disorder caused by combined deficiency of vitamin K dependent clotting factors type 2 (VKCFD2) arises from a homozygous Arg98Trp mutation. The bleeding phenotype can be corrected by vitamin K administration. Here, we summarize published experimental data and in silico modeling results in order to rationalize the mechanisms of VKA resistance and VKCFD2. PMID:26287237

Phenotypic characterization of glioblastoma identified through shape descriptors

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

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

A review of standardized metabolic phenotyping of animal models.

PubMed

Rozman, Jan; Klingenspor, Martin; Hrabě de Angelis, Martin

2014-10-01

Metabolic phenotyping of genetically modified animals aims to detect new candidate genes and related metabolic pathways that result in dysfunctional energy balance regulation and predispose for diseases such as obesity or type 2 diabetes mellitus. In this review, we provide a comprehensive overview on the technologies available to monitor energy flux (food uptake, bomb calorimetry of feces and food, and indirect calorimetry) and body composition (qNMR, DXA, and MRI) in animal models for human diseases with a special focus on phenotyping methods established in genetically engineered mice. We use an energy flux model to illustrate the principles of energy allocation, describe methodological aspects how to monitor energy balance, and introduce strategies for data analysis and presentation.

Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

PubMed Central

Reinagel, Adam; Bray Speth, Elena

2016-01-01

In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students’ understanding of 1) the origin of variation in a population and 2) how genes/alleles determine phenotypes. Guided by theory on hierarchical development of systems-thinking skills, we scaffolded instruction and assessment so that students would first focus on articulating isolated relationships between pairs of molecular genetics structures and then integrate these relationships into an explanatory network. We analyzed models students generated on two exams to assess whether students’ learning of molecular genetics progressed along the theoretical hierarchical sequence of systems-thinking skills acquisition. With repeated practice, peer discussion, and instructor feedback over the course of the semester, students’ models became more accurate, better contextualized, and more meaningful. At the end of the semester, however, more than 25% of students still struggled to describe phenotype as an output of protein function. We therefore recommend that 1) practices like modeling, which require connecting genes to phenotypes; and 2) well-developed case studies highlighting proteins and their functions, take center stage in molecular genetics instruction. PMID:26903496

Acquisition of Epithelial-Mesenchymal Transition phenotype of gemcitabine-resistant pancreatic cancer cells is linked with activation of Notch signaling pathway

PubMed Central

Wang, Zhiwei; Li, Yiwei; Kong, Dejuan; Banerjee, Sanjeev; Ahmad, Aamir; Azmi, Asfar Sohail; Ali, Shadan; Abbruzzese, James L.; Gallick, Gary E.; Sarkar, Fazlul H

2009-01-01

Despite rapid advances in many fronts, pancreatic cancer (PC) remains one of the most difficult human malignancies to treat, in part due to de novo and acquired chemo- and radio-resistance. Gemcitabine alone or in combination with other conventional therapeutics is the standard of care for the treatment of advanced PC without any significant improvement in the overall survival of patients diagnosed with this deadly disease. Previous studies have shown that PC cells that are gemcitabine-resistant (GR) acquired epithelial-mesenchymal transition (EMT) phenotype which is reminiscent of “cancer stem-like cells (CSC)”; however the molecular mechanism that led to EMT phenotype has not been fully investigated. The present study demonstrates that Notch-2 and its ligand Jagged-1 are highly up-regulated in GR cells, which is consistent with the role of Notch signaling pathway in the acquisition of EMT and CSC phenotype. We also found that the down-regulation of Notch signaling was associated with decreased invasive behavior of GR cells. Moreover, down-regulation of Notch signaling by siRNA approach led to partial reversal of the EMT phenotype, resulting in the mesenchymal-epithelial transition (MET), which was associated with decreased expression of vimentin, ZEB1, Slug, Snail and NF-κB. These results provide molecular evidence showing that the activation of Notch signaling is mechanistically linked with chemo-resistance phenotype (EMT phenotype) of PC cells, suggesting that the inactivation of Notch signaling by novel strategies could be a potential targeted therapeutic approach for overcoming chemo-resistance toward the prevention of tumor progression and/or treatment of metastatic PC. PMID:19276344

The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching

PubMed Central

Howe, Douglas G.; Bradford, Yvonne M.; Eagle, Anne; Fashena, David; Frazer, Ken; Kalita, Patrick; Mani, Prita; Martin, Ryan; Moxon, Sierra Taylor; Paddock, Holly; Pich, Christian; Ramachandran, Sridhar; Ruzicka, Leyla; Schaper, Kevin; Shao, Xiang; Singer, Amy; Toro, Sabrina; Van Slyke, Ceri; Westerfield, Monte

2017-01-01

The Zebrafish Model Organism Database (ZFIN; http://zfin.org) is the central resource for zebrafish (Danio rerio) genetic, genomic, phenotypic and developmental data. ZFIN curators provide expert manual curation and integration of comprehensive data involving zebrafish genes, mutants, transgenic constructs and lines, phenotypes, genotypes, gene expressions, morpholinos, TALENs, CRISPRs, antibodies, anatomical structures, models of human disease and publications. We integrate curated, directly submitted, and collaboratively generated data, making these available to zebrafish research community. Among the vertebrate model organisms, zebrafish are superbly suited for rapid generation of sequence-targeted mutant lines, characterization of phenotypes including gene expression patterns, and generation of human disease models. The recent rapid adoption of zebrafish as human disease models is making management of these data particularly important to both the research and clinical communities. Here, we describe recent enhancements to ZFIN including use of the zebrafish experimental conditions ontology, ‘Fish’ records in the ZFIN database, support for gene expression phenotypes, models of human disease, mutation details at the DNA, RNA and protein levels, and updates to the ZFIN single box search. PMID:27899582

Link-topic model for biomedical abbreviation disambiguation.

PubMed

Kim, Seonho; Yoon, Juntae

2015-02-01

The ambiguity of biomedical abbreviations is one of the challenges in biomedical text mining systems. In particular, the handling of term variants and abbreviations without nearby definitions is a critical issue. In this study, we adopt the concepts of topic of document and word link to disambiguate biomedical abbreviations. We newly suggest the link topic model inspired by the latent Dirichlet allocation model, in which each document is perceived as a random mixture of topics, where each topic is characterized by a distribution over words. Thus, the most probable expansions with respect to abbreviations of a given abstract are determined by word-topic, document-topic, and word-link distributions estimated from a document collection through the link topic model. The model allows two distinct modes of word generation to incorporate semantic dependencies among words, particularly long form words of abbreviations and their sentential co-occurring words; a word can be generated either dependently on the long form of the abbreviation or independently. The semantic dependency between two words is defined as a link and a new random parameter for the link is assigned to each word as well as a topic parameter. Because the link status indicates whether the word constitutes a link with a given specific long form, it has the effect of determining whether a word forms a unigram or a skipping/consecutive bigram with respect to the long form. Furthermore, we place a constraint on the model so that a word has the same topic as a specific long form if it is generated in reference to the long form. Consequently, documents are generated from the two hidden parameters, i.e. topic and link, and the most probable expansion of a specific abbreviation is estimated from the parameters. Our model relaxes the bag-of-words assumption of the standard topic model in which the word order is neglected, and it captures a richer structure of text than does the standard topic model by considering

Model-Independent Phenotyping of C. elegans Locomotion Using Scale-Invariant Feature Transform

PubMed Central

Koren, Yelena; Sznitman, Raphael; Arratia, Paulo E.; Carls, Christopher; Krajacic, Predrag; Brown, André E. X.; Sznitman, Josué

2015-01-01

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior. PMID:25816290

Cross-Link Guided Molecular Modeling with ROSETTA

PubMed Central

Leitner, Alexander; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2013-01-01

Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods. PMID:24069194

Identification of Multiple QTLs Linked to Neuropathology in the Engrailed-1 Heterozygous Mouse Model of Parkinson's Disease.

PubMed

Kurowska, Zuzanna; Jewett, Michael; Brattås, Per Ludvik; Jimenez-Ferrer, Itzia; Kenéz, Xuyian; Björklund, Tomas; Nordström, Ulrika; Brundin, Patrik; Swanberg, Maria

2016-08-23

Motor symptoms in Parkinson's disease are attributed to degeneration of midbrain dopaminergic neurons (DNs). Heterozygosity for Engrailed-1 (En1), one of the key factors for programming and maintenance of DNs, results in a parkinsonian phenotype featuring progressive degeneration of DNs in substantia nigra pars compacta (SNpc), decreased striatal dopamine levels and swellings of nigro-striatal axons in the SwissOF1-En1+/- mouse strain. In contrast, C57Bl/6-En1+/- mice do not display this neurodegenerative phenotype, suggesting that susceptibility to En1 heterozygosity is genetically regulated. Our goal was to identify quantitative trait loci (QTLs) that regulate the susceptibility to PD-like neurodegenerative changes in response to loss of one En1 allele. We intercrossed SwissOF1-En1+/- and C57Bl/6 mice to obtain F2 mice with mixed genomes and analyzed number of DNs in SNpc and striatal axonal swellings in 120 F2-En1+/- 17 week-old male mice. Linkage analyses revealed 8 QTLs linked to number of DNs (p = 2.4e-09, variance explained = 74%), 7 QTLs linked to load of axonal swellings (p = 1.7e-12, variance explained = 80%) and 8 QTLs linked to size of axonal swellings (p = 7.0e-11, variance explained = 74%). These loci should be of prime interest for studies of susceptibility to Parkinson's disease-like damage in rodent disease models and considered in clinical association studies in PD.

Optimizing complex phenotypes through model-guided multiplex genome engineering

DOE PAGES

Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.; ...

2017-05-25

Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.

Optimizing complex phenotypes through model-guided multiplex genome engineering

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

Kuznetsov, Gleb; Goodman, Daniel B.; Filsinger, Gabriel T.

Here, we present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA. By introducing targeted combinations of changes in multiplex we generate rich genotypic and phenotypic diversity and characterize clones using whole-genome sequencing and doubling time measurements. Regularized multivariate linear regression accurately quantifies individual allelic effects and overcomes bias from hitchhiking mutations and context-dependence of genome editing efficiency that would confound other strategies.

Molecular Mechanisms Modulating the Phenotype of Macrophages and Microglia

PubMed Central

Amici, Stephanie A.; Dong, Joycelyn; Guerau-de-Arellano, Mireia

2017-01-01

Macrophages and microglia play crucial roles during central nervous system development, homeostasis and acute events such as infection or injury. The diverse functions of tissue macrophages and microglia are mirrored by equally diverse phenotypes. A model of inflammatory/M1 versus a resolution phase/M2 macrophages has been widely used. However, the complexity of macrophage function can only be achieved by the existence of varied, plastic and tridimensional macrophage phenotypes. Understanding how tissue macrophages integrate environmental signals via molecular programs to define pathogen/injury inflammatory responses provides an opportunity to better understand the multilayered nature of macrophages, as well as target and modulate cellular programs to control excessive inflammation. This is particularly important in MS and other neuroinflammatory diseases, where chronic inflammatory macrophage and microglial responses may contribute to pathology. Here, we perform a comprehensive review of our current understanding of how molecular pathways modulate tissue macrophage phenotype, covering both classic pathways and the emerging role of microRNAs, receptor-tyrosine kinases and metabolism in macrophage phenotype. In addition, we discuss pathway parallels in microglia, novel markers helpful in the identification of peripheral macrophages versus microglia and markers linked to their phenotype. PMID:29176977

Endocrine regulation of predator-induced phenotypic plasticity.

PubMed

Dennis, Stuart R; LeBlanc, Gerald A; Beckerman, Andrew P

2014-11-01

Elucidating the developmental and genetic control of phenotypic plasticity remains a central agenda in evolutionary ecology. Here, we investigate the physiological regulation of phenotypic plasticity induced by another organism, specifically predator-induced phenotypic plasticity in the model ecological and evolutionary organism Daphnia pulex. Our research centres on using molecular tools to test among alternative mechanisms of developmental control tied to hormone titres, receptors and their timing in the life cycle. First, we synthesize detail about predator-induced defenses and the physiological regulation of arthropod somatic growth and morphology, leading to a clear prediction that morphological defences are regulated by juvenile hormone and life-history plasticity by ecdysone and juvenile hormone. We then show how a small network of genes can differentiate phenotype expression between the two primary developmental control pathways in arthropods: juvenoid and ecdysteroid hormone signalling. Then, by applying an experimental gradient of predation risk, we show dose-dependent gene expression linking predator-induced plasticity to the juvenoid hormone pathway. Our data support three conclusions: (1) the juvenoid signalling pathway regulates predator-induced phenotypic plasticity; (2) the hormone titre (ligand), rather than receptor, regulates predator-induced developmental plasticity; (3) evolution has favoured the harnessing of a major, highly conserved endocrine pathway in arthropod development to regulate the response to cues about changing environments (risk) from another organism (predator).

Linking metabolic network features to phenotypes using sparse group lasso.

PubMed

Samal, Satya Swarup; Radulescu, Ovidiu; Weber, Andreas; Fröhlich, Holger

2017-11-01

Integration of metabolic networks with '-omics' data has been a subject of recent research in order to better understand the behaviour of such networks with respect to differences between biological and clinical phenotypes. Under the conditions of steady state of the reaction network and the non-negativity of fluxes, metabolic networks can be algebraically decomposed into a set of sub-pathways often referred to as extreme currents (ECs). Our objective is to find the statistical association of such sub-pathways with given clinical outcomes, resulting in a particular instance of a self-contained gene set analysis method. In this direction, we propose a method based on sparse group lasso (SGL) to identify phenotype associated ECs based on gene expression data. SGL selects a sparse set of feature groups and also introduces sparsity within each group. Features in our model are clusters of ECs, and feature groups are defined based on correlations among these features. We apply our method to metabolic networks from KEGG database and study the association of network features to prostate cancer (where the outcome is tumor and normal, respectively) as well as glioblastoma multiforme (where the outcome is survival time). In addition, simulations show the superior performance of our method compared to global test, which is an existing self-contained gene set analysis method. R code (compatible with version 3.2.5) is available from http://www.abi.bit.uni-bonn.de/index.php?id=17. samal@combine.rwth-aachen.de or frohlich@bit.uni-bonn.de. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Genotypic and phenotypic characterization of the O-linked protein glycosylation system reveals high glycan diversity in paired meningococcal carriage isolates.

PubMed

Børud, Bente; Bårnes, Guro K; Brynildsrud, Ola Brønstad; Fritzsønn, Elisabeth; Caugant, Dominique A

2018-03-19

Species within the genus Neisseria display significant glycan diversity associated with the O -linked protein glycosylation ( pgl ) systems due to phase variation, polymorphic genes and gene content. The aim of this study was to examine in detail the pgl genotype and glycosylation phenotype in meningococcal isolates and the changes occurring during short-term asymptomatic carriage. Paired meningococcal isolates derived from 50 asymptomatic meningococcal carriers, taken about two months apart, were analyzed with whole genome sequencing. The O -linked protein glycosylation genes were characterized in detail using the Genome Comparator tool at the PubMLST.org database. Immunoblotting with glycan specific antibodies were used to investigate the protein glycosylation phenotype. All major pgl locus polymorphisms identified in N. meningitidis to date were present in our isolate collection, with the variable presence of pglG-pglH, both in combination with either pglB or pglB2. We identified significant changes and diversity in the pgl genotype and/or glycan phenotype in 96% of the paired isolates. There was also a high degree of glycan microheterogeneity, in which different variants of glycan structures were found at a given glycoprotein. The main mechanism responsible for the observed differences was phase variable expression of the involved glycosyltransferases and the O-acetyltransferase. To our knowledge, this is the first characterization of the pgl genotype and glycosylation phenotype in a larger strain collection. This study thus provides important insight into glycan diversity in N. meningitidis and phase variability changes that influence the expressed glycoform repertoire during meningococcal carriage. Importance Bacterial meningitis is a serious global health problem and one of the major causative organisms is Neisseria meningitidis , which is also a common commensal in the upper respiratory tract of healthy humans. In bacteria, numerous loci involved in

Variability in clinical phenotypes of PRPF8-linked autosomal dominant retinitis pigmentosa correlates with differential PRPF8/SNRNP200 interactions.

PubMed

Escher, Pascal; Passarin, Olga; Munier, Francis L; Tran, Viet H; Vaclavik, Veronika

2018-01-01

To expand the genotype/phenotype correlations in patients with autosomal dominant retinitis pigmentosa (adRP) harboring PRPF8 variants. Two patients, a father and his daughter, harboring a novel p.PRPF8-Glu2331* variant, underwent ophthalmic examination at 3-year-interval, including fundus photography, fundus autofluorescence, optical coherence tomography, and ISCEV standard full field ERGs. All reported disease-causing PRPF8 variants were collected and localized in the PRPF8 and PRPF8/SNRNP200 protein structures. The p.PRPF8-Glu2331* variant results in a truncated PRPF8 protein lacking the last five C-terminal amino acids and caused in the two patients a severe clinical phenotype, with the macula being affected from the second decade on. All but two adRP-linked variants are located in the last exon 43 encoding the C-terminal tail of the C-terminal PRPF8 Jab1 domain. The p.PRPF8-Ser2118Phe and -Asn2280Lys variants encoded by exons 39 and 42, respectively, are located at the basis of the C-terminal tail. Frame-shift mutations and nonconservative amino acid changes in PRPF8 typically cause severe clinical phenotypes. The conservative missense variant p.PRPF8-Arg2310Lys that is not altering the global charge of the C-terminal tail, and variants located at the basis of the C-terminal tail show milder clinical phenotypes, in accordance with functional data on PRPF8/SNRNP200 interactions in yeast.

Modeling the Transitions between Collective and Solitary Migration Phenotypes in Cancer Metastasis

PubMed Central

Huang, Bin; Jolly, Mohit Kumar; Lu, Mingyang; Tsarfaty, Ilan; Ben-Jacob, Eshel; Onuchic, Jose’ N

2015-01-01

Cellular plasticity during cancer metastasis is a major clinical challenge. Two key cellular plasticity mechanisms —Epithelial-to-Mesenchymal Transition (EMT) and Mesenchymal-to-Amoeboid Transition (MAT) – have been carefully investigated individually, yet a comprehensive understanding of their interconnections remains elusive. Previously, we have modeled the dynamics of the core regulatory circuits for both EMT (miR-200/ZEB/miR-34/SNAIL) and MAT (Rac1/RhoA). We now extend our previous work to study the coupling between these two core circuits by considering the two microRNAs (miR-200 and miR-34) as external signals to the core MAT circuit. We show that this coupled circuit enables four different stable steady states (phenotypes) that correspond to hybrid epithelial/mesenchymal (E/M), mesenchymal (M), amoeboid (A) and hybrid amoeboid/mesenchymal (A/M) phenotypes. Our model recapitulates the metastasis-suppressing role of the microRNAs even in the presence of EMT-inducing signals like Hepatocyte Growth Factor (HGF). It also enables mapping the microRNA levels to the transitions among various cell migration phenotypes. Finally, it offers a mechanistic understanding for the observed phenotypic transitions among different cell migration phenotypes, specifically the Collective-to-Amoeboid Transition (CAT). PMID:26627083

Modeling the human MTM1 p.R69C mutation in murine Mtm1 results in exon 4 skipping and a less severe myotubular myopathy phenotype

PubMed Central

Pierson, Christopher R.; Dulin-Smith, Ashley N.; Durban, Ashley N.; Marshall, Morgan L.; Marshall, Jordan T.; Snyder, Andrew D.; Naiyer, Nada; Gladman, Jordan T.; Chandler, Dawn S.; Lawlor, Michael W.; Buj-Bello, Anna; Dowling, James J.; Beggs, Alan H.

2012-01-01

X-linked myotubular myopathy (MTM) is a severe neuromuscular disease of infancy caused by mutations of MTM1, which encodes the phosphoinositide lipid phosphatase, myotubularin. The Mtm1 knockout (KO) mouse has a severe phenotype and its short lifespan (8 weeks) makes it a challenge to use as a model in the testing of certain preclinical therapeutics. Many MTM patients succumb early in life, but some have a more favorable prognosis. We used human genotype–phenotype correlation data to develop a myotubularin-deficient mouse model with a less severe phenotype than is seen in Mtm1 KO mice. We modeled the human c.205C>T point mutation in Mtm1 exon 4, which is predicted to introduce the p.R69C missense change in myotubularin. Hemizygous male Mtm1 p.R69C mice develop early muscle atrophy prior to the onset of weakness at 2 months. The median survival period is 66 weeks. Histopathology shows small myofibers with centrally placed nuclei. Myotubularin protein is undetectably low because the introduced c.205C>T base change induced exon 4 skipping in most mRNAs, leading to premature termination of myotubularin translation. Some full-length Mtm1 mRNA bearing the mutation is present, which provides enough myotubularin activity to account for the relatively mild phenotype, as Mtm1 KO and Mtm1 p.R69C mice have similar muscle phosphatidylinositol 3-phosphate levels. These data explain the basis for phenotypic variability among human patients with MTM1 p.R69C mutations and establish the Mtm1 p.R69C mouse as a valuable model for the disease, as its less severe phenotype will expand the scope of testable preclinical therapies. PMID:22068590

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

PubMed Central

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Zemojtel, Tomasz; Schriml, Lynn Marie; Kibbe, Warren Alden; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole L.; Mungall, Christopher J.; Lewis, Suzanna E.; Haendel, Melissa A.; Parkinson, Helen; Robinson, Peter N.

2015-01-01

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available. PMID:26119816

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

DOE PAGES

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; ...

2015-06-25

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000more » rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.« less

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

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

NASA Astrophysics Data System (ADS)

Lobo, Daniel; Lobikin, Maria; Levin, Michael

2017-01-01

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

Design and modelling of a link monitoring mechanism for the Common Data Link (CDL)

NASA Astrophysics Data System (ADS)

Eichelberger, John W., III

1994-09-01

The Common Data Link (CDL) is a full duplex, point-to-point microwave communications system used in imagery and signals intelligence collection systems. It provides a link between two remote Local Area Networks (LAN's) aboard collection and surface platforms. In a hostile environment, there is an overwhelming need to dynamically monitor the link and thus, limit the impact of jamming. This work describes steps taken to design, model, and evaluate a link monitoring system suitable for the CDL. The monitoring system is based on features and monitoring constructs of the Link Control Protocol (LCP) in the Point-to-Point Protocol (PPP) suite. The CDL model is based on a system of two remote Fiber Distributed Data Interface (FDDI) LAN's. In particular, the policies and mechanisms associated with monitoring are described in detail. An implementation of the required mechanisms using the OPNET network engineering tool is described. Performance data related to monitoring parameters is reported. Finally, integration of the FDDI-CDL model with the OPNET Internet model is described.

Mouse phenotyping.

PubMed

Fuchs, Helmut; Gailus-Durner, Valérie; Adler, Thure; Aguilar-Pimentel, Juan Antonio; Becker, Lore; Calzada-Wack, Julia; Da Silva-Buttkus, Patricia; Neff, Frauke; Götz, Alexander; Hans, Wolfgang; Hölter, Sabine M; Horsch, Marion; Kastenmüller, Gabi; Kemter, Elisabeth; Lengger, Christoph; Maier, Holger; Matloka, Mikolaj; Möller, Gabriele; Naton, Beatrix; Prehn, Cornelia; Puk, Oliver; Rácz, Ildikó; Rathkolb, Birgit; Römisch-Margl, Werner; Rozman, Jan; Wang-Sattler, Rui; Schrewe, Anja; Stöger, Claudia; Tost, Monica; Adamski, Jerzy; Aigner, Bernhard; Beckers, Johannes; Behrendt, Heidrun; Busch, Dirk H; Esposito, Irene; Graw, Jochen; Illig, Thomas; Ivandic, Boris; Klingenspor, Martin; Klopstock, Thomas; Kremmer, Elisabeth; Mempel, Martin; Neschen, Susanne; Ollert, Markus; Schulz, Holger; Suhre, Karsten; Wolf, Eckhard; Wurst, Wolfgang; Zimmer, Andreas; Hrabě de Angelis, Martin

2011-02-01

Model organisms like the mouse are important tools to learn more about gene function in man. Within the last 20 years many mutant mouse lines have been generated by different methods such as ENU mutagenesis, constitutive and conditional knock-out approaches, knock-down, introduction of human genes, and knock-in techniques, thus creating models which mimic human conditions. Due to pleiotropic effects, one gene may have different functions in different organ systems or time points during development. Therefore mutant mouse lines have to be phenotyped comprehensively in a highly standardized manner to enable the detection of phenotypes which might otherwise remain hidden. The German Mouse Clinic (GMC) has been established at the Helmholtz Zentrum München as a phenotyping platform with open access to the scientific community (www.mousclinic.de; [1]). The GMC is a member of the EUMODIC consortium which created the European standard workflow EMPReSSslim for the systemic phenotyping of mouse models (http://www.eumodic.org/[2]). Copyright © 2010 Elsevier Inc. All rights reserved.

The queen's gut refines with age: longevity phenotypes in a social insect model.

PubMed

Anderson, Kirk E; Ricigliano, Vincent A; Mott, Brendon M; Copeland, Duan C; Floyd, Amy S; Maes, Patrick

2018-06-18

In social insects, identical genotypes can show extreme lifespan variation providing a unique perspective on age-associated microbial succession. In honey bees, short- and long-lived host phenotypes are polarized by a suite of age-associated factors including hormones, nutrition, immune senescence, and oxidative stress. Similar to other model organisms, the aging gut microbiota of short-lived (worker) honey bees accrue Proteobacteria and are depleted of Lactobacillus and Bifidobacterium, consistent with a suite of host senescence markers. In contrast, long-lived (queen) honey bees maintain youthful cellular function with much lower expression of oxidative stress genes, suggesting a very different host environment for age-associated microbial succession. We sequenced the microbiota of 63 honey bee queens exploring two chronological ages and four alimentary tract niches. To control for genetic and environmental variation, we quantified carbonyl accumulation in queen fat body tissue as a proxy for biological aging. We compared our results to the age-specific microbial succession of worker guts. Accounting for queen source variation, two or more bacterial species per niche differed significantly by queen age. Biological aging in queens was correlated with microbiota composition highlighting the relationship of microbiota with oxidative stress. Queens and workers shared many major gut bacterial species, but differ markedly in community structure and age succession. In stark contrast to aging workers, carbonyl accumulation in queens was significantly associated with increased Lactobacillus and Bifidobacterium and depletion of various Proteobacteria. We present a model system linking changes in gut microbiota to diet and longevity, two of the most confounding variables in human microbiota research. The pattern of age-associated succession in the queen microbiota is largely the reverse of that demonstrated for workers. The guts of short-lived worker phenotypes are

AB067. X-linked adrenoleukodystrophy: Phenotype and genotype in Vietnamese patients

PubMed Central

Nguyen, Khanh Ngoc; Nguyen, Ha Thu; Can, Ngoc Thi Bich; Bui, Thao Phuong; Nobuyuki, Shimozawa; Vu, Huynh Anh; Do, Mai Thi Thanh; Vu, Dung Chi

2017-01-01

Background X-linked adrenoleukodystrophy (X-ALD) is caused by a defect in the gene ABCD1, which maps to Xq28 and codes for a peroxisomal membrane protein that is a member of the ATP-binding cassette transporter superfamily. This disease characterized by progressive neurologic dysfunction, occasionally associated with adrenal insufficiency. Objective is to identify phenotype and genotype in Vietnamese patients with X-ALD. Methods Genomic DNA from 20 Vietnamese patients from 18 unrelated families was extracted using standard procedures from the peripheral blood leukocytes. Mutation analysis of ABCD1 was performed using polymerase chain reaction (PCR) and DNA direct sequencing. Results We identified 17 different mutations of ABCD1 in 20 patients including missense mutations (2/17), deletion (4/17), frameshift mutation (1/17) and splice site mutation (1/17). Of which, six novel mutations including c.1202G>T (p.Arg401Trp); c.1208T>A (p.Met403Lys); IVS8+28-551bp del; c.1668G>C (p.Q556H); c.292_296delTCGGC (p.S98RfsX95); and the extent of deletion included between IVS1+505 and IVS2+1501, containing whole the exon 2 (4243bp), plus insertion of 79bp from BAP31 and 8bp from unknown origin in this deleted region were identified in six unrelated patients. Eleven reported mutations including c.796G>A (p.Gly266Arg); c.1628C>T (p.Pro543Leu); c.1553G>A (p.Arg518Gln); c.1552 C>T (p.Arg518Trp); c.854G>C (p.R285P); c.1825G>A (p.E609K); c.1415_1416delAG (p.Q472RfsX83) and c.46-53del insG, c.1553G>A (p.Arg518Gln), c.1946-1947insA (p.Asp649fsX733), c.1978C>T (p.Arg660Trp) were identified in 14 patients from 12 families. Most of patients (17/20) presented cerebral ALD type with/without adrenal insufficiency and only 3 patients presented Addison type. Conclusions Mutation analysis of ABCD1 gene helped confirmation of diagnosis of X-ALD, genetic counselling and prenatal diagnosis but could not be used to predict the specific phenotype of X-ALD.

Early phenotypical diagnoses in Trembler-J mice model.

PubMed

Rosso, Gonzalo; Cal, Karina; Canclini, Lucía; Damián, Juan Pablo; Ruiz, Paul; Rodríguez, Héctor; Sotelo, José Roberto; Vazquez, Cristina; Kun, Alejandra

2010-06-30

Pmp-22 mutant mice (Trembler-J: B6.D2-Pmp22/J), are used as a model to study Charcot-Marie-Tooth type 1A (CMT1A). The identification of individual genotypes is a routine in the management of the Tr(J) colony. The earliest phenotypic manifestation of the pmp-22 mutation is just about 20th postnatal days, when pups begin to tremble. In this study, a rapid and simple diagnostic method was developed by modifying the Tail Suspension Test (MTST) to determine the difference between the Tr(J) and the wild-type mice phenotype. The animal behavioral phenotypes generated during the test were consistent with the specific genotype of each animal. The MTST allowed us to infer the heterozygous genotype in early postnatal stages, at 11 days after birth. The motor impairment of Tr(J) mice was also analyzed by a Fixed Bar Test (FBT), which revealed the disease evolution according to age. The main advantages of MTST are its objectivity, simplicity, and from the viewpoint of animal welfare, it is a non-invasive technique that combined with his rapidity show its very well applicability for use from an early age in these mice. Copyright 2010 Elsevier B.V. All rights reserved.

PRELIM: Predictive Relevance Estimation from Linked Models

DTIC Science & Technology

2014-10-14

code ) 14-10-2014 Final Report 11-07-2014 to 14-10-2014 PRELIM: Predictive Relevance Estimation from Linked Models N00014-14-P-1185 10257H. Van Dyke...Parunak, Ph.D. Soar Technology, Inc. 1 Executive  Summary   PRELIM (Predictive Relevance Estimation from Linked Models) draws on semantic models...The central challenge in proactive decision support is to anticipate the decision and information needs of decision-makers, in the light of likely

Linking MedDRA®-coded Clinical Phenotypes to Biological Mechanisms by The Ontology of Adverse Events: A pilot study on Tyrosine Kinase Inhibitors (TKIs)

PubMed Central

Sarntivijai, Sirarat; Zhang, Shelley; Jagannathan, Desikan G.; Zaman, Shadia; Burkhart, Keith K.; Omenn, Gilbert S.; He, Yongqun; Athey, Brian D.; Abernethy, Darrell R.

2016-01-01

Introduction A translational bioinformatics challenge lies in connecting population and individual’s clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA®) is the default dictionary for Adverse Event (AE) reporting in the FDA Adverse Event Reporting System (FAERS). The Ontology of Adverse Events (OAE) represents AEs as pathological processes occurring after drug exposures. Objectives The aim is to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA® in FAERS data analysis. We investigated the AEs associated with Tyrosine Kinase Inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The selected 5 TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity. Results Statistical analysis of FAERS data identified 1,053 distinct MedDRA® terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA®. The data integration to provide insights into molecular mechanisms for drug-associated AEs is performed by including linkages in OAE for all related AE terms to MedDRA® and existing ontologies including Human Phenotype Ontology (HP), Uber Anatomy Ontology (UBERON), and Gene Ontology (GO). Sixteen AEs are shared by all 5 TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed ‘cardiac failure’ using the relations established in OAE with other ontologies, and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction. Conclusion By expanding existing OAE ontological design, our TKI use case demonstrates that the combination of OAE and Med

Phenotypic heterogeneity and mutational spectrum in a cohort of 45 Italian males subjects with X-linked ectodermal dysplasia.

PubMed

Guazzarotti, L; Tadini, G; Mancini, G E; Giglio, S; Willoughby, C E; Callea, M; Sani, I; Nannini, P; Mameli, C; Tenconi, A A; Mauri, S; Bottero, A; Caimi, A; Morelli, M; Zuccotti, G V

2015-04-01

Ectodermal dysplasias (EDs) are a group of genetic disorders characterized by the abnormal development of the ectodermal-derived structures. X-linked hypohidrotic ectodermal dysplasia, resulting from mutations in ED1 gene, is the most common form. The main purpose of this study was to characterize the phenotype spectrum in 45 males harboring ED1 mutations. The study showed that in addition to the involvement of the major ectodermal tissues, the majority of patients also have alterations of several minor ectodermal-derived structures. Characterizing the clinical spectrum resulting from ED1 gene mutations improves diagnosis and can direct clinical care. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Phenotypic switching in bacteria

NASA Astrophysics Data System (ADS)

Merrin, Jack

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

Rethinking the evolution of specialization: A model for the evolution of phenotypic heterogeneity.

PubMed

Rubin, Ilan N; Doebeli, Michael

2017-12-21

Phenotypic heterogeneity refers to genetically identical individuals that express different phenotypes, even when in the same environment. Traditionally, "bet-hedging" in fluctuating environments is offered as the explanation for the evolution of phenotypic heterogeneity. However, there are an increasing number of examples of microbial populations that display phenotypic heterogeneity in stable environments. Here we present an evolutionary model of phenotypic heterogeneity of microbial metabolism and a resultant theory for the evolution of phenotypic versus genetic specialization. We use two-dimensional adaptive dynamics to track the evolution of the population phenotype distribution of the expression of two metabolic processes with a concave trade-off. Rather than assume a Gaussian phenotype distribution, we use a Beta distribution that is capable of describing genotypes that manifest as individuals with two distinct phenotypes. Doing so, we find that environmental variation is not a necessary condition for the evolution of phenotypic heterogeneity, which can evolve as a form of specialization in a stable environment. There are two competing pressures driving the evolution of specialization: directional selection toward the evolution of phenotypic heterogeneity and disruptive selection toward genetically determined specialists. Because of the lack of a singular point in the two-dimensional adaptive dynamics and the fact that directional selection is a first order process, while disruptive selection is of second order, the evolution of phenotypic heterogeneity dominates and often precludes speciation. We find that branching, and therefore genetic specialization, occurs mainly under two conditions: the presence of a cost to maintaining a high phenotypic variance or when the effect of mutations is large. A cost to high phenotypic variance dampens the strength of selection toward phenotypic heterogeneity and, when sufficiently large, introduces a singular point into

Identification of Multiple QTLs Linked to Neuropathology in the Engrailed-1 Heterozygous Mouse Model of Parkinson’s Disease

PubMed Central

Kurowska, Zuzanna; Jewett, Michael; Brattås, Per Ludvik; Jimenez-Ferrer, Itzia; Kenéz, Xuyian; Björklund, Tomas; Nordström, Ulrika; Brundin, Patrik; Swanberg, Maria

2016-01-01

Motor symptoms in Parkinson’s disease are attributed to degeneration of midbrain dopaminergic neurons (DNs). Heterozygosity for Engrailed-1 (En1), one of the key factors for programming and maintenance of DNs, results in a parkinsonian phenotype featuring progressive degeneration of DNs in substantia nigra pars compacta (SNpc), decreased striatal dopamine levels and swellings of nigro-striatal axons in the SwissOF1-En1+/− mouse strain. In contrast, C57Bl/6-En1+/− mice do not display this neurodegenerative phenotype, suggesting that susceptibility to En1 heterozygosity is genetically regulated. Our goal was to identify quantitative trait loci (QTLs) that regulate the susceptibility to PD-like neurodegenerative changes in response to loss of one En1 allele. We intercrossed SwissOF1-En1+/− and C57Bl/6 mice to obtain F2 mice with mixed genomes and analyzed number of DNs in SNpc and striatal axonal swellings in 120 F2-En1+/− 17 week-old male mice. Linkage analyses revealed 8 QTLs linked to number of DNs (p = 2.4e-09, variance explained = 74%), 7 QTLs linked to load of axonal swellings (p = 1.7e-12, variance explained = 80%) and 8 QTLs linked to size of axonal swellings (p = 7.0e-11, variance explained = 74%). These loci should be of prime interest for studies of susceptibility to Parkinson’s disease-like damage in rodent disease models and considered in clinical association studies in PD. PMID:27550741

Shuttle/TDRSS modelling and link simulation study

NASA Technical Reports Server (NTRS)

Braun, W. R.; Mckenzie, T. M.; Biederman, L.; Lindsey, W. C.

1979-01-01

A Shuttle/TDRSS S-band and Ku-band link simulation package called LinCsim was developed for the evaluation of link performance for specific Shuttle signal designs. The link models were described in detail and the transmitter distortion parameters or user constraints were carefully defined. The overall link degradation (excluding hardware degradations) relative to an ideal BPSK channel were given for various sets of user constraint values. The performance sensitivity to each individual user constraint was then illustrated. The effect of excessive Spacelab clock jitter on the return link BER performance was also investigated as was the problem of subcarrier recovery for the K-band Shuttle return link signal.

Phenotypic expression of the HLA-linked iron-loading gene in the Afrikaner population of the western Cape.

PubMed

Meyer, T E; Baynes, R D; Bothwell, T H; Jenkins, T; Ballot, D; Jooste, P L; Green, A; Du Toit, E; Jacobs, P

1988-03-05

A previous study conducted on a group of Afrikaans-speaking subjects in the south-western Cape indicated a high frequency (0.115) of the HLA-linked iron-loading gene which causes idiopathic haemochromatosis. The results of phenotypic and genotypic studies on the first degree relatives of identified homozygotes and heterozygotes are now reported. There was considerable heterogeneity of phenotypic expression in the group of heterozygotes, with overlap between the homozygous and heterozygous subjects. The heterozygous relatives of heterozygous index cases, who had been identified on the basis of a serum ferritin concentration greater than 400 micrograms/l, appeared to have more frequent and more marked abnormalities of iron measurements than the heterozygote relatives of homozygous index cases (serum ferritin value greater than 400 micrograms/l, percentage transferrin saturation greater than 60). This suggests that the screening test was identifying a group of more significantly affected heterozygotes, with biochemical abnormalities that overlapped with the identified homozygotes. The index cases were followed up over a period of 5 years and during this time the 7 subjects diagnosed as heterozygotes showed a progressive increase in serum ferritin concentrations, which suggests some iron accumulation. Individual pedigrees included instances of gene recombination within the major histocompatibility complex, and of probable false-positive genotype assignment. The overall results confirm a high frequency of the gene in this particular community.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Extended model of restricted beam for FSO links

NASA Astrophysics Data System (ADS)

Poliak, Juraj; Wilfert, Otakar

2012-10-01

Modern wireless optical communication systems in many aspects overcome wire or radio communications. Their advantages are license-free operation and broad bandwidth that they offer. The medium in free-space optical (FSO) links is the atmosphere. Operation of outdoor FSO links struggles with many atmospheric phenomena that deteriorate phase and amplitude of the transmitted optical beam. This beam originates in the transmitter and is affected by its individual parts, especially by the lens socket and the transmitter aperture, where attenuation and diffraction effects take place. Both of these phenomena unfavourable influence the beam and cause degradation of link availability, or its total malfunction. Therefore, both of these phenomena should be modelled and simulated, so that one can judge the link function prior to the realization of the system. Not only the link availability and reliability are concerned, but also economic aspects. In addition, the transmitted beam is not, generally speaking, circularly symmetrical, what makes the link simulation more difficult. In a comprehensive model, it is necessary to take into account the ellipticity of the beam that is restricted by circularly symmetrical aperture where then the attenuation and diffraction occur. General model is too computationally extensive; therefore simplification of the calculations by means of analytical and numerical approaches will be discussed. Presented model is not only simulated using computer, but also experimentally proven. One can then deduce the ability of the model to describe the reality and to estimate how far can one go with approximations, i.e. limitations of the model are discussed.

High-fertility phenotypes: two outbred mouse models exhibit substantially different molecular and physiological strategies warranting improved fertility.

PubMed

Langhammer, Martina; Michaelis, Marten; Hoeflich, Andreas; Sobczak, Alexander; Schoen, Jennifer; Weitzel, Joachim M

2014-01-01

Animal models are valuable tools in fertility research. Worldwide, there are more than 400 transgenic or knockout mouse models available showing a reproductive phenotype; almost all of them exhibit an infertile or at least subfertile phenotype. By contrast, animal models revealing an improved fertility phenotype are barely described. This article summarizes data on two outbred mouse models exhibiting a 'high-fertility' phenotype. These mouse lines were generated via selection over a time period of more than 40 years and 161 generations. During this selection period, the number of offspring per litter and the total birth weight of the entire litter nearly doubled. Concomitantly with the increased fertility phenotype, several endocrine parameters (e.g. serum testosterone concentrations in male animals), physiological parameters (e.g. body weight, accelerated puberty, and life expectancy), and behavioral parameters (e.g. behavior in an open field and endurance fitness on a treadmill) were altered. We demonstrate that the two independently bred high-fertility mouse lines warranted their improved fertility phenotype using different molecular and physiological strategies. The fertility lines display female- as well as male-specific characteristics. These genetically heterogeneous mouse models provide new insights into molecular and cellular mechanisms that enhance fertility. In view of decreasing fertility in men, these models will therefore be a precious information source for human reproductive medicine. Translated abstract A German translation of abstract is freely available at http://www.reproduction-online.org/content/147/4/427/suppl/DC1.

The roles of connective tissue growth factor and integrin-linked kinase in high glucose-induced phenotypic alterations of podocytes.

PubMed

Dai, Hou-Yong; Zheng, Min; Lv, Lin-Li; Tang, Ri-Ning; Ma, Kun-Ling; Liu, Dan; Wu, Min; Liu, Bi-Cheng

2012-01-01

Emerging evidence has suggested that podocytes undergo epithelial-mesenchymal transition (EMT) in diabetic nephropathy (DN). Connective tissue growth factor (CTGF) and integrin-linked kinase (ILK) are involved in the progression of DN. However, the underlying mechanisms of EMT are not well understood. The study aimed to investigate the roles of CTGF and ILK in high glucose-induced phenotypic alterations of podocytes and determine whether ILK signaling is downstream of CTGF. The epithelial marker of nephrin and the mesenchymal marker of desmin were investigated by real-time RT-PCR and Western blotting. The results demonstrated that podocytes displayed a spreading, arborized morphology in normal glucose, whereas they had a cobblestone morphology in high glucose conditions, accompanied by decreased nephrin expression and increased desmin expression, suggesting podocytes underwent EMT. In response to high glucose, CTGF and ILK expression in podocytes were increased in a dose- and time-dependent manner, whereas the increase did not occur in the osmotic control. Furthermore, the inhibition of CTGF with anti-CTGF antibody prevented the phenotypic transition, as demonstrated by the preservation of epithelial morphology, the suppression of high glucose-induced desmin overexpression and the restoration of nephrin. Of note, the upregulation of ILK induced by high glucose was partially blocked by the inhibition of CTGF. In summary, these findings suggested that CTGF and ILK were involved in high glucose-induced phenotypic alterations of podocytes. ILK acted as a downstream kinase of CTGF and high glucose-induced ILK expression might occur through CTGF-dependent and -independent pathways. Copyright © 2011 Wiley Periodicals, Inc.

Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

ERIC Educational Resources Information Center

Reinagel, Adam; Speth, Elena Bray

2016-01-01

In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students' understanding of 1) the origin of variation in a population…

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.

Structure of the Autism Symptom Phenotype: A Proposed Multidimensional Model

ERIC Educational Resources Information Center

Georgiades, Stelios; Szatmari, Peter; Zwaigenbaum, Lonnie; Duku, Eric; Bryson, Susan; Roberts, Wendy; Goldberg, Jeremy; Mahoney, William

2007-01-01

Background: The main objective of this study was to develop a comprehensive, empirical model that would allow the reorganization of the structure of the pervasive developmental disorder symptom phenotype through factor analysis into more homogeneous dimensions. Method: The sample consisted of 209 children with pervasive developmental disorder…

Phenotypic and biomarker evaluation of zebrafish larvae as an alternative model to predict mammalian hepatotoxicity.

PubMed

Verstraelen, Sandra; Peers, Bernard; Maho, Walid; Hollanders, Karen; Remy, Sylvie; Berckmans, Pascale; Covaci, Adrian; Witters, Hilda

2016-09-01

Zebrafish phenotypic assays have shown promise to assess human hepatotoxicity, though scoring of liver morphology remains subjective and difficult to standardize. Liver toxicity in zebrafish larvae at 5 days was assessed using gene expression as the biomarker approach, complementary to phenotypic analysis and analytical data on compound uptake. This approach aimed to contribute to improved hepatotoxicity prediction, with the goal of identifying biomarker(s) as a step towards the development of transgenic models for prioritization. Morphological effects of hepatotoxic compounds (acetaminophen, amiodarone, coumarin, methapyrilene and myclobutanil) and saccharin as the negative control were assessed after exposure in zebrafish larvae. The hepatotoxic compounds induced the expected zebrafish liver degeneration or changes in size, whereas saccharin did not have any phenotypic adverse effect. Analytical methods based on liquid chromatography-mass spectrometry were optimized to measure stability of selected compounds in exposure medium and internal concentration in larvae. All compounds were stable, except amiodarone for which precipitation was observed. There was a wide variation between the levels of compound in the zebrafish larvae with a higher uptake of amiodarone, methapyrilene and myclobutanil. Detection of hepatocyte markers (CP, CYP3A65, GC and TF) was accomplished by in situ hybridization of larvae to coumarin and myclobutanil and confirmed by real-time reverse transcription-quantitative polymerase chain reaction. Experiments showed decreased expression of all markers. Next, other liver-specific biomarkers (i.e. FABP10a and NR1H4) and apoptosis (i.e. CASP-3 A and TP53) or cytochrome P450-related (CYP2K19) and oxidoreductase activity-related (ZGC163022) genes, were screened. Links between basic mechanisms of liver injury and results of biomarker responses are described. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Linking Goal-Oriented Requirements and Model-Driven Development

NASA Astrophysics Data System (ADS)

Pastor, Oscar; Giachetti, Giovanni

In the context of Goal-Oriented Requirement Engineering (GORE) there are interesting modeling approaches for the analysis of complex scenarios that are oriented to obtain and represent the relevant requirements for the development of software products. However, the way to use these GORE models in an automated Model-Driven Development (MDD) process is not clear, and, in general terms, the translation of these models into the final software products is still manually performed. Therefore, in this chapter, we show an approach to automatically link GORE models and MDD processes, which has been elaborated by considering the experience obtained from linking the i * framework with an industrially applied MDD approach. The linking approach proposed is formulated by means of a generic process that is based on current modeling standards and technologies in order to facilitate its application for different MDD and GORE approaches. Special attention is paid to how this process generates appropriate model transformation mechanisms to automatically obtain MDD conceptual models from GORE models, and how it can be used to specify validation mechanisms to assure the correct model transformations.

Behavioral Phenotyping and Pathological Indicators of Parkinson's Disease in C. elegans Models

PubMed Central

Maulik, Malabika; Mitra, Swarup; Bult-Ito, Abel; Taylor, Barbara E.; Vayndorf, Elena M.

2017-01-01

Parkinson's disease (PD) is a neurodegenerative disorder with symptoms that progressively worsen with age. Pathologically, PD is characterized by the aggregation of α-synuclein in cells of the substantia nigra in the brain and loss of dopaminergic neurons. This pathology is associated with impaired movement and reduced cognitive function. The etiology of PD can be attributed to a combination of environmental and genetic factors. A popular animal model, the nematode roundworm Caenorhabditis elegans, has been frequently used to study the role of genetic and environmental factors in the molecular pathology and behavioral phenotypes associated with PD. The current review summarizes cellular markers and behavioral phenotypes in transgenic and toxin-induced PD models of C. elegans. PMID:28659967

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

PubMed

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia

PubMed Central

Gao, Kun; Swarup, Vivek; Versano, Revital; Dong, Hongmei; Jordan, Maria C

2017-01-01

Friedreich's ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model of Fxn deficiency that enabled us to control the onset and progression of disease phenotypes by the modulation of Fxn levels. Systemic knockdown of Fxn in adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease. PMID:29257745

Modeling and executing electronic health records driven phenotyping algorithms using the NQF Quality Data Model and JBoss® Drools Engine.

PubMed

Li, Dingcheng; Endle, Cory M; Murthy, Sahana; Stancl, Craig; Suesse, Dale; Sottara, Davide; Huff, Stanley M; Chute, Christopher G; Pathak, Jyotishman

2012-01-01

With increasing adoption of electronic health records (EHRs), the need for formal representations for EHR-driven phenotyping algorithms has been recognized for some time. The recently proposed Quality Data Model from the National Quality Forum (NQF) provides an information model and a grammar that is intended to represent data collected during routine clinical care in EHRs as well as the basic logic required to represent the algorithmic criteria for phenotype definitions. The QDM is further aligned with Meaningful Use standards to ensure that the clinical data and algorithmic criteria are represented in a consistent, unambiguous and reproducible manner. However, phenotype definitions represented in QDM, while structured, cannot be executed readily on existing EHRs. Rather, human interpretation, and subsequent implementation is a required step for this process. To address this need, the current study investigates open-source JBoss® Drools rules engine for automatic translation of QDM criteria into rules for execution over EHR data. In particular, using Apache Foundation's Unstructured Information Management Architecture (UIMA) platform, we developed a translator tool for converting QDM defined phenotyping algorithm criteria into executable Drools rules scripts, and demonstrated their execution on real patient data from Mayo Clinic to identify cases for Coronary Artery Disease and Diabetes. To the best of our knowledge, this is the first study illustrating a framework and an approach for executing phenotyping criteria modeled in QDM using the Drools business rules management system.

Modeling and Executing Electronic Health Records Driven Phenotyping Algorithms using the NQF Quality Data Model and JBoss® Drools Engine

PubMed Central

Li, Dingcheng; Endle, Cory M; Murthy, Sahana; Stancl, Craig; Suesse, Dale; Sottara, Davide; Huff, Stanley M.; Chute, Christopher G.; Pathak, Jyotishman

2012-01-01

With increasing adoption of electronic health records (EHRs), the need for formal representations for EHR-driven phenotyping algorithms has been recognized for some time. The recently proposed Quality Data Model from the National Quality Forum (NQF) provides an information model and a grammar that is intended to represent data collected during routine clinical care in EHRs as well as the basic logic required to represent the algorithmic criteria for phenotype definitions. The QDM is further aligned with Meaningful Use standards to ensure that the clinical data and algorithmic criteria are represented in a consistent, unambiguous and reproducible manner. However, phenotype definitions represented in QDM, while structured, cannot be executed readily on existing EHRs. Rather, human interpretation, and subsequent implementation is a required step for this process. To address this need, the current study investigates open-source JBoss® Drools rules engine for automatic translation of QDM criteria into rules for execution over EHR data. In particular, using Apache Foundation’s Unstructured Information Management Architecture (UIMA) platform, we developed a translator tool for converting QDM defined phenotyping algorithm criteria into executable Drools rules scripts, and demonstrated their execution on real patient data from Mayo Clinic to identify cases for Coronary Artery Disease and Diabetes. To the best of our knowledge, this is the first study illustrating a framework and an approach for executing phenotyping criteria modeled in QDM using the Drools business rules management system. PMID:23304325

Congenital heart disease linked to maternal autoimmunity against cardiac myosin.

PubMed

Cole, Charles R; Yutzey, Katherine E; Brar, Anoop K; Goessling, Lisa S; Van Vickle-Chavez, Sarah J; Cunningham, Madeleine W; Eghtesady, Pirooz

2014-05-01

Structural congenital heart disease (CHD) has not previously been linked to autoimmunity. In our study, we developed an autoimmune model of structural CHD that resembles hypoplastic left heart syndrome (HLHS), a life-threatening CHD primarily affecting the left ventricle. Because cardiac myosin (CM) is a dominant autoantigen in autoimmune heart disease, we hypothesized that immunization with CM might lead to transplacental passage of maternal autoantibodies and a prenatal HLHS phenotype in exposed fetuses. Elevated anti-CM autoantibodies in maternal and fetal sera, as well as IgG reactivity in fetal myocardium, were correlated with structural CHD that included diminished left ventricular cavity dimensions in the affected progeny. Further, fetuses that developed a marked HLHS phenotype had elevated serum titers of anti-β-adrenergic receptor Abs, as well as increased protein kinase A activity, suggesting a potential mechanism for the observed pathological changes. Our maternal-fetal model presents a new concept linking autoimmunity against CM and cardiomyocyte proliferation with cardinal features of HLHS. To our knowledge, this report shows the first evidence in support of a novel immune-mediated mechanism for pathogenesis of structural CHD that may have implications in its future diagnosis and treatment.

A novel mutation in the X-linked cyclin-dependent kinase-like 5 (CDKL5) gene associated with a severe Rett phenotype.

PubMed

Sprovieri, T; Conforti, F L; Fiumara, A; Mazzei, R; Ungaro, C; Citrigno, L; Muglia, M; Arena, A; Quattrone, A

2009-02-15

Mutations in the X-linked cyclin-dependent kinase-like 5 (CDKL5) gene have recently been reported in patients with severe neurodevelopmental disorder characterized by early-onset seizures, infantile spasms, severe psychomotor impairment and very recently, in patients with Rett syndrome (RTT)-like phenotype. Although the involvement of CDKL5 in specific biological pathways and its neurodevelopmental role have not been completely elucidated, the CDKL5 appears to be physiologically related to the MECP2 gene. Here we report on the clinical and CDKL5 molecular investigation in a very unusual RTT case, with severe, early-neurological involvement in which we have shown in a previous report, a novel P388S MECP2 mutation [Conforti et al. (2003); Am J Med Genet A 117A: 184-187]. The patient has had severe psychomotor delay since the first month of life and infantile spasms since age 5 months. Moreover, at age 5 years the patient suddenly presented with renal failure. The severe pattern of symptoms in our patient, similar to a CDKL5 phenotype, prompted us to perform an analysis of the CDKL5, which revealed a novel missense mutation never previously described. The X-inactivation assay was non-informative. In conclusion, this report reinforces the observation that the CDKL5 phenotype overlaps with RTT and that CDKL5 analysis is recommended in patients with a seizure disorder commencing during the first months of life.

Generating Phenotypical Erroneous Human Behavior to Evaluate Human-automation Interaction Using Model Checking

PubMed Central

Bolton, Matthew L.; Bass, Ellen J.; Siminiceanu, Radu I.

2012-01-01

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human-automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel’s zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human-automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development. PMID:23105914

Modeling lineage and phenotypic diversification in the New World monkey (Platyrrhini, Primates) radiation.

PubMed

Aristide, Leandro; Rosenberger, Alfred L; Tejedor, Marcelo F; Perez, S Ivan

2015-01-01

Adaptive radiations that have taken place in the distant past can now be more thoroughly studied with the availability of large molecular phylogenies and comparative data drawn from extant and fossil species. Platyrrhines are a good example of a major mammalian evolutionary radiation confined to a single continent, involving a relatively large temporal scale and documented by a relatively small but informative fossil record. Here, we present comparative evidence using data on extant and fossil species to explore alternative evolutionary models in an effort to better understand the process of platyrrhine lineage and phenotypic diversification. Specifically, we compare the likelihood of null models of lineage and phenotypic diversification versus various models of adaptive evolution. Moreover, we statistically explore the main ecological dimension behind the platyrrhine diversification. Contrary to the previous proposals, our study did not find evidence of a rapid lineage accumulation in the phylogenetic tree of extant platyrrhine species. However, the fossil-based diversity curve seems to show a slowdown in diversification rates toward present times. This also suggests an early high rate of extinction among lineages within crown Platyrrhini. Finally, our analyses support the hypothesis that the platyrrhine phenotypic diversification appears to be characterized by an early and profound differentiation in body size related to a multidimensional niche model, followed by little subsequent change (i.e., stasis). Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism Phenotypes

DTIC Science & Technology

2014-09-01

AD_________________ Award Number: TITLE: Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...AUG 2013-7 Aug 2014 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Preclinical Testing of Novel Oxytocin Receptor Activators in Models of Autism ...a genetic mouse model of autism -like phenotypes, the Grin1 knockdown mouse. The Grin1 gene encodes the NR1 subunit of the NMDA receptor . In the

Stem cell derived phenotypic human neuromuscular junction model for dose response evaluation of therapeutics.

PubMed

Santhanam, Navaneetha; Kumanchik, Lee; Guo, Xiufang; Sommerhage, Frank; Cai, Yunqing; Jackson, Max; Martin, Candace; Saad, George; McAleer, Christopher W; Wang, Ying; Lavado, Andrea; Long, Christopher J; Hickman, James J

2018-06-01

There are currently no functional neuromuscular junction (hNMJ) systems composed of human cells that could be used for drug evaluations or toxicity testing in vitro. These systems are needed to evaluate NMJs for diseases such as amyotrophic lateral sclerosis, spinal muscular atrophy or other neurodegenerative diseases or injury states. There are certainly no model systems, animal or human, that allows for isolated treatment of motoneurons or muscle capable of generating dose response curves to evaluate pharmacological activity of these highly specialized functional units. A system was developed in which human myotubes and motoneurons derived from stem cells were cultured in a serum-free medium in a BioMEMS construct. The system is composed of two chambers linked by microtunnels to enable axonal outgrowth to the muscle chamber that allows separate stimulation of each component and physiological NMJ function and MN stimulated tetanus. The muscle's contractions, induced by motoneuron activation or direct electrical stimulation, were monitored by image subtraction video recording for both frequency and amplitude. Bungarotoxin, BOTOX ® and curare dose response curves were generated to demonstrate pharmacological relevance of the phenotypic screening device. This quantifiable functional hNMJ system establishes a platform for generating patient-specific NMJ models by including patient-derived iPSCs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of linking a soil-water-balance model with a groundwater-flow model

USGS Publications Warehouse

Stanton, Jennifer S.; Ryter, Derek W.; Peterson, Steven M.

2013-01-01

A previously published regional groundwater-flow model in north-central Nebraska was sequentially linked with the recently developed soil-water-balance (SWB) model to analyze effects to groundwater-flow model parameters and calibration results. The linked models provided a more detailed spatial and temporal distribution of simulated recharge based on hydrologic processes, improvement of simulated groundwater-level changes and base flows at specific sites in agricultural areas, and a physically based assessment of the relative magnitude of recharge for grassland, nonirrigated cropland, and irrigated cropland areas. Root-mean-squared (RMS) differences between the simulated and estimated or measured target values for the previously published model and linked models were relatively similar and did not improve for all types of calibration targets. However, without any adjustment to the SWB-generated recharge, the RMS difference between simulated and estimated base-flow target values for the groundwater-flow model was slightly smaller than for the previously published model, possibly indicating that the volume of recharge simulated by the SWB code was closer to actual hydrogeologic conditions than the previously published model provided. Groundwater-level and base-flow hydrographs showed that temporal patterns of simulated groundwater levels and base flows were more accurate for the linked models than for the previously published model at several sites, particularly in agricultural areas.

Disease modeling and phenotypic drug screening for diabetic cardiomyopathy using human induced pluripotent stem cells.

PubMed

Drawnel, Faye M; Boccardo, Stefano; Prummer, Michael; Delobel, Frédéric; Graff, Alexandra; Weber, Michael; Gérard, Régine; Badi, Laura; Kam-Thong, Tony; Bu, Lei; Jiang, Xin; Hoflack, Jean-Christophe; Kiialainen, Anna; Jeworutzki, Elena; Aoyama, Natsuyo; Carlson, Coby; Burcin, Mark; Gromo, Gianni; Boehringer, Markus; Stahlberg, Henning; Hall, Benjamin J; Magnone, Maria Chiara; Kolaja, Kyle; Chien, Kenneth R; Bailly, Jacques; Iacone, Roberto

2014-11-06

Diabetic cardiomyopathy is a complication of type 2 diabetes, with known contributions of lifestyle and genetics. We develop environmentally and genetically driven in vitro models of the condition using human-induced-pluripotent-stem-cell-derived cardiomyocytes. First, we mimic diabetic clinical chemistry to induce a phenotypic surrogate of diabetic cardiomyopathy, observing structural and functional disarray. Next, we consider genetic effects by deriving cardiomyocytes from two diabetic patients with variable disease progression. The cardiomyopathic phenotype is recapitulated in the patient-specific cells basally, with a severity dependent on their original clinical status. These models are incorporated into successive levels of a screening platform, identifying drugs that preserve cardiomyocyte phenotype in vitro during diabetic stress. In this work, we present a patient-specific induced pluripotent stem cell (iPSC) model of a complex metabolic condition, showing the power of this technique for discovery and testing of therapeutic strategies for a disease with ever-increasing clinical significance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Genetic and Environmental Models of Circadian Disruption Link SRC-2 Function to Hepatic Pathology

PubMed Central

Fleet, Tiffany; Stashi, Erin; Zhu, Bokai; Rajapakshe, Kimal; Marcelo, Kathrina L.; Kettner, Nicole M.; Gorman, Blythe K.; Coarfa, Cristian; Fu, Loning; O’Malley, Bert W.; York, Brian

2017-01-01

Circadian rhythmicity is a fundamental process that synchronizes behavioral cues with metabolic homeostasis. Disruption of daily cycles due to jet lag or shift work results in severe physiological consequences including advanced aging, metabolic syndrome, and even cancer. Our understanding of the molecular clock, which is regulated by intricate positive feedforward and negative feedback loops, has expanded to include an important metabolic transcriptional coregulator, Steroid Receptor Coactivator-2 (SRC-2), that regulates both the central clock of the suprachiasmatic nucleus (SCN) and peripheral clocks including the liver. We hypothesized that an environmental uncoupling of the light-dark phases, termed chronic circadian disruption (CCD), would lead to pathology similar to the genetic circadian disruption observed with loss of SRC-2. We found that CCD and ablation of SRC-2 in mice led to a common comorbidity of metabolic syndrome also found in humans with circadian disruption, non-alcoholic fatty liver disease (NAFLD). The combination of SRC-2−/− and CCD results in a more robust phenotype that correlates with human non-alcoholic steatohepatitis (NASH) and hepatocellular carcinoma (HCC) gene signatures. Either CCD or SRC-2 ablation produces an advanced aging phenotype leading to increased mortality consistent with other circadian mutant mouse models. Collectively, our studies demonstrate that SRC-2 provides an essential link between the behavioral activities influenced by light cues and the metabolic homeostasis maintained by the liver. PMID:27432117

Temporal abstraction-based clinical phenotyping with Eureka!

PubMed

Post, Andrew R; Kurc, Tahsin; Willard, Richie; Rathod, Himanshu; Mansour, Michel; Pai, Akshatha Kalsanka; Torian, William M; Agravat, Sanjay; Sturm, Suzanne; Saltz, Joel H

2013-01-01

Temporal abstraction, a method for specifying and detecting temporal patterns in clinical databases, is very expressive and performs well, but it is difficult for clinical investigators and data analysts to understand. Such patterns are critical in phenotyping patients using their medical records in research and quality improvement. We have previously developed the Analytic Information Warehouse (AIW), which computes such phenotypes using temporal abstraction but requires software engineers to use. We have extended the AIW's web user interface, Eureka! Clinical Analytics, to support specifying phenotypes using an alternative model that we developed with clinical stakeholders. The software converts phenotypes from this model to that of temporal abstraction prior to data processing. The model can represent all phenotypes in a quality improvement project and a growing set of phenotypes in a multi-site research study. Phenotyping that is accessible to investigators and IT personnel may enable its broader adoption.

Stochastic modeling and experimental analysis of phenotypic switching and survival of cancer cells under stress

NASA Astrophysics Data System (ADS)

Zamani Dahaj, Seyed Alireza; Kumar, Niraj; Sundaram, Bala; Celli, Jonathan; Kulkarni, Rahul

The phenotypic heterogeneity of cancer cells is critical to their survival under stress. A significant contribution to heterogeneity of cancer calls derives from the epithelial-mesenchymal transition (EMT), a conserved cellular program that is crucial for embryonic development. Several studies have investigated the role of EMT in growth of early stage tumors into invasive malignancies. Also, EMT has been closely associated with the acquisition of chemoresistance properties in cancer cells. Motivated by these studies, we analyze multi-phenotype stochastic models of the evolution of cancers cell populations under stress. We derive analytical results for time-dependent probability distributions that provide insights into the competing rates underlying phenotypic switching (e.g. during EMT) and the corresponding survival of cancer cells. Experimentally, we evaluate these model-based predictions by imaging human pancreatic cancer cell lines grown with and without cytotoxic agents and measure growth kinetics, survival, morphological changes and (terminal evaluation of) biomarkers with associated epithelial and mesenchymal phenotypes. The results derived suggest approaches for distinguishing between adaptation and selection scenarios for survival in the presence of external stresses.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of

Model invariance across genders of the Broad Autism Phenotype Questionnaire.

PubMed

Broderick, Neill; Wade, Jordan L; Meyer, J Patrick; Hull, Michael; Reeve, Ronald E

2015-10-01

ASD is one of the most heritable neuropsychiatric disorders, though comprehensive genetic liability remains elusive. To facilitate genetic research, researchers employ the concept of the broad autism phenotype (BAP), a milder presentation of traits in undiagnosed relatives. Research suggests that the BAP Questionnaire (BAPQ) demonstrates psychometric properties superior to other self-report measures. To examine evidence regarding validity of the BAPQ, the current study used confirmatory factor analysis to test the assumption of model invariance across genders. Results of the current study upheld model invariance at each level of parameter constraint; however, model fit indices suggested limited goodness-of-fit between the proposed model and the sample. Exploratory analyses investigated alternate factor structure models but ultimately supported the proposed three-factor structure model.

Link performance model for filter bank based multicarrier systems

NASA Astrophysics Data System (ADS)

Petrov, Dmitry; Oborina, Alexandra; Giupponi, Lorenza; Stitz, Tobias Hidalgo

2014-12-01

This paper presents a complete link level abstraction model for link quality estimation on the system level of filter bank multicarrier (FBMC)-based networks. The application of mean mutual information per coded bit (MMIB) approach is validated for the FBMC systems. The considered quality measure of the resource element for the FBMC transmission is the received signal-to-noise-plus-distortion ratio (SNDR). Simulation results of the proposed link abstraction model show that the proposed approach is capable of estimating the block error rate (BLER) accurately, even when the signal is propagated through the channels with deep and frequent fades, as it is the case for the 3GPP Hilly Terrain (3GPP-HT) and Enhanced Typical Urban (ETU) models. The FBMC-related results of link level simulations are compared with cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) analogs. Simulation results are also validated through the comparison to reference publicly available results. Finally, the steps of link level abstraction algorithm for FBMC are formulated and its application for system level simulation of a professional mobile radio (PMR) network is discussed.

Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource

PubMed Central

Ananiadou, Sophia

2016-01-01

Biomedical literature articles and narrative content from Electronic Health Records (EHRs) both constitute rich sources of disease-phenotype information. Phenotype concepts may be mentioned in text in multiple ways, using phrases with a variety of structures. This variability stems partly from the different backgrounds of the authors, but also from the different writing styles typically used in each text type. Since EHR narrative reports and literature articles contain different but complementary types of valuable information, combining details from each text type can help to uncover new disease-phenotype associations. However, the alternative ways in which the same concept may be mentioned in each source constitutes a barrier to the automatic integration of information. Accordingly, identification of the unique concepts represented by phrases in text can help to bridge the gap between text types. We describe our development of a novel method, PhenoNorm, which integrates a number of different similarity measures to allow automatic linking of phenotype concept mentions to known concepts in the UMLS Metathesaurus, a biomedical terminological resource. PhenoNorm was developed using the PhenoCHF corpus—a collection of literature articles and narratives in EHRs, annotated for phenotypic information relating to congestive heart failure (CHF). We evaluate the performance of PhenoNorm in linking CHF-related phenotype mentions to Metathesaurus concepts, using a newly enriched version of PhenoCHF, in which each phenotype mention has an expert-verified link to a concept in the UMLS Metathesaurus. We show that PhenoNorm outperforms a number of alternative methods applied to the same task. Furthermore, we demonstrate PhenoNorm’s wider utility, by evaluating its ability to link mentions of various other types of medically-related information, occurring in texts covering wider subject areas, to concepts in different terminological resources. We show that PhenoNorm can

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

PubMed

Fox, Jeremy W

2012-01-01

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

Phenotypic integration emerges from aposematism and scale in poison frogs

PubMed Central

Santos, Juan C.; Cannatella, David C.

2011-01-01

Complex phenotypes can be modeled as networks of component traits connected by genetic, developmental, or functional interactions. Aposematism, which has evolved multiple times in poison frogs (Dendrobatidae), links a warning signal to a chemical defense against predators. Other traits are involved in this complex phenotype. Most aposematic poison frogs are ant specialists, from which they sequester defensive alkaloids. We found that aposematic species have greater aerobic capacity, also related to diet specialization. To characterize the aposematic trait network more fully, we analyzed phylogenetic correlations among its hypothesized components: conspicuousness, chemical defense, diet specialization, body mass, active and resting metabolic rates, and aerobic scope. Conspicuous coloration was correlated with all components except resting metabolism. Structural equation modeling on the basis of trait correlations recovered “aposematism” as one of two latent variables in an integrated phenotypic network, the other being scaling with body mass and physiology (“scale”). Chemical defense and diet specialization were uniquely tied to aposematism whereas conspicuousness was related to scale. The phylogenetic distribution of the aposematic syndrome suggests two scenarios for its evolution: (i) chemical defense and conspicuousness preceded greater aerobic capacity, which supports the increased resource-gathering abilities required of ant–mite diet specialization; and (ii) assuming that prey are patchy, diet specialization and greater aerobic capacity evolved in tandem, and both traits subsequently facilitated the evolution of aposematism. PMID:21444790

A VGI data integration framework based on linked data model

NASA Astrophysics Data System (ADS)

Wan, Lin; Ren, Rongrong

2015-12-01

This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

Manipulators with flexible links: A simple model and experiments

NASA Technical Reports Server (NTRS)

Shimoyama, Isao; Oppenheim, Irving J.

1989-01-01

A simple dynamic model proposed for flexible links is briefly reviewed and experimental control results are presented for different flexible systems. A simple dynamic model is useful for rapid prototyping of manipulators and their control systems, for possible application to manipulator design decisions, and for real time computation as might be applied in model based or feedforward control. Such a model is proposed, with the further advantage that clear physical arguments and explanations can be associated with its simplifying features and with its resulting analytical properties. The model is mathematically equivalent to Rayleigh's method. Taking the example of planar bending, the approach originates in its choice of two amplitude variables, typically chosen as the link end rotations referenced to the chord (or the tangent) motion of the link. This particular choice is key in establishing the advantageous features of the model, and it was used to support the series of experiments reported.

Imaging techniques for visualizing and phenotyping congenital heart defects in murine models.

PubMed

Liu, Xiaoqin; Tobita, Kimimasa; Francis, Richard J B; Lo, Cecilia W

2013-06-01

Mouse model is ideal for investigating the genetic and developmental etiology of congenital heart disease. However, cardiovascular phenotyping for the precise diagnosis of structural heart defects in mice remain challenging. With rapid advances in imaging techniques, there are now high throughput phenotyping tools available for the diagnosis of structural heart defects. In this review, we discuss the efficacy of four different imaging modalities for congenital heart disease diagnosis in fetal/neonatal mice, including noninvasive fetal echocardiography, micro-computed tomography (micro-CT), micro-magnetic resonance imaging (micro-MRI), and episcopic fluorescence image capture (EFIC) histopathology. The experience we have gained in the use of these imaging modalities in a large-scale mouse mutagenesis screen have validated their efficacy for congenital heart defect diagnosis in the tiny hearts of fetal and newborn mice. These cutting edge phenotyping tools will be invaluable for furthering our understanding of the developmental etiology of congenital heart disease. Copyright © 2013 Wiley Periodicals, Inc.

Assessing spatial and temporal variability of phytoplankton communities' composition in the Iroise Sea ecosystem (Brittany, France): A 3D modeling approach. Part 2: Linking summer mesoscale distribution of phenotypic diversity to hydrodynamism

NASA Astrophysics Data System (ADS)

Cadier, Mathilde; Sourisseau, Marc; Gorgues, Thomas; Edwards, Christopher A.; Memery, Laurent

2017-05-01

Tidal front ecosystems are especially dynamic environments usually characterized by high phytoplankton biomass and high primary production. However, the description of functional microbial diversity occurring in these regions remains only partially documented. In this article, we use a numerical model, simulating a large number of phytoplankton phenotypes to explore the three-dimensional spatial patterns of phytoplankton abundance and diversity in the Iroise Sea (western Brittany). Our results suggest that, in boreal summer, a seasonally marked tidal front shapes the phytoplankton species richness. A diversity maximum is found in the surface mixed layer located slightly west of the tidal front (i.e., not strictly co-localized with high biomass concentrations) which separates tidally mixed from stratified waters. Differences in phenotypic composition between sub-regions with distinct hydrodynamic regimes (defined by vertical mixing, nutrients gradients and light penetration) are discussed. Local growth and/or physical transport of phytoplankton phenotypes are shown to explain our simulated diversity distribution. We find that a large fraction (64%) of phenotypes present during the considered period of September are ubiquitous, found in the frontal area and on both sides of the front (i.e., over the full simulated domain). The frontal area does not exhibit significant differences between its community composition and that of either the well-mixed region or an offshore Deep Chlorophyll Maximum (DCM). Only three phenotypes (out of 77) specifically grow locally and are found at substantial concentration only in the surface diversity maximum. Thus, this diversity maximum is composed of a combination of ubiquitous phenotypes with specific picoplankton deriving from offshore, stratified waters (including specific phenotypes from both the surface and the DCM) and imported through physical transport, completed by a few local phenotypes. These results are discussed in light

Coevolutionary dynamics of phenotypic diversity and contingent cooperation

PubMed Central

Wang, Long

2017-01-01

Phenotypic diversity is considered beneficial to the evolution of contingent cooperation, in which cooperators channel their help preferentially towards others of similar phenotypes. However, it remains largely unclear how phenotypic variation arises in the first place and thus leads to the construction of phenotypic complexity. Here we propose a mathematical model to study the coevolutionary dynamics of phenotypic diversity and contingent cooperation. Unlike previous models, our model does not assume any prescribed level of phenotypic diversity, but rather lets it be an evolvable trait. Each individual expresses one phenotype at a time and only the phenotypes expressed are visible to others. Moreover, individuals can differ in their potential of phenotypic variation, which is characterized by the number of distinct phenotypes they can randomly switch to. Each individual incurs a cost proportional to the number of potentially expressible phenotypes so as to retain phenotypic variation and expression. Our results show that phenotypic diversity coevolves with contingent cooperation under a wide range of conditions and that there exists an optimal level of phenotypic diversity best promoting contingent cooperation. It pays for contingent cooperators to elevate their potential of phenotypic variation, thereby increasing their opportunities of establishing cooperation via novel phenotypes, as these new phenotypes serve as secret tags that are difficult for defector to discover and chase after. We also find that evolved high levels of phenotypic diversity can occasionally collapse due to the invasion of defector mutants, suggesting that cooperation and phenotypic diversity can mutually reinforce each other. Thus, our results provide new insights into better understanding the coevolution of cooperation and phenotypic diversity. PMID:28141806

[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.

Molecular Model for HNBR with Tunable Cross-Link Density.

PubMed

Molinari, N; Khawaja, M; Sutton, A P; Mostofi, A A

2016-12-15

We introduce a chemically inspired, all-atom model of hydrogenated nitrile butadiene rubber (HNBR) and assess its performance by computing the mass density and glass-transition temperature as a function of cross-link density in the structure. Our HNBR structures are created by a procedure that mimics the real process used to produce HNBR, that is, saturation of the carbon-carbon double bonds in NBR, either by hydrogenation or by cross-linking. The atomic interactions are described by the all-atom "Optimized Potentials for Liquid Simulations" (OPLS-AA). In this paper, first, we assess the use of OPLS-AA in our models, especially using NBR bulk properties, and second, we evaluate the validity of the proposed model for HNBR by investigating mass density and glass transition as a function of the tunable cross-link density. Experimental densities are reproduced within 3% for both elastomers, and qualitatively correct trends in the glass-transition temperature as a function of monomer composition and cross-link density are obtained.

Age-dependent phenotypic characteristics of a triple transgenic mouse model of Alzheimer disease.

PubMed

Pietropaolo, Susanna; Feldon, Joram; Yee, Benjamin K

2008-08-01

The triple-transgenic mouse line (3 x Tg-AD) harboring PS1M146V, APPSwe, and taup301L transgenes represents the only transgenic model for Alzheimer's disease (AD) to date capturing both beta-amyloid and tau neuropathology. The present study provides an extensive behavioral characterization of the 3 x Tg-AD mouse line, evaluating the emergence of noncognitive and cognitive AD-like symptoms at two ages corresponding to the early (6-7 months) and advanced (12-13 months) stages of AD-pathology. Enhanced responsiveness to aversive stimulation was detected in mutant mice at both ages: the 3 x Tg-AD genotype enhanced acoustic startle response and facilitated performance in the cued-version of the water maze. These noncognitive phenotypes were accompanied by hyperactivity and reduced locomotor habituation in the open field at the older age. Signs of cognitive aberrations were also detected at both ages, but they were limited to associative learning. The present study suggests that this popular transgenic mouse model of AD has clear phenotypes beyond the cognitive domain, and their potential relationship to the cognitive phenotypes should be further explored.

Federated Tensor Factorization for Computational Phenotyping

PubMed Central

Kim, Yejin; Sun, Jimeng; Yu, Hwanjo; Jiang, Xiaoqian

2017-01-01

Tensor factorization models offer an effective approach to convert massive electronic health records into meaningful clinical concepts (phenotypes) for data analysis. These models need a large amount of diverse samples to avoid population bias. An open challenge is how to derive phenotypes jointly across multiple hospitals, in which direct patient-level data sharing is not possible (e.g., due to institutional policies). In this paper, we developed a novel solution to enable federated tensor factorization for computational phenotyping without sharing patient-level data. We developed secure data harmonization and federated computation procedures based on alternating direction method of multipliers (ADMM). Using this method, the multiple hospitals iteratively update tensors and transfer secure summarized information to a central server, and the server aggregates the information to generate phenotypes. We demonstrated with real medical datasets that our method resembles the centralized training model (based on combined datasets) in terms of accuracy and phenotypes discovery while respecting privacy. PMID:29071165

Intermittent fasting alleviates the neuropathic phenotype in a mouse model of Charcot-Marie-Tooth disease

PubMed Central

Madorsky, Irina; Opalach, Katherine; Waber, Amanda; Verrier, Jonathan D.; Solmo, Chelsea; Foster, Thomas; Dunn, William A; Notterpek, Lucia

2009-01-01

Charcot-Marie-Tooth type 1A (CMT1A) neuropathies linked to the misexpression of peripheral myelin protein 22 (PMP22) are progressive demyelinating disorders of the peripheral nervous system. In this study we asked whether dietary restriction by intermittent fasting (IF) could alleviate the neuropathic phenotype in the Trembler J (TrJ) mouse model of CMT1A. Our results show that neuropathic mice kept on a five month long IF regimen had improved locomotor performance compared to ad libitum (AL) fed littermates. The functional benefits of this dietary intervention are associated with an increased expression of myelin proteins combined with a thicker myelin sheath, less redundant basal lamina, and a reduction in aberrant Schwann cell proliferation. These morphological improvements are accompanied by a decrease in PMP22 protein aggregates, and enhanced expression of cytosolic chaperones and constituents of the autophagy-lysosomal pathway. These results indicate that dietary restriction is beneficial for peripheral nerve function in TrJ neuropathic mice, as it promotes the maintenance of locomotor performance. PMID:19320048

Four novel connexin 32 mutations in X-linked Charcot-Marie-Tooth disease. Phenotypic variability and central nervous system involvement.

PubMed

Karadima, Georgia; Koutsis, Georgios; Raftopoulou, Maria; Floroskufi, Paraskewi; Karletidi, Karolina-Maria; Panas, Marios

2014-06-15

Charcot-Marie-Tooth (CMT) disease, the most common hereditary neuropathy, is clinically and genetically heterogeneous. X-linked CMT (CMTX) is usually caused by mutations in the gap junction protein b 1 gene (GJB1) coding for connexin 32 (Cx32). The clinical manifestations of CMTX are characterized by significant variability, with some patients exhibiting central nervous system (CNS) involvement. We report four novel mutations in GJB1, c.191G>A (p.Cys64Tyr), c.508G>T (p.Val170Phe), c.778A>G (p.Lys260Glu) and c.300C>G (p.His100Gln) identified in four unrelated Greek families. These mutations were characterized by variable phenotypic expression, including a family with the Roussy-Lévy syndrome, and three of them were associated with mild clinical CNS manifestations. Copyright © 2014. Published by Elsevier B.V.

The fractography-modeling link in cleavage fracture

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

Thompson, A.W.

1997-12-31

Cleavage fracture has historically been modelled, out of necessity, in rather idealized terms. In real materials, however, there are a number of difficulties in linking such models with metallographic and fractographic observations. Some of the most vivid examples occur for {alpha}{sub 2} titanium aluminide alloys, in which, when the microstructure contains primary {alpha}{sub 2} particles, the primary particles crack first. When basketweave or Widmanstaetten structures of {alpha}{sub 2} laths comprise the microstructure, it appears that individual laths crack first. And in colony structures, cracking occurs first across the {alpha}{sub 2} lath colonies. Both detailed fractographic observations, and also a statisticalmore » model for brittle fracture by failure of weakest links, have been developed. The extent to which this can be interpreted in classical cleavage terms will be discussed.« less

Epigenome-associated phenotypic acclimatization to ocean acidification in a reef-building coral.

PubMed

Liew, Yi Jin; Zoccola, Didier; Li, Yong; Tambutté, Eric; Venn, Alexander A; Michell, Craig T; Cui, Guoxin; Deutekom, Eva S; Kaandorp, Jaap A; Voolstra, Christian R; Forêt, Sylvain; Allemand, Denis; Tambutté, Sylvie; Aranda, Manuel

2018-06-01

There are increasing concerns that the current rate of climate change might outpace the ability of reef-building corals to adapt to future conditions. Work on model systems has shown that environmentally induced alterations in DNA methylation can lead to phenotypic acclimatization. While DNA methylation has been reported in corals and is thought to associate with phenotypic plasticity, potential mechanisms linked to changes in whole-genome methylation have yet to be elucidated. We show that DNA methylation significantly reduces spurious transcription in the coral Stylophora pistillata . Furthermore, we find that DNA methylation also reduces transcriptional noise by fine-tuning the expression of highly expressed genes. Analysis of DNA methylation patterns of corals subjected to long-term pH stress showed widespread changes in pathways regulating cell cycle and body size. Correspondingly, we found significant increases in cell and polyp sizes that resulted in more porous skeletons, supporting the hypothesis that linear extension rates are maintained under conditions of reduced calcification. These findings suggest an epigenetic component in phenotypic acclimatization that provides corals with an additional mechanism to cope with environmental change.

Model updating in flexible-link multibody systems

NASA Astrophysics Data System (ADS)

Belotti, R.; Caneva, G.; Palomba, I.; Richiedei, D.; Trevisani, A.

2016-09-01

The dynamic response of flexible-link multibody systems (FLMSs) can be predicted through nonlinear models based on finite elements, to describe the coupling between rigid- body and elastic behaviour. Their accuracy should be as high as possible to synthesize controllers and observers. Model updating based on experimental measurements is hence necessary. By taking advantage of the experimental modal analysis, this work proposes a model updating procedure for FLMSs and applies it experimentally to a planar robot. Indeed, several peculiarities of the model of FLMS should be carefully tackled. On the one hand, nonlinear models of a FLMS should be linearized about static equilibrium configurations. On the other, the experimental mode shapes should be corrected to be consistent with the elastic displacements represented in the model, which are defined with respect to a fictitious moving reference (the equivalent rigid link system). Then, since rotational degrees of freedom are also represented in the model, interpolation of the experimental data should be performed to match the model displacement vector. Model updating has been finally cast as an optimization problem in the presence of bounds on the feasible values, by also adopting methods to improve the numerical conditioning and to compute meaningful updated inertial and elastic parameters.

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.

CHALLENGES IN PHENOTYPE DEFINITION IN THE WHOLE-GENOME ERA: MULTIVARIATE MODELS OF MEMORY AND INTELLIGENCE

PubMed Central

SABB, F. W.; BURGGREN, A. C.; HIGIER, R. G.; FOX, J.; HE, J.; PARKER, D. S.; POLDRACK, R. A.; CHU, W.; CANNON, T. D.; FREIMER, N. B.; BILDER, R. M.

2009-01-01

Refining phenotypes for the study of neuropsychiatric disorders is of paramount importance in neuroscience. Poor phenotype definition provides the greatest obstacle for making progress in disorders like schizophrenia, bipolar disorder, Attention Deficit/Hyperactivity Disorder (ADHD), and autism. Using freely available informatics tools developed by the Consortium for Neuropsychiatric Phenomics (CNP), we provide a framework for defining and refining latent constructs used in neuroscience research and then apply this strategy to review known genetic contributions to memory and intelligence in healthy individuals. This approach can help us begin to build multi-level phenotype models that express the interactions between constructs necessary to understand complex neuropsychiatric diseases. PMID:19450667

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.

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis

PubMed Central

Acharya, Biswa R.; Roy Choudhury, Swarup; Estelle, Aiden B.; Vijayakumar, Anitha; Zhu, Chuanmei; Hovis, Laryssa; Pandey, Sona

2017-01-01

Setaria viridis (green foxtail) is an important model plant for the study of C4 photosynthesis in panicoid grasses, and is fast emerging as a system of choice for the study of plant development, domestication, abiotic stress responses and evolution. Basic research findings in Setaria are expected to advance research not only in this species and its close relative S. italica (foxtail millet), but also in other panicoid grasses, many of which are important food or bioenergy crops. Here we report on the standardization of multiple growth and development assays for S. viridis under controlled conditions, and in response to several phytohormones and abiotic stresses. We optimized these assays at three different stages of the plant’s life: seed germination and post-germination growth using agar plate-based assays, early seedling growth and development using germination pouch-based assays, and adult plant growth and development under environmentally controlled growth chambers and greenhouses. These assays will be useful for the community to perform large scale phenotyping analyses, mutant screens, comparative physiological analysis, and functional characterization of novel genes of Setaria or other related agricultural crops. Precise description of various growth conditions, effective treatment conditions and description of the resultant phenotypes will help expand the use of S. viridis as an effective model system. PMID:29312412

Optimization of Phenotyping Assays for the Model Monocot Setaria viridis.

PubMed

Acharya, Biswa R; Roy Choudhury, Swarup; Estelle, Aiden B; Vijayakumar, Anitha; Zhu, Chuanmei; Hovis, Laryssa; Pandey, Sona

2017-01-01

Setaria viridis (green foxtail) is an important model plant for the study of C4 photosynthesis in panicoid grasses, and is fast emerging as a system of choice for the study of plant development, domestication, abiotic stress responses and evolution. Basic research findings in Setaria are expected to advance research not only in this species and its close relative S. italica (foxtail millet), but also in other panicoid grasses, many of which are important food or bioenergy crops. Here we report on the standardization of multiple growth and development assays for S. viridis under controlled conditions, and in response to several phytohormones and abiotic stresses. We optimized these assays at three different stages of the plant's life: seed germination and post-germination growth using agar plate-based assays, early seedling growth and development using germination pouch-based assays, and adult plant growth and development under environmentally controlled growth chambers and greenhouses. These assays will be useful for the community to perform large scale phenotyping analyses, mutant screens, comparative physiological analysis, and functional characterization of novel genes of Setaria or other related agricultural crops. Precise description of various growth conditions, effective treatment conditions and description of the resultant phenotypes will help expand the use of S. viridis as an effective model system.

Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency

PubMed Central

Bone, William P.; Washington, Nicole L.; Buske, Orion J.; Adams, David R.; Davis, Joie; Draper, David; Flynn, Elise D.; Girdea, Marta; Godfrey, Rena; Golas, Gretchen; Groden, Catherine; Jacobsen, Julius; Köhler, Sebastian; Lee, Elizabeth M. J.; Links, Amanda E.; Markello, Thomas C.; Mungall, Christopher J.; Nehrebecky, Michele; Robinson, Peter N.; Sincan, Murat; Soldatos, Ariane G.; Tifft, Cynthia J.; Toro, Camilo; Trang, Heather; Valkanas, Elise; Vasilevsky, Nicole; Wahl, Colleen; Wolfe, Lynne A.; Boerkoel, Cornelius F.; Brudno, Michael; Haendel, Melissa A.; Gahl, William A.; Smedley, Damian

2016-01-01

Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Genet Med 18 6, 608–617. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors. Genet Med 18 6, 608–617. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Genet Med 18 6, 608–617. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders. Genet Med 18 6, 608–617. PMID:26562225

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.

Tumour model with intrusive morphology, progressive phenotypical heterogeneity and memory

NASA Astrophysics Data System (ADS)

Atangana, Abdon; Alqahtani, Rubayyi T.

2018-03-01

The model of a tumour, taking into account invasive morphology, progressive phenotypical heterogeneity and also memory, is developed and analyzed in this paper. Three models are investigated: first we consider the model describing the proliferation concentrates in proximity of tumour boundaries, in which the oxygen levels are pronounced. Then we consider the model where the oxygen around the tumour is considered to be unchanged by the vascular system. Finally, we investigate the model of growth of tumours using the concept of non-local operators with the Mittag-Leffler kernel. We provide the numerical solution using the extended 3/8 Simpson method for the new trends of fractional integration for the proliferation concentrates in the proximity of the tumour model. Then we provide the exact solutions of the Gompertz model with three different fractional differentiations involving power law, exponential decay law and the Mittag-Leffler law.

Pathway perturbations in signaling networks: Linking genotype to phenotype.

PubMed

Li, Yongsheng; McGrail, Daniel J; Latysheva, Natasha; Yi, Song; Babu, M Madan; Sahni, Nidhi

2018-05-10

Genes and gene products interact with each other to form signal transduction networks in the cell. The interactome networks are under intricate regulation in physiological conditions, but could go awry upon genome instability caused by genetic mutations. In the past decade with next-generation sequencing technologies, an increasing number of genomic mutations have been identified in a variety of disease patients and healthy individuals. As functional and systematic studies on these mutations leap forward, they begin to reveal insights into cellular homeostasis and disease mechanisms. In this review, we discuss recent advances in the field of network biology and signaling pathway perturbations upon genomic changes, and highlight the success of various omics datasets in unraveling genotype-to-phenotype relationships. Copyright © 2018 Elsevier Ltd. All rights reserved.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Modeling water quality, temperature, and flow in Link River, south-central Oregon

USGS Publications Warehouse

Sullivan, Annett B.; Rounds, Stewart A.

2016-09-09

The 2.1-km (1.3-mi) Link River connects Upper Klamath Lake to the Klamath River in south-central Oregon. A CE-QUAL-W2 flow and water-quality model of Link River was developed to provide a connection between an existing model of the upper Klamath River and any existing or future models of Upper Klamath Lake. Water-quality sampling at six locations in Link River was done during 2013–15 to support model development and to provide a better understanding of instream biogeochemical processes. The short reach and high velocities in Link River resulted in fast travel times and limited water-quality transformations, except for dissolved oxygen. Reaeration through the reach, especially at the falls in Link River, was particularly important in moderating dissolved oxygen concentrations that at times entered the reach at Link River Dam with marked supersaturation or subsaturation. This reaeration resulted in concentrations closer to saturation downstream at the mouth of Link River.

Complex phenotype linked to a mutation in exon 11 of the lamin A/C gene: Hypertrophic cardiomyopathy, atrioventricular block, severe dyslipidemia and diabetes.

PubMed

Francisco, Ana Rita G; Santos Gonçalves, Inês; Veiga, Fátima; Mendes Pedro, Mónica; Pinto, Fausto J; Brito, Dulce

2017-09-01

The lamin A/C (LMNA) gene encodes lamins A and C, which have an important role in nuclear cohesion and chromatin organization. Mutations in this gene usually lead to the so-called laminopathies, the primary cardiac manifestations of which are dilated cardiomyopathy and intracardiac conduction defects. Some mutations, associated with lipodystrophy but not cardiomyopathy, have been linked to metabolic abnormalities such as diabetes and severe dyslipidemia. Herein we describe a new phenotype associated with a mutation in exon 11 of the LMNA gene: hypertrophic cardiomyopathy, atrioventricular block, severe dyslipidemia and diabetes. A 64-year-old woman with hypertrophic cardiomyopathy and a point mutation in exon 11 of the LMNA gene (c.1718C>T, Ser573Leu) presented with severe symptomatic ventricular hypertrophy and left ventricular outflow tract obstruction. She underwent septal alcohol ablation, followed by Morrow myectomy. The patient was also diagnosed with severe dyslipidemia, diabetes and obesity, and fulfilled diagnostic criteria for metabolic syndrome. No other characteristics of LMNA mutation-related phenotypes were identified. The development of type III atrioventricular block with no apparent cause, and mildly depressed systolic function, prompted referral for cardiac resynchronization therapy. In conclusion, the association between LMNA mutations and different phenotypes is complex and not fully understood, and can present with a broad spectrum of severity. Copyright © 2017 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.

The immature dentate gyrus represents a shared phenotype of mouse models of epilepsy and psychiatric disease

PubMed Central

Shin, Rick; Kobayashi, Katsunori; Hagihara, Hideo; Kogan, Jeffrey H; Miyake, Shinichi; Tajinda, Katsunori; Walton, Noah M; Gross, Adam K; Heusner, Carrie L; Chen, Qian; Tamura, Kouichi; Miyakawa, Tsuyoshi; Matsumoto, Mitsuyuki

2013-01-01

Objectives There is accumulating evidence to suggest psychiatric disorders, such as bipolar disorder and schizophrenia, share common etiologies, pathophysiologies, genetics, and drug responses with many of the epilepsies. Here, we explored overlaps in cellular/molecular, electrophysiological, and behavioral phenotypes between putative mouse models of bipolar disorder/schizophrenia and epilepsy. We tested the hypothesis that an immature dentate gyrus (iDG), whose association with psychosis in patients has recently been reported, represents a common phenotype of both diseases. Methods Behaviors of calcium/calmodulin-dependent protein kinase II alpha (α-CaMKII) heterozygous knock-out (KO) mice, which are a representative bipolar disorder/schizophrenia model displaying iDG, and pilocarpine-treated mice, which are a representative epilepsy model, were tested followed by quantitative polymerase chain reaction (qPCR)/immunohistochemistry for mRNA/protein expression associated with an iDG phenotype. In vitro electrophysiology of dentate gyrus granule cells (DG GCs) was examined in pilocarpine-treated epileptic mice. Results The two disease models demonstrated similar behavioral deficits, such as hyperactivity, poor working memory performance, and social withdrawal. Significant reductions in mRNA expression and immunoreactivity of the mature neuronal marker calbindin and concomitant increases in mRNA expression and immunoreactivity of the immature neuronal marker calretinin represent iDG signatures that are present in both mice models. Electrophysiologically, we have confirmed that DG GCs from pilocarpine-treated mice represent an immature state. A significant decrease in hippocampal α-CaMKII protein levels was also found in both models. Conclusions Our data have shown iDG signatures from mouse models of both bipolar disorder/schizophrenia and epilepsy. The evidence suggests that the iDG may, in part, be responsible for the abnormal behavioral phenotype, and that the

The immature dentate gyrus represents a shared phenotype of mouse models of epilepsy and psychiatric disease.

PubMed

Shin, Rick; Kobayashi, Katsunori; Hagihara, Hideo; Kogan, Jeffrey H; Miyake, Shinichi; Tajinda, Katsunori; Walton, Noah M; Gross, Adam K; Heusner, Carrie L; Chen, Qian; Tamura, Kouichi; Miyakawa, Tsuyoshi; Matsumoto, Mitsuyuki

2013-06-01

There is accumulating evidence to suggest psychiatric disorders, such as bipolar disorder and schizophrenia, share common etiologies, pathophysiologies, genetics, and drug responses with many of the epilepsies. Here, we explored overlaps in cellular/molecular, electrophysiological, and behavioral phenotypes between putative mouse models of bipolar disorder/schizophrenia and epilepsy. We tested the hypothesis that an immature dentate gyrus (iDG), whose association with psychosis in patients has recently been reported, represents a common phenotype of both diseases. Behaviors of calcium/calmodulin-dependent protein kinase II alpha (α-CaMKII) heterozygous knock-out (KO) mice, which are a representative bipolar disorder/schizophrenia model displaying iDG, and pilocarpine-treated mice, which are a representative epilepsy model, were tested followed by quantitative polymerase chain reaction (qPCR)/immunohistochemistry for mRNA/protein expression associated with an iDG phenotype. In vitro electrophysiology of dentate gyrus granule cells (DG GCs) was examined in pilocarpine-treated epileptic mice. The two disease models demonstrated similar behavioral deficits, such as hyperactivity, poor working memory performance, and social withdrawal. Significant reductions in mRNA expression and immunoreactivity of the mature neuronal marker calbindin and concomitant increases in mRNA expression and immunoreactivity of the immature neuronal marker calretinin represent iDG signatures that are present in both mice models. Electrophysiologically, we have confirmed that DG GCs from pilocarpine-treated mice represent an immature state. A significant decrease in hippocampal α-CaMKII protein levels was also found in both models. Our data have shown iDG signatures from mouse models of both bipolar disorder/schizophrenia and epilepsy. The evidence suggests that the iDG may, in part, be responsible for the abnormal behavioral phenotype, and that the underlying pathophysiologies in epilepsy

Combined effects of aging and inflammation on renin-angiotensin system mediate mitochondrial dysfunction and phenotypic changes in cardiomyopathies.

PubMed

Burks, Tyesha N; Marx, Ruth; Powell, Laura; Rucker, Jasma; Bedja, Djahida; Heacock, Elisa; Smith, Barbara J; Foster, D Brian; Kass, David; O'Rourke, Brian; Walston, Jeremy D; Abadir, Peter M

2015-05-20

Although the effects of aging and inflammation on the health of the cardiac muscle are well documented, the combined effects of aging and chronic inflammation on cardiac muscle are largely unknown. The renin-angiotensin system (RAS) has been linked independently to both aging and inflammation, but is understudied in the context of their collective effect. Thus, we investigated localized cardiac angiotensin II type I and type II receptors (AT(1)R, AT(2)R), downstream effectors, and phenotypic outcomes using mouse models of the combination of aging and inflammation and compared it to a model of aging and a model of inflammation. We show molecular distinction in the combined effect of aging and inflammation as compared to each independently. The combination maintained an increased AT(1)R:AT(2)R and expression of Nox2 and exhibited the lowest activity of antioxidants. Despite signaling pathway differences, the combined effect shared phenotypic similarities with aging including oxidative damage, fibrosis, and hypertrophy. These phenotypic similarities have dubbed inflammatory conditions as premature aging, but they are, in fact, molecularly distinct. Moreover, treatment with an AT(1)R blocker, losartan, selectively reversed the signaling changes and ameliorated adverse phenotypic effects in the combination of aging and inflammation as well as each independently.

Combined effects of aging and inflammation on renin-angiotensin system mediate mitochondrial dysfunction and phenotypic changes in cardiomyopathies

PubMed Central

Burks, Tyesha N.; Marx, Ruth; Powell, Laura; Rucker, Jasma; Bedja, Djahida; Heacock, Elisa; Smith, Barbara J.; Foster, D. Brian; Kass, David; O'Rourke, Brian; Walston, Jeremy D.; Abadir, Peter M.

2015-01-01

Although the effects of aging and inflammation on the health of the cardiac muscle are well documented, the combined effects of aging and chronic inflammation on cardiac muscle are largely unknown. The renin-angiotensin system (RAS) has been linked independently to both aging and inflammation, but is understudied in the context of their collective effect. Thus, we investigated localized cardiac angiotensin II type I and type II receptors (AT1R, AT2R), downstream effectors, and phenotypic outcomes using mouse models of the combination of aging and inflammation and compared it to a model of aging and a model of inflammation. We show molecular distinction in the combined effect of aging and inflammation as compared to each independently. The combination maintained an increased AT1R:AT2R and expression of Nox2 and exhibited the lowest activity of antioxidants. Despite signaling pathway differences, the combined effect shared phenotypic similarities with aging including oxidative damage, fibrosis, and hypertrophy. These phenotypic similarities have dubbed inflammatory conditions as premature aging, but they are, in fact, molecularly distinct. Moreover, treatment with an AT1R blocker, losartan, selectively reversed the signaling changes and ameliorated adverse phenotypic effects in the combination of aging and inflammation as well as each independently. PMID:26221650

X-Linked and Autosomal Recessive Alport Syndrome: Pathogenic Variant Features and Further Genotype-Phenotype Correlations

PubMed Central

Savige, Judith; Storey, Helen; Il Cheong, Hae; Gyung Kang, Hee; Park, Eujin; Hilbert, Pascale; Persikov, Anton; Torres-Fernandez, Carmen; Ars, Elisabet; Torra, Roser; Hertz, Jens Michael; Thomassen, Mads; Shagam, Lev; Wang, Dongmao; Wang, Yanyan; Flinter, Frances; Nagel, Mato

2016-01-01

Alport syndrome results from mutations in the COL4A5 (X-linked) or COL4A3/COL4A4 (recessive) genes. This study examined 754 previously- unpublished variants in these genes from individuals referred for genetic testing in 12 accredited diagnostic laboratories worldwide, in addition to all published COL4A5, COL4A3 and COL4A4 variants in the LOVD databases. It also determined genotype-phenotype correlations for variants where clinical data were available. Individuals were referred for genetic testing where Alport syndrome was suspected clinically or on biopsy (renal failure, hearing loss, retinopathy, lamellated glomerular basement membrane), variant pathogenicity was assessed using currently-accepted criteria, and variants were examined for gene location, and age at renal failure onset. Results were compared using Fisher’s exact test (DNA Stata). Altogether 754 new DNA variants were identified, an increase of 25%, predominantly in people of European background. Of the 1168 COL4A5 variants, 504 (43%) were missense mutations, 273 (23%) splicing variants, 73 (6%) nonsense mutations, 169 (14%) short deletions and 76 (7%) complex or large deletions. Only 135 of the 432 Gly residues in the collagenous sequence were substituted (31%), which means that fewer than 10% of all possible variants have been identified. Both missense and nonsense mutations in COL4A5 were not randomly distributed but more common at the 70 CpG sequences (p<10−41 and p<0.001 respectively). Gly>Ala substitutions were underrepresented in all three genes (p< 0.0001) probably because of an association with a milder phenotype. The average age at end-stage renal failure was the same for all mutations in COL4A5 (24.4 ±7.8 years), COL4A3 (23.3 ± 9.3) and COL4A4 (25.4 ± 10.3) (COL4A5 and COL4A3, p = 0.45; COL4A5 and COL4A4, p = 0.55; COL4A3 and COL4A4, p = 0.41). For COL4A5, renal failure occurred sooner with non-missense than missense variants (p<0.01). For the COL4A3 and COL4A4 genes, age at renal

X-Linked and Autosomal Recessive Alport Syndrome: Pathogenic Variant Features and Further Genotype-Phenotype Correlations.

PubMed

Savige, Judith; Storey, Helen; Il Cheong, Hae; Gyung Kang, Hee; Park, Eujin; Hilbert, Pascale; Persikov, Anton; Torres-Fernandez, Carmen; Ars, Elisabet; Torra, Roser; Hertz, Jens Michael; Thomassen, Mads; Shagam, Lev; Wang, Dongmao; Wang, Yanyan; Flinter, Frances; Nagel, Mato

2016-01-01

Alport syndrome results from mutations in the COL4A5 (X-linked) or COL4A3/COL4A4 (recessive) genes. This study examined 754 previously- unpublished variants in these genes from individuals referred for genetic testing in 12 accredited diagnostic laboratories worldwide, in addition to all published COL4A5, COL4A3 and COL4A4 variants in the LOVD databases. It also determined genotype-phenotype correlations for variants where clinical data were available. Individuals were referred for genetic testing where Alport syndrome was suspected clinically or on biopsy (renal failure, hearing loss, retinopathy, lamellated glomerular basement membrane), variant pathogenicity was assessed using currently-accepted criteria, and variants were examined for gene location, and age at renal failure onset. Results were compared using Fisher's exact test (DNA Stata). Altogether 754 new DNA variants were identified, an increase of 25%, predominantly in people of European background. Of the 1168 COL4A5 variants, 504 (43%) were missense mutations, 273 (23%) splicing variants, 73 (6%) nonsense mutations, 169 (14%) short deletions and 76 (7%) complex or large deletions. Only 135 of the 432 Gly residues in the collagenous sequence were substituted (31%), which means that fewer than 10% of all possible variants have been identified. Both missense and nonsense mutations in COL4A5 were not randomly distributed but more common at the 70 CpG sequences (p<10-41 and p<0.001 respectively). Gly>Ala substitutions were underrepresented in all three genes (p< 0.0001) probably because of an association with a milder phenotype. The average age at end-stage renal failure was the same for all mutations in COL4A5 (24.4 ±7.8 years), COL4A3 (23.3 ± 9.3) and COL4A4 (25.4 ± 10.3) (COL4A5 and COL4A3, p = 0.45; COL4A5 and COL4A4, p = 0.55; COL4A3 and COL4A4, p = 0.41). For COL4A5, renal failure occurred sooner with non-missense than missense variants (p<0.01). For the COL4A3 and COL4A4 genes, age at renal failure

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.

[FOXP2 and the molecular biology of language: new evidence. I. Phenotypic aspects and animal models].

PubMed

Benítez-Burraco, A

FOXP2 is the first gene linked to a hereditary variant of specific language impairment and seems to code for a transcriptional repressor that intervenes in the regulation of development and the functioning of certain thalamic-cortical-striatal circuits. In the last three years significant progress has been made in the analysis of the structural and functional properties of the gene. The most notable advances have been made in the genotypic and phenotypic characterisation of new alterations in its sequencing in human beings; the determination in vivo of the functional properties of the mutated proteins generated from said variants; the cloning and characterisation of new orthologues of the gene; the generation of the first knockout and knockdown organisms for it; and a more precise molecular characterisation of the biological role played by the orthologues corresponding to species that are also capable of learning the articulatory patterns of the vocalisations they use to communicate. The latest clinical evidence and that obtained from analysing animal models generated to date appear to suggest the presence of a 'sensory-motor disorder' as the central deficit behind the different phenotypes associated to the different mutations of the gene in the human species, the functionality of the gene FOXP2 during development of the embryo and during the adult phase, its involvement in the development and functioning of the thalamic-cortical-striatal circuits associated to motor planning, sequential behaviour and procedural learning, and significant old age, in developmental terms, of a part of the neuroanatomical substrate that is involved in processing linguistic stimuli in our species.

Ultrasonic vocalizations: a tool for behavioural phenotyping of mouse models of neurodevelopmental disorders

PubMed Central

Scattoni, Maria Luisa; Crawley, Jacqueline; Ricceri, Laura

2009-01-01

In neonatal mice ultrasonic vocalizations have been studied both as an early communicative behavior of the pup-mother dyad and as a sign of an aversive affective state. Adult mice of both sexes produce complex ultrasonic vocalization patterns in different experimental/social contexts. All these vocalizations are becoming an increasingly valuable assay for behavioral phenotyping throughout the mouse life-span and alterations of the ultrasound patterns have been reported in several mouse models of neurodevelopmental disorders. Here we also show that the modulation of vocalizations by maternal cues (maternal potentiation paradigm) – originally identified and investigated in rats - can be measured in C57Bl/6 mouse pups with appropriate modifications of the rat protocol and can likely be applied to mouse behavioral phenotyping. In addition we suggest that a detailed qualitative evaluation of neonatal calls together with analysis of adult mouse vocalization patterns in both sexes in social settings, may lead to a greater understanding of the communication value of vocalizations in mice. Importantly, both neonatal and adult USV altered patterns can be determined during the behavioural phenotyping of mouse models of human neurodevelopmental and neuropsychiatric disorders, starting from those in which deficits in communication are a primary symptom. PMID:18771687

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of

Global urban signatures of phenotypic change in animal and plant populations

PubMed Central

Correa, Cristian; Marzluff, John M.; Hendry, Andrew P.; Palkovacs, Eric P.; Hunt, Victoria M.; Apgar, Travis M.; Zhou, Yuyu

2017-01-01

Humans challenge the phenotypic, genetic, and cultural makeup of species by affecting the fitness landscapes on which they evolve. Recent studies show that cities might play a major role in contemporary evolution by accelerating phenotypic changes in wildlife, including animals, plants, fungi, and other organisms. Many studies of ecoevolutionary change have focused on anthropogenic drivers, but none of these studies has specifically examined the role that urbanization plays in ecoevolution or explicitly examined its mechanisms. This paper presents evidence on the mechanisms linking urban development patterns to rapid evolutionary changes for species that play important functional roles in communities and ecosystems. Through a metaanalysis of experimental and observational studies reporting more than 1,600 phenotypic changes in species across multiple regions, we ask whether we can discriminate an urban signature of phenotypic change beyond the established natural baselines and other anthropogenic signals. We then assess the relative impact of five types of urban disturbances including habitat modifications, biotic interactions, habitat heterogeneity, novel disturbances, and social interactions. Our study shows a clear urban signal; rates of phenotypic change are greater in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to traits that affect ecosystem function, we can map potential ecoevolutionary implications of emerging patterns of urban agglomerations and uncover insights for maintaining key ecosystem functions upon which the sustainability of human well-being depends. PMID:28049817

Global urban signatures of phenotypic change in animal and plant populations.

PubMed

Alberti, Marina; Correa, Cristian; Marzluff, John M; Hendry, Andrew P; Palkovacs, Eric P; Gotanda, Kiyoko M; Hunt, Victoria M; Apgar, Travis M; Zhou, Yuyu

2017-08-22

Humans challenge the phenotypic, genetic, and cultural makeup of species by affecting the fitness landscapes on which they evolve. Recent studies show that cities might play a major role in contemporary evolution by accelerating phenotypic changes in wildlife, including animals, plants, fungi, and other organisms. Many studies of ecoevolutionary change have focused on anthropogenic drivers, but none of these studies has specifically examined the role that urbanization plays in ecoevolution or explicitly examined its mechanisms. This paper presents evidence on the mechanisms linking urban development patterns to rapid evolutionary changes for species that play important functional roles in communities and ecosystems. Through a metaanalysis of experimental and observational studies reporting more than 1,600 phenotypic changes in species across multiple regions, we ask whether we can discriminate an urban signature of phenotypic change beyond the established natural baselines and other anthropogenic signals. We then assess the relative impact of five types of urban disturbances including habitat modifications, biotic interactions, habitat heterogeneity, novel disturbances, and social interactions. Our study shows a clear urban signal; rates of phenotypic change are greater in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to traits that affect ecosystem function, we can map potential ecoevolutionary implications of emerging patterns of urban agglomerations and uncover insights for maintaining key ecosystem functions upon which the sustainability of human well-being depends.

An ENU mutagenesis-derived mouse model with a dominant Jak1 mutation resembling phenotypes of systemic autoimmune disease.

PubMed

Sabrautzki, Sibylle; Janas, Eva; Lorenz-Depiereux, Bettina; Calzada-Wack, Julia; Aguilar-Pimentel, Juan A; Rathkolb, Birgit; Adler, Thure; Cohrs, Christian; Hans, Wolfgang; Diener, Susanne; Fuchs, Helmut; Gailus-Durner, Valerie; Busch, Dirk H; Höfler, Heinz; Ollert, Markus; Strom, Tim M; Wolf, Eckhard; Neff, Frauke; Hrabě de Angelis, Martin

2013-08-01

Within the Munich, Germany, N-ethyl-N-nitrosourea mouse mutagenesis program, we isolated a dominant Jak1 mouse model resembling phenotypic characteristics related to autoimmune disease. Chromosomal sequencing revealed a new Jak1 (p.Ser645Pro) point mutation at the conserved serine of the pseudokinase domain, corresponding to a somatic human mutation (p.Ser646Phe) inducing a constitutive activation of the Janus kinase (JAK)/STAT pathway. Morphologically, all Jak1(S645P+/-) mice showed a progressive structural deterioration of ears starting at the age of 4 months, with mononuclear cell infiltration into the dermis. Female mutant mice, in particular, developed severe skin lesions in the neck from 7 months of age. The IHC analysis of these lesions showed an activation of Stat3 downstream to Jak1(S645P) and elevated tissue levels of IL-6. Histopathological analysis of liver revealed a nodular regenerative hyperplasia. In the spleen, the number of Russell bodies was doubled, correlating with significant increased levels of all immunoglobulin isotypes and anti-DNA antibodies in serum. Older mutant mice developed thrombocytopenia and altered microcytic red blood cell counts. Jak1(S645P+/-) mice showed phenotypes related to impaired bone metabolism as increased carboxy-terminal collagen cross-link-1 levels and alkaline phosphatase activities in plasma, hypophosphatemia, and strongly decreased bone morphometric values. Taken together, Jak1(S645P+/-) mice showed an increased activation of the IL-6-JAK-STAT pathway leading to a systemic lupus erythematosus-like phenotype and offering a new valuable tool to study the role of the JAK/STAT pathway in disease development. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Assessment of Cell Line Models of Primary Human Cells by Raman Spectral Phenotyping

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2010-01-01

Abstract Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures. PMID:20409492

Recapitulation of spinal motor neuron-specific disease phenotypes in a human cell model of spinal muscular atrophy

PubMed Central

Wang, Zhi-Bo; Zhang, Xiaoqing; Li, Xue-Jun

2013-01-01

Establishing human cell models of spinal muscular atrophy (SMA) to mimic motor neuron-specific phenotypes holds the key to understanding the pathogenesis of this devastating disease. Here, we developed a closely representative cell model of SMA by knocking down the disease-determining gene, survival motor neuron (SMN), in human embryonic stem cells (hESCs). Our study with this cell model demonstrated that knocking down of SMN does not interfere with neural induction or the initial specification of spinal motor neurons. Notably, the axonal outgrowth of spinal motor neurons was significantly impaired and these disease-mimicking neurons subsequently degenerated. Furthermore, these disease phenotypes were caused by SMN-full length (SMN-FL) but not SMN-Δ7 (lacking exon 7) knockdown, and were specific to spinal motor neurons. Restoring the expression of SMN-FL completely ameliorated all of the disease phenotypes, including specific axonal defects and motor neuron loss. Finally, knockdown of SMN-FL led to excessive mitochondrial oxidative stress in human motor neuron progenitors. The involvement of oxidative stress in the degeneration of spinal motor neurons in the SMA cell model was further confirmed by the administration of N-acetylcysteine, a potent antioxidant, which prevented disease-related apoptosis and subsequent motor neuron death. Thus, we report here the successful establishment of an hESC-based SMA model, which exhibits disease gene isoform specificity, cell type specificity, and phenotype reversibility. Our model provides a unique paradigm for studying how motor neurons specifically degenerate and highlights the potential importance of antioxidants for the treatment of SMA. PMID:23208423

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.

PubMed

Masino, Aaron J; Dechene, Elizabeth T; Dulik, Matthew C; Wilkens, Alisha; Spinner, Nancy B; Krantz, Ian D; Pennington, Jeffrey W; Robinson, Peter N; White, Peter S

2014-07-21

Exome sequencing is a promising method for diagnosing patients with a complex phenotype. However, variant interpretation relative to patient phenotype can be challenging in some scenarios, particularly clinical assessment of rare complex phenotypes. Each patient's sequence reveals many possibly damaging variants that must be individually assessed to establish clear association with patient phenotype. To assist interpretation, we implemented an algorithm that ranks a given set of genes relative to patient phenotype. The algorithm orders genes by the semantic similarity computed between phenotypic descriptors associated with each gene and those describing the patient. Phenotypic descriptor terms are taken from the Human Phenotype Ontology (HPO) and semantic similarity is derived from each term's information content. Model validation was performed via simulation and with clinical data. We simulated 33 Mendelian diseases with 100 patients per disease. We modeled clinical conditions by adding noise and imprecision, i.e. phenotypic terms unrelated to the disease and terms less specific than the actual disease terms. We ranked the causative gene against all 2488 HPO annotated genes. The median causative gene rank was 1 for the optimal and noise cases, 12 for the imprecision case, and 60 for the imprecision with noise case. Additionally, we examined a clinical cohort of subjects with hearing impairment. The disease gene median rank was 22. However, when also considering the patient's exome data and filtering non-exomic and common variants, the median rank improved to 3. Semantic similarity can rank a causative gene highly within a gene list relative to patient phenotype characteristics, provided that imprecision is mitigated. The clinical case results suggest that phenotype rank combined with variant analysis provides significant improvement over the individual approaches. We expect that this combined prioritization approach may increase accuracy and decrease effort for

Mathematical modeling of atopic dermatitis reveals "double-switch" mechanisms underlying 4 common disease phenotypes.

PubMed

Domínguez-Hüttinger, Elisa; Christodoulides, Panayiotis; Miyauchi, Kosuke; Irvine, Alan D; Okada-Hatakeyama, Mariko; Kubo, Masato; Tanaka, Reiko J

2017-06-01

The skin barrier acts as the first line of defense against constant exposure to biological, microbial, physical, and chemical environmental stressors. Dynamic interplay between defects in the skin barrier, dysfunctional immune responses, and environmental stressors are major factors in the development of atopic dermatitis (AD). A systems biology modeling approach can yield significant insights into these complex and dynamic processes through integration of prior biological data. We sought to develop a multiscale mathematical model of AD pathogenesis that describes the dynamic interplay between the skin barrier, environmental stress, and immune dysregulation and use it to achieve a coherent mechanistic understanding of the onset, progression, and prevention of AD. We mathematically investigated synergistic effects of known genetic and environmental risk factors on the dynamic onset and progression of the AD phenotype, from a mostly asymptomatic mild phenotype to a severe treatment-resistant form. Our model analysis identified a "double switch," with 2 concatenated bistable switches, as a key network motif that dictates AD pathogenesis: the first switch is responsible for the reversible onset of inflammation, and the second switch is triggered by long-lasting or frequent activation of the first switch, causing irreversible onset of systemic T H 2 sensitization and worsening of AD symptoms. Our mathematical analysis of the bistable switch predicts that genetic risk factors decrease the threshold of environmental stressors to trigger systemic T H 2 sensitization. This analysis predicts and explains 4 common clinical AD phenotypes from a mild and reversible phenotype through to severe and recalcitrant disease and provides a mechanistic explanation for clinically demonstrated preventive effects of emollient treatments against development of AD. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A latent modeling approach to genotype-phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype.

PubMed

McGrath, L M; Mustanski, B; Metzger, A; Pine, D S; Kistner-Griffin, E; Cook, E; Wakschlag, L S

2012-08-01

This study illustrates the application of a latent modeling approach to genotype-phenotype relationships and gene × environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the monoamine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N = 192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA × physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA.

Multi-source and ontology-based retrieval engine for maize mutant phenotypes

PubMed Central

Green, Jason M.; Harnsomburana, Jaturon; Schaeffer, Mary L.; Lawrence, Carolyn J.; Shyu, Chi-Ren

2011-01-01

Model Organism Databases, including the various plant genome databases, collect and enable access to massive amounts of heterogeneous information, including sequence data, gene product information, images of mutant phenotypes, etc, as well as textual descriptions of many of these entities. While a variety of basic browsing and search capabilities are available to allow researchers to query and peruse the names and attributes of phenotypic data, next-generation search mechanisms that allow querying and ranking of text descriptions are much less common. In addition, the plant community needs an innovative way to leverage the existing links in these databases to search groups of text descriptions simultaneously. Furthermore, though much time and effort have been afforded to the development of plant-related ontologies, the knowledge embedded in these ontologies remains largely unused in available plant search mechanisms. Addressing these issues, we have developed a unique search engine for mutant phenotypes from MaizeGDB. This advanced search mechanism integrates various text description sources in MaizeGDB to aid a user in retrieving desired mutant phenotype information. Currently, descriptions of mutant phenotypes, loci and gene products are utilized collectively for each search, though expansion of the search mechanism to include other sources is straightforward. The retrieval engine, to our knowledge, is the first engine to exploit the content and structure of available domain ontologies, currently the Plant and Gene Ontologies, to expand and enrich retrieval results in major plant genomic databases. Database URL: http:www.PhenomicsWorld.org/QBTA.php PMID:21558151

Decentralising Curriculum Reform: The Link Teacher Model of In-Service Training.

ERIC Educational Resources Information Center

Wildy, Helen; And Others

1996-01-01

Presents a (Western Australian) case study of the link teacher model, a decentralized, "train the trainer" approach to inservice education. Discusses the model's perceived effectiveness, the link teachers' role, central authority support, and new experimentation opportunities. Combining centralized syllabus change with decentralized…

Linking knowledge and action through mental models of sustainable agriculture.

PubMed

Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

2014-09-09

Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer "mental models" of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems.

Dosage effect of a Phex mutation in a murine model of X-linked hypophosphatemia

PubMed Central

Ichikawa, Shoji; Gray, Amie K.; Bikorimana, Emmanuel; Econs, Michael J.

2013-01-01

X-linked hypophosphatemia (XLH) is caused by mutations in the PHEX gene, which increase circulating levels of the phosphaturic hormone, fibroblast growth factor 23 (FGF23). Since XLH is a dominant disease, one mutant allele is sufficient for manifestation of the disease. However, dosage effect of a PHEX mutation in XLH is not completely understood. To examine the effect of Phex genotypes, we compared serum biochemistries and skeletal measures between all five possible genotypes of a new murine model of XLH (PhexK496X or PhexJrt). Compared to sex-matched littermate controls, all Phex mutant mice had hypophosphatemia, mild hypocalcemia, and increased parathyroid hormone and alkaline phosphatase levels. Furthermore, mutant mice had markedly elevated serum Fgf23 levels due to increased Fgf23 expression and reduced cleavage of Fgf23. Although females with a homozygous Phex mutation were slightly more hypocalcemic and hypophosphatemic than heterozygous females, the two groups had comparable intact Fgf23 levels. Similarly, there was no difference in intact Fgf23 or phosphorus concentrations between hemizygous males and heterozygous females. Compared to heterozygous females, homozygous counterparts were significantly smaller and had shorter femurs with reduced bone mineral density, suggesting the existence of dosage effect in the skeletal phenotype of XLH. However, overall phenotypic trends in regards to mineral ion homeostasis were mostly unaffected by the presence of one or two mutant Phex allele(s). The lack of gene dosage effect on circulating Fgf23 (and thus, phosphorus) levels suggests that a Phex mutation may create the lower set point for extracellular phosphate concentrations. PMID:23700148

Dosage effect of a Phex mutation in a murine model of X-linked hypophosphatemia.

PubMed

Ichikawa, Shoji; Gray, Amie K; Bikorimana, Emmanuel; Econs, Michael J

2013-08-01

X-linked hypophosphatemia (XLH) is caused by mutations in the PHEX gene, which increase circulating levels of the phosphaturic hormone, fibroblast growth factor 23 (FGF23). Because XLH is a dominant disease, one mutant allele is sufficient for manifestation of the disease. However, the dosage effect of a PHEX mutation in XLH is not completely understood. To examine the effect of Phex genotypes, we compared serum biochemistries and skeletal measures between all five possible genotypes of a new murine model of XLH (Phex (K496X) or Phex (Jrt) ). Compared to sex-matched littermate controls, all Phex mutant mice had hypophosphatemia, mild hypocalcemia, and increased parathyroid hormone and alkaline phosphatase levels. Furthermore, mutant mice had markedly elevated serum Fgf23 levels due to increased Fgf23 expression and reduced cleavage of Fgf23. Although females with a homozygous Phex mutation were slightly more hypocalcemic and hypophosphatemic than heterozygous females, the two groups had comparable intact Fgf23 levels. Similarly, there was no difference in intact Fgf23 or phosphorus concentrations between hemizygous males and heterozygous females. Compared to heterozygous females, homozygous counterparts were significantly smaller and had shorter femurs with reduced bone mineral density, suggesting the existence of dosage effect in the skeletal phenotype of XLH. However, overall phenotypic trends in regards to mineral ion homeostasis were mostly unaffected by the presence of one or two mutant Phex allele(s). The lack of a gene dosage effect on circulating Fgf23 (and thus phosphorus) levels suggests that a Phex mutation may create the lower set point for extracellular phosphate concentrations.

XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments

PubMed Central

2010-01-01

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans. PMID:20214801

XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments.

PubMed

Swertz, Morris A; Velde, K Joeri van der; Tesson, Bruno M; Scheltema, Richard A; Arends, Danny; Vera, Gonzalo; Alberts, Rudi; Dijkstra, Martijn; Schofield, Paul; Schughart, Klaus; Hancock, John M; Smedley, Damian; Wolstencroft, Katy; Goble, Carole; de Brock, Engbert O; Jones, Andrew R; Parkinson, Helen E; Jansen, Ritsert C

2010-01-01

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.

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

PubMed Central

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

2014-01-01

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

An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms.

PubMed

Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Peissig, Peggy L; Denny, Joshua C; Kho, Abel N; Miller, Aaron; Pathak, Jyotishman

2012-01-01

The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts and informaticians. To make it easier to port algorithms across institutions, it is desirable to represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: the Quality Data Model (QDM). We selected 9 phenotyping algorithms that had been previously developed as part of the eMERGE consortium and translated them into QDM format. Our study concluded that the QDM contains several core elements that make it a promising format for EHR-driven phenotyping algorithms for clinical research. However, we also found areas in which the QDM could be usefully extended, such as representing information extracted from clinical text, and the ability to handle algorithms that do not consist of Boolean combinations of criteria.

Natural Variation of Model Mutant Phenotypes in Ciona intestinalis

PubMed Central

Brown, Euan R.; Leccia, Nicola I.; Squarzoni, Paola; Tarallo, Raffaella; Alfano, Christian; Caputi, Luigi; D'Ambrosio, Palmira; Daniele, Paola; D'Aniello, Enrico; D'Aniello, Salvatore; Maiella, Sylvie; Miraglia, Valentina; Russo, Monia Teresa; Sorrenti, Gerarda; Branno, Margherita; Cariello, Lucio; Cirino, Paola; Locascio, Annamaria; Spagnuolo, Antonietta; Zanetti, Laura; Ristoratore, Filomena

2008-01-01

Background The study of ascidians (Chordata, Tunicata) has made a considerable contribution to our understanding of the origin and evolution of basal chordates. To provide further information to support forward genetics in Ciona intestinalis, we used a combination of natural variation and neutral population genetics as an approach for the systematic identification of new mutations. In addition to the significance of developmental variation for phenotype-driven studies, this approach can encompass important implications in evolutionary and population biology. Methodology/Principal Findings Here, we report a preliminary survey for naturally occurring mutations in three geographically interconnected populations of C. intestinalis. The influence of historical, geographical and environmental factors on the distribution of abnormal phenotypes was assessed by means of 12 microsatellites. We identified 37 possible mutant loci with stereotyped defects in embryonic development that segregate in a way typical of recessive alleles. Local populations were found to differ in genetic organization and frequency distribution of phenotypic classes. Conclusions/Significance Natural genetic polymorphism of C. intestinalis constitutes a valuable source of phenotypes for studying embryonic development in ascidians. Correlating genetic structure and the occurrence of abnormal phenotypes is a crucial focus for understanding the selective forces that shape natural finite populations, and may provide insights of great importance into the evolutionary mechanisms that generate animal diversity. PMID:18523552

Genetics Home Reference: X-linked juvenile retinoschisis

MedlinePlus

... juvenile retinoschisis (XLRS): a review of genotype-phenotype relationships. Semin Ophthalmol. 2013 Sep-Nov;28(5-6): ... for Links Data Files & API Site Map Subscribe Customer Support USA.gov Copyright Privacy Accessibility FOIA Viewers & ...

How to consistently link extraversion and intelligence to the catechol-O-methyltransferase (COMT) gene: on defining and measuring psychological phenotypes in neurogenetic research.

PubMed

Wacker, Jan; Mueller, Erik M; Hennig, Jürgen; Stemmler, Gerhard

2012-02-01

The evidence for associations between genetic polymorphisms and complex behavioral/psychological phenotypes (traits) has thus far been weak and inconsistent. Using the well-studied Val158Met polymorphism of the catechol-O-methyltransferase (COMT) gene as an example, we demonstrate that using theoretical models to guide phenotype definition and measuring the phenotypes of interest with a high degree of specificity reveals strong gene-behavior associations that are consistent with prior work and that would have otherwise gone unnoticed. Only after statistically controlling for irrelevant portions of phenotype variance did we observe strong (Cohen's d = 0.33-0.70) and significant associations between COMT Val158Met and both cognitive and affective traits in a healthy male sample (N = 201) in Study 1: Carriers of the Met allele scored higher in fluid intelligence (reasoning) but lower in both crystallized intelligence (general knowledge) and the agency facet of extraversion. In Study 2, we conceptually replicated the association of COMT Val158Met with the agency facet of extraversion after partialing irrelevant phenotype variance in a female sample (N = 565). Finally, through reanalysis of a large published data set we showed that Met allele carriers also scored higher in indicators of fluid intelligence after partialing verbal fluency. Because the Met allele codes for a less efficient variant of the enzyme COMT, resulting in higher levels of extrasynaptic prefrontal dopamine, these observations provide further support for a role for dopamine in both intelligence and extraversion. More importantly, the present findings have important implications for the definition of psychological phenotypes in neurogenetic research.

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

PubMed Central

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

2008-01-01

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

Towards improving phenotype representation in OWL

PubMed Central

2012-01-01

Background Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected entities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies. Methods We analyze formalizations of complex phenotype descriptions in the Web Ontology Language (OWL) that are based on the EQ model, identify several representational challenges and analyze potential solutions to address these challenges. Results In particular, we suggest a novel, role-based approach to represent relational qualities such as concentration of iron in spleen, discuss its ontological foundation in the General Formal Ontology (GFO) and evaluate its representation in OWL and the benefits it can bring to the representation of phenotype annotations. Conclusion Our analysis of OWL-based representations of phenotypes can contribute to improving consistency and expressiveness of formal phenotype descriptions. PMID:23046625

Phenotypic Robustness and the Assortativity Signature of Human Transcription Factor Networks

PubMed Central

Pechenick, Dov A.; Payne, Joshua L.; Moore, Jason H.

2014-01-01

Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs — such as their degree distribution — with the robustness of a TFN's gene expression phenotype to genetic and environmental perturbation. Another important topological property is assortativity, which measures the tendency of nodes with similar numbers of edges to connect. In directed networks, assortativity comprises four distinct components that collectively form an assortativity signature. We know very little about how a TFN's assortativity signature affects the robustness of its gene expression phenotype to perturbation. While recent theoretical results suggest that increasing one specific component of a TFN's assortativity signature leads to increased phenotypic robustness, the biological context of this finding is currently limited because the assortativity signatures of real-world TFNs have not been characterized. It is therefore unclear whether these earlier theoretical findings are biologically relevant. Moreover, it is not known how the other three components of the assortativity signature contribute to the phenotypic robustness of TFNs. Here, we use publicly available DNaseI-seq data to measure the assortativity signatures of genome-wide TFNs in 41 distinct human cell and tissue types. We find that all TFNs share a common assortativity signature and that this signature confers phenotypic robustness to model TFNs. Lastly, we determine the extent to which each of the four components of

CRAVE: a database, middleware and visualization system for phenotype ontologies.

PubMed

Gkoutos, Georgios V; Green, Eain C J; Greenaway, Simon; Blake, Andrew; Mallon, Ann-Marie; Hancock, John M

2005-04-01

A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.

A latent modeling approach to genotype–phenotype relationships: maternal problem behavior clusters, prenatal smoking, and MAOA genotype

PubMed Central

Mustanski, B.; Metzger, A.; Pine, D. S.; Kistner-Griffin, E.; Cook, E.; Wakschlag, L. S.

2013-01-01

This study illustrates the application of a latent modeling approach to genotype–phenotype relationships and gene×environment interactions, using a novel, multidimensional model of adult female problem behavior, including maternal prenatal smoking. The gene of interest is the mono-amine oxidase A (MAOA) gene which has been well studied in relation to antisocial behavior. Participants were adult women (N=192) who were sampled from a prospective pregnancy cohort of non-Hispanic, white individuals recruited from a neighborhood health clinic. Structural equation modeling was used to model a female problem behavior phenotype, which included conduct problems, substance use, impulsive-sensation seeking, interpersonal aggression, and prenatal smoking. All of the female problem behavior dimensions clustered together strongly, with the exception of prenatal smoking. A main effect of MAOA genotype and a MAOA× physical maltreatment interaction were detected with the Conduct Problems factor. Our phenotypic model showed that prenatal smoking is not simply a marker of other maternal problem behaviors. The risk variant in the MAOA main effect and interaction analyses was the high activity MAOA genotype, which is discrepant from consensus findings in male samples. This result contributes to an emerging literature on sex-specific interaction effects for MAOA. PMID:22610759

Relational machine learning for electronic health record-driven phenotyping.

PubMed

Peissig, Peggy L; Santos Costa, Vitor; Caldwell, Michael D; Rottscheit, Carla; Berg, Richard L; Mendonca, Eneida A; Page, David

2014-12-01

Electronic health records (EHR) offer medical and pharmacogenomics research unprecedented opportunities to identify and classify patients at risk. EHRs are collections of highly inter-dependent records that include biological, anatomical, physiological, and behavioral observations. They comprise a patient's clinical phenome, where each patient has thousands of date-stamped records distributed across many relational tables. Development of EHR computer-based phenotyping algorithms require time and medical insight from clinical experts, who most often can only review a small patient subset representative of the total EHR records, to identify phenotype features. In this research we evaluate whether relational machine learning (ML) using inductive logic programming (ILP) can contribute to addressing these issues as a viable approach for EHR-based phenotyping. Two relational learning ILP approaches and three well-known WEKA (Waikato Environment for Knowledge Analysis) implementations of non-relational approaches (PART, J48, and JRIP) were used to develop models for nine phenotypes. International Classification of Diseases, Ninth Revision (ICD-9) coded EHR data were used to select training cohorts for the development of each phenotypic model. Accuracy, precision, recall, F-Measure, and Area Under the Receiver Operating Characteristic (AUROC) curve statistics were measured for each phenotypic model based on independent manually verified test cohorts. A two-sided binomial distribution test (sign test) compared the five ML approaches across phenotypes for statistical significance. We developed an approach to automatically label training examples using ICD-9 diagnosis codes for the ML approaches being evaluated. Nine phenotypic models for each ML approach were evaluated, resulting in better overall model performance in AUROC using ILP when compared to PART (p=0.039), J48 (p=0.003) and JRIP (p=0.003). ILP has the potential to improve phenotyping by independently delivering

Fluctuating selection across years and phenotypic variation in food-deceptive orchids.

PubMed

Scopece, Giovanni; Juillet, Nicolas; Lexer, Christian; Cozzolino, Salvatore

2017-01-01

Nectarless flowers that deceive pollinators offer an opportunity to study asymmetric plant-insect interactions. Orchids are a widely used model for studying these interactions because they encompass several thousand species adopting deceptive pollination systems. High levels of intra-specific phenotypic variation have been reported in deceptive orchids, suggesting a reduced consistency of pollinator-mediated selection on their floral traits. Nevertheless, several studies report on widespread directional selection mediated by pollinators even in these deceptive orchids. In this study we test the hypothesis that the observed selection can fluctuate across years in strength and direction thus likely contributing to the phenotypic variability of this orchid group. We performed a three-year study estimating selection differentials and selection gradients for nine phenotypic traits involved in insect attraction in two Mediterranean orchid species, namely Orchis mascula and O. pauciflora , both relying on a well-described food-deceptive pollination strategy. We found weak directional selection and marginally significant selection gradients in the two investigated species with significant intra-specific differences in selection differentials across years. Our data do not link this variation with a specific environmental cause, but our results suggest that pollinator-mediated selection in food-deceptive orchids can change in strength and in direction over time. In perennial plants, such as orchids, different selection differentials in the same populations in different flowering seasons can contribute to the maintenance of phenotypic variation often reported in deceptive orchids.

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Protection, pathogenesis and phenotypic plasticity in Plasmodium falciparum malaria.

PubMed

Roberts, D J; Biggs, B A; Brown, G; Newbold, C I

1993-08-01

Why does Plasmodium falciparum cause severe illness in some but not all infections? How is clinical immunity acquired? These questions have intrigued investigators since the clinical epidemiology of malaria was first described. The search for answers to both questions has highlighted the changes that take place at the surface of infected red blood cells during the last half of the erythrocytic cycle. These changes specify the antigenic and adhesive or cytoadherence phenotypes for the infected cell. Now the antigenic and adhesive phenotypes appear to be linked and together undergo clonal variation. In this article David Roberts, Beverley-Ann Biggs, Graham Brown and Christopher Newbold explain how clonal phenotypic variation and the linkage between adhesive and antigenic types contribute to our understanding of naturally acquired immunity and of pathogenesis of severe malaria.

UAS Modeling of the Communication Links Study Results

NASA Technical Reports Server (NTRS)

Birr, Richard B.; Girgis, Nancy; Murray, Jennifer

2011-01-01

The Federal Aviation Administration (FAA) is the authority that grants access into, and operations within, the National Airspace System (NAS) for all aircraft, including Unmanned Aircraft Systems (UAS). The safe operation of UAS in the NAS must be assured if the full potential of UAS is to be realized and supported by the public and Congress. This report analyzed the communication systems that are needed for the safe operations of UAS in the NAS. Safe operations can be defined as the availability of the required links to carry the information to control the UAS and the return links to allow controllers to know where the UAS is at any given moment as well as how it is performing. This report is the end result of work performed jointly between the FAA and National Aeronautics and Space Administration (NASA)/Kennedy Space Center (NASA KSC). The work was done in support of the Radio Technical Commission for Aeronautics (RTCA) Special Committee 203 (SC-203) Control and Communications Working Group. The RTCA is a federal advisory committee to the FAA. Though the work was not under the direction of the working group, a large part of the specific values used in the simulations came from the working group. Specifically, all of the radio links were modeled based on the formulation completed by the working group. This report analyzed three scenarios from RTCA SC-203 that represent how a UAS would operate in the NAS. Each scenario was created using the Satellite Tool Kit (STK) modeling and simulation tool. The flight paths of the UAS were generated and the UAS dynamics were likewise modeled. Then each communication asset such as transmitters, receivers, and antennas were modeled and placed on the appropriate UAS, satellite, or Control Station (CS). After that, the radio links were analyzed for signal strength and antenna blockage, and the overall link performance was analyzed in detail. The goal was to obtain 99.9% availability on all of the radio communication links. In order

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.

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

PubMed Central

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

2018-01-01

Background Researchers are developing methods to automatically extract clinically relevant and useful patient characteristics from raw healthcare datasets. These characteristics, often capturing essential properties of patients with common medical conditions, are called computational phenotypes. Being generated by automated or semiautomated, data-driven methods, such potential phenotypes need to be validated as clinically meaningful (or not) before they are acceptable for use in decision making. Objective The objective of this study was to present Phenotype Instance Verification and Evaluation Tool (PIVET), a framework that uses co-occurrence analysis on an online corpus of publically available medical journal articles to build clinical relevance evidence sets for user-supplied phenotypes. PIVET adopts a conceptual framework similar to the pioneering prototype tool PheKnow-Cloud that was developed for the phenotype validation task. PIVET completely refactors each part of the PheKnow-Cloud pipeline to deliver vast improvements in speed without sacrificing the quality of the insights PheKnow-Cloud achieved. Methods PIVET leverages indexing in NoSQL databases to efficiently generate evidence sets. Specifically, PIVET uses a succinct representation of the phenotypes that corresponds to the index on the corpus database and an optimized co-occurrence algorithm inspired by the Aho-Corasick algorithm. We compare PIVET’s phenotype representation with PheKnow-Cloud’s by using PheKnow-Cloud’s experimental setup. In PIVET’s framework, we also introduce a statistical model trained on domain expert–verified phenotypes to automatically classify phenotypes as clinically relevant or not. Additionally, we show how the classification model can be used to examine user-supplied phenotypes in an online, rather than batch, manner. Results PIVET maintains the discriminative power of PheKnow-Cloud in terms of identifying clinically relevant phenotypes for the same corpus with

Pathophysiological mechanisms of neuropathic pain: comparison of sensory phenotypes in patients and human surrogate pain models.

PubMed

Vollert, Jan; Magerl, Walter; Baron, Ralf; Binder, Andreas; Enax-Krumova, Elena K; Geisslinger, Gerd; Gierthmühlen, Janne; Henrich, Florian; Hüllemann, Philipp; Klein, Thomas; Lötsch, Jörn; Maier, Christoph; Oertel, Bruno; Schuh-Hofer, Sigrid; Tölle, Thomas R; Treede, Rolf-Detlef

2018-06-01

As an indirect approach to relate previously identified sensory phenotypes of patients suffering from peripheral neuropathic pain to underlying mechanisms, we used a published sorting algorithm to estimate the prevalence of denervation, peripheral and central sensitization in 657 healthy subjects undergoing experimental models of nerve block (NB) (compression block and topical lidocaine), primary hyperalgesia (PH) (sunburn and topical capsaicin), or secondary hyperalgesia (intradermal capsaicin and electrical high-frequency stimulation), and in 902 patients suffering from neuropathic pain. Some of the data have been previously published. Randomized split-half analysis verified a good concordance with a priori mechanistic sensory profile assignment in the training (79%, Cohen κ = 0.54, n = 265) and the test set (81%, Cohen κ = 0.56, n = 279). Nerve blocks were characterized by pronounced thermal and mechanical sensory loss, but also mild pinprick hyperalgesia and paradoxical heat sensations. Primary hyperalgesia was characterized by pronounced gain for heat, pressure and pinprick pain, and mild thermal sensory loss. Secondary hyperalgesia was characterized by pronounced pinprick hyperalgesia and mild thermal sensory loss. Topical lidocaine plus topical capsaicin induced a combined phenotype of NB plus PH. Topical menthol was the only model with significant cold hyperalgesia. Sorting of the 902 patients into these mechanistic phenotypes led to a similar distribution as the original heuristic clustering (65% identity, Cohen κ = 0.44), but the denervation phenotype was more frequent than in heuristic clustering. These data suggest that sorting according to human surrogate models may be useful for mechanism-based stratification of neuropathic pain patients for future clinical trials, as encouraged by the European Medicines Agency.

Percolation on fitness landscapes: effects of correlation, phenotype, and incompatibilities

PubMed Central

Gravner, Janko; Pitman, Damien; Gavrilets, Sergey

2009-01-01

We study how correlations in the random fitness assignment may affect the structure of fitness landscapes, in three classes of fitness models. The first is a phenotype space in which individuals are characterized by a large number n of continuously varying traits. In a simple model of random fitness assignment, viable phenotypes are likely to form a giant connected cluster percolating throughout the phenotype space provided the viability probability is larger than 1/2n. The second model explicitly describes genotype-to-phenotype and phenotype-to-fitness maps, allows for neutrality at both phenotype and fitness levels, and results in a fitness landscape with tunable correlation length. Here, phenotypic neutrality and correlation between fitnesses can reduce the percolation threshold, and correlations at the point of phase transition between local and global are most conducive to the formation of the giant cluster. In the third class of models, particular combinations of alleles or values of phenotypic characters are “incompatible” in the sense that the resulting genotypes or phenotypes have zero fitness. This setting can be viewed as a generalization of the canonical Bateson-Dobzhansky-Muller model of speciation and is related to K- SAT problems, prominent in computer science. We analyze the conditions for the existence of viable genotypes, their number, as well as the structure and the number of connected clusters of viable genotypes. We show that analysis based on expected values can easily lead to wrong conclusions, especially when fitness correlations are strong. We focus on pairwise incompatibilities between diallelic loci, but we also address multiple alleles, complex incompatibilities, and continuous phenotype spaces. In the case of diallelic loci, the number of clusters is stochastically bounded and each cluster contains a very large sub-cube. Finally, we demonstrate that the discrete NK model shares some signature properties of models with high

Disease Model Discovery from 3,328 Gene Knockouts by The International Mouse Phenotyping Consortium

PubMed Central

Meehan, Terrence F.; Conte, Nathalie; West, David B.; Jacobsen, Julius O.; Mason, Jeremy; Warren, Jonathan; Chen, Chao-Kung; Tudose, Ilinca; Relac, Mike; Matthews, Peter; Karp, Natasha; Santos, Luis; Fiegel, Tanja; Ring, Natalie; Westerberg, Henrik; Greenaway, Simon; Sneddon, Duncan; Morgan, Hugh; Codner, Gemma F; Stewart, Michelle E; Brown, James; Horner, Neil; Haendel, Melissa; Washington, Nicole; Mungall, Christopher J.; Reynolds, Corey L; Gallegos, Juan; Gailus-Durner, Valerie; Sorg, Tania; Pavlovic, Guillaume; Bower, Lynette R; Moore, Mark; Morse, Iva; Gao, Xiang; Tocchini-Valentini, Glauco P; Obata, Yuichi; Cho, Soo Young; Seong, Je Kyung; Seavitt, John; Beaudet, Arthur L.; Dickinson, Mary E.; Herault, Yann; Wurst, Wolfgang; de Angelis, Martin Hrabe; Lloyd, K.C. Kent; Flenniken, Ann M; Nutter, Lauryl MJ; Newbigging, Susan; McKerlie, Colin; Justice, Monica J.; Murray, Stephen A.; Svenson, Karen L.; Braun, Robert E.; White, Jacqueline K.; Bradley, Allan; Flicek, Paul; Wells, Sara; Skarnes, William C.; Adams, David J.; Parkinson, Helen; Mallon, Ann-Marie; Brown, Steve D.M.; Smedley, Damian

2017-01-01

Although next generation sequencing has revolutionised the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by our lack of knowledge of function and pathobiological mechanism for most genes. To address this challenge, the International Mouse Phenotyping Consortium (IMPC) is creating a genome- and phenome-wide catalogue of gene function by characterizing new knockout mouse strains across diverse biological systems through a broad set of standardised phenotyping tests, with all mice made readily available to the biomedical community. Analysing the first 3328 genes reveals models for 360 diseases including the first for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations are novel, providing the first functional evidence for 1092 genes and candidates in unsolved diseases such as Arrhythmogenic Right Ventricular Dysplasia 3. Finally, we describe our role in variant functional validation with the 100,000 Genomes and other projects. PMID:28650483

X-linked Alport syndrome caused by splicing mutations in COL4A5.

PubMed

Nozu, Kandai; Vorechovsky, Igor; Kaito, Hiroshi; Fu, Xue Jun; Nakanishi, Koichi; Hashimura, Yuya; Hashimoto, Fusako; Kamei, Koichi; Ito, Shuichi; Kaku, Yoshitsugu; Imasawa, Toshiyuki; Ushijima, Katsumi; Shimizu, Junya; Makita, Yoshio; Konomoto, Takao; Yoshikawa, Norishige; Iijima, Kazumoto

2014-11-07

X-linked Alport syndrome is caused by mutations in the COL4A5 gene. Although many COL4A5 mutations have been detected, the mutation detection rate has been unsatisfactory. Some men with X-linked Alport syndrome show a relatively mild phenotype, but molecular basis investigations have rarely been conducted to clarify the underlying mechanism. In total, 152 patients with X-linked Alport syndrome who were suspected of having Alport syndrome through clinical and pathologic investigations and referred to the hospital for mutational analysis between January of 2006 and January of 2013 were genetically diagnosed. Among those patients, 22 patients had suspected splice site mutations. Transcripts are routinely examined when suspected splice site mutations for abnormal transcripts are detected; 11 of them showed expected exon skipping, but others showed aberrant splicing patterns. The mutation detection strategy had two steps: (1) genomic DNA analysis using PCR and direct sequencing and (2) mRNA analysis using RT-PCR to detect RNA processing abnormalities. Six splicing consensus site mutations resulting in aberrant splicing patterns, one exonic mutation leading to exon skipping, and four deep intronic mutations producing cryptic splice site activation were identified. Interestingly, one case produced a cryptic splice site with a single nucleotide substitution in the deep intron that led to intronic exonization containing a stop codon; however, the patient showed a clearly milder phenotype for X-linked Alport syndrome in men with a truncating mutation. mRNA extracted from the kidney showed both normal and abnormal transcripts, with the normal transcript resulting in the milder phenotype. This novel mechanism leads to mild clinical characteristics. This report highlights the importance of analyzing transcripts to enhance the mutation detection rate and provides insight into genotype-phenotype correlations. This approach can clarify the cause of atypically mild phenotypes in X-linked

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

PubMed Central

Chong, Jessica X.; Buckingham, Kati J.; Jhangiani, Shalini N.; Boehm, Corinne; Sobreira, Nara; Smith, Joshua D.; Harrell, Tanya M.; McMillin, Margaret J.; Wiszniewski, Wojciech; Gambin, Tomasz; Coban Akdemir, Zeynep H.; Doheny, Kimberly; Scott, Alan F.; Avramopoulos, Dimitri; Chakravarti, Aravinda; Hoover-Fong, Julie; Mathews, Debra; Witmer, P. Dane; Ling, Hua; Hetrick, Kurt; Watkins, Lee; Patterson, Karynne E.; Reinier, Frederic; Blue, Elizabeth; Muzny, Donna; Kircher, Martin; Bilguvar, Kaya; López-Giráldez, Francesc; Sutton, V. Reid; Tabor, Holly K.; Leal, Suzanne M.; Gunel, Murat; Mane, Shrikant; Gibbs, Richard A.; Boerwinkle, Eric; Hamosh, Ada; Shendure, Jay; Lupski, James R.; Lifton, Richard P.; Valle, David; Nickerson, Deborah A.; Bamshad, Michael J.

2015-01-01

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families. PMID:26166479

Modeling Protein Excited-state Structures from "Over-length" Chemical Cross-links.

PubMed

Ding, Yue-He; Gong, Zhou; Dong, Xu; Liu, Kan; Liu, Zhu; Liu, Chao; He, Si-Min; Dong, Meng-Qiu; Tang, Chun

2017-01-27

Chemical cross-linking coupled with mass spectroscopy (CXMS) provides proximity information for the cross-linked residues and is used increasingly for modeling protein structures. However, experimentally identified cross-links are sometimes incompatible with the known structure of a protein, as the distance calculated between the cross-linked residues far exceeds the maximum length of the cross-linker. The discrepancies may persist even after eliminating potentially false cross-links and excluding intermolecular ones. Thus the "over-length" cross-links may arise from alternative excited-state conformation of the protein. Here we present a method and associated software DynaXL for visualizing the ensemble structures of multidomain proteins based on intramolecular cross-links identified by mass spectrometry with high confidence. Representing the cross-linkers and cross-linking reactions explicitly, we show that the protein excited-state structure can be modeled with as few as two over-length cross-links. We demonstrate the generality of our method with three systems: calmodulin, enzyme I, and glutamine-binding protein, and we show that these proteins alternate between different conformations for interacting with other proteins and ligands. Taken together, the over-length chemical cross-links contain valuable information about protein dynamics, and our findings here illustrate the relationship between dynamic domain movement and protein function. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Limited Phylogeographic Signal in Sex-Linked and Autosomal Loci Despite Geographically, Ecologically, and Phenotypically Concordant Structure of mtDNA Variation in the Holarctic Avian Genus Eremophila

PubMed Central

Drovetski, Sergei V.; Raković, Marko; Semenov, Georgy; Fadeev, Igor V.; Red’kin, Yaroslav A.

2014-01-01

Phylogeographic studies of Holarctic birds are challenging because they involve vast geographic scale, complex glacial history, extensive phenotypic variation, and heterogeneous taxonomic treatment across countries, all of which require large sample sizes. Knowledge about the quality of phylogeographic information provided by different loci is crucial for study design. We use sequences of one mtDNA gene, one sex-linked intron, and one autosomal intron to elucidate large scale phylogeographic patterns in the Holarctic lark genus Eremophila. The mtDNA ND2 gene identified six geographically, ecologically, and phenotypically concordant clades in the Palearctic that diverged in the Early - Middle Pleistocene and suggested paraphyly of the horned lark (E. alpestris) with respect to the Temminck's lark (E. bilopha). In the Nearctic, ND2 identified five subclades which diverged in the Late Pleistocene. They overlapped geographically and were not concordant phenotypically or ecologically. Nuclear alleles provided little information on geographic structuring of genetic variation in horned larks beyond supporting the monophyly of Eremophila and paraphyly of the horned lark. Multilocus species trees based on two nuclear or all three loci provided poor support for haplogroups identified by mtDNA. The node ages calculated using mtDNA were consistent with the available paleontological data, whereas individual nuclear loci and multilocus species trees appeared to underestimate node ages. We argue that mtDNA is capable of discovering independent evolutionary units within avian taxa and can provide a reasonable phylogeographic hypothesis when geographic scale, geologic history, and phenotypic variation in the study system are too complex for proposing reasonable a priori hypotheses required for multilocus methods. Finally, we suggest splitting the currently recognized horned lark into five Palearctic and one Nearctic species. PMID:24498139

Plant Phenotyping using Probabilistic Topic Models: Uncovering the Hyperspectral Language of Plants

PubMed Central

Wahabzada, Mirwaes; Mahlein, Anne-Katrin; Bauckhage, Christian; Steiner, Ulrike; Oerke, Erich-Christian; Kersting, Kristian

2016-01-01

Modern phenotyping and plant disease detection methods, based on optical sensors and information technology, provide promising approaches to plant research and precision farming. In particular, hyperspectral imaging have been found to reveal physiological and structural characteristics in plants and to allow for tracking physiological dynamics due to environmental effects. In this work, we present an approach to plant phenotyping that integrates non-invasive sensors, computer vision, as well as data mining techniques and allows for monitoring how plants respond to stress. To uncover latent hyperspectral characteristics of diseased plants reliably and in an easy-to-understand way, we “wordify” the hyperspectral images, i.e., we turn the images into a corpus of text documents. Then, we apply probabilistic topic models, a well-established natural language processing technique that identifies content and topics of documents. Based on recent regularized topic models, we demonstrate that one can track automatically the development of three foliar diseases of barley. We also present a visualization of the topics that provides plant scientists an intuitive tool for hyperspectral imaging. In short, our analysis and visualization of characteristic topics found during symptom development and disease progress reveal the hyperspectral language of plant diseases. PMID:26957018

PhenoTips: patient phenotyping software for clinical and research use.

PubMed

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

2013-08-01

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

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

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.

Sheep models of polycystic ovary syndrome phenotype

PubMed Central

Veiga-Lopez, Almudena

2012-01-01

Polycystic ovary syndrome (PCOS) is a fertility disorder affecting 5–7% of reproductive-aged women. Women with PCOS manifest both reproductive and metabolic defects. Several animal models have evolved, which implicate excess steroid exposure during fetal life in the development of the PCOS phenotype. This review addresses the fetal and adult reproductive and metabolic consequences of prenatal steroid excess in sheep and the translational relevance of these findings to PCOS. By comparing findings in various breeds of sheep, the review targets the role of genetic susceptibility to fetal insults. Disruptions induced by prenatal testosterone excess are evident at both the reproductive and metabolic level with each influencing the other thus creating a self-perpetuating vicious cycle. The review highlights the need for identifying a common mediator of the dysfunctions at the reproductive and metabolic levels and developing prevention and treatment interventions targeting all sites of disruption in unison for achieving optimal success. PMID:23084976

Taxonomically-linked growth phenotypes during arsenic stress among arsenic resistant bacteria isolated from soils overlying the Centralia coal seam fire.

PubMed

Dunivin, Taylor K; Miller, Justine; Shade, Ashley

2018-01-01

Arsenic (As), a toxic element, has impacted life since early Earth. Thus, microorganisms have evolved many As resistance and tolerance mechanisms to improve their survival outcomes given As exposure. We isolated As resistant bacteria from Centralia, PA, the site of an underground coal seam fire that has been burning since 1962. From a 57.4°C soil collected from a vent above the fire, we isolated 25 unique aerobic As resistant bacterial strains spanning seven genera. We examined their diversity, resistance gene content, transformation abilities, inhibitory concentrations, and growth phenotypes. Although As concentrations were low at the time of soil collection (2.58 ppm), isolates had high minimum inhibitory concentrations (MICs) of arsenate and arsenite (>300 mM and 20 mM respectively), and most isolates were capable of arsenate reduction. We screened isolates (PCR and sequencing) using 12 published primer sets for six As resistance genes (AsRGs). Genes encoding arsenate reductase (arsC) and arsenite efflux pumps (arsB, ACR3(2)) were present, and phylogenetic incongruence between 16S rRNA genes and AsRGs provided evidence for horizontal gene transfer. A detailed investigation of differences in isolate growth phenotypes across As concentrations (lag time to exponential growth, maximum growth rate, and maximum OD590) showed a relationship with taxonomy, providing information that could help to predict an isolate's performance given As exposure in situ. Our results suggest that microbiological management and remediation of environmental As could be informed by taxonomically-linked As tolerance, potential for resistance gene transferability, and the rare biosphere.

Taxonomically-linked growth phenotypes during arsenic stress among arsenic resistant bacteria isolated from soils overlying the Centralia coal seam fire

PubMed Central

Dunivin, Taylor K.; Miller, Justine

2018-01-01

Arsenic (As), a toxic element, has impacted life since early Earth. Thus, microorganisms have evolved many As resistance and tolerance mechanisms to improve their survival outcomes given As exposure. We isolated As resistant bacteria from Centralia, PA, the site of an underground coal seam fire that has been burning since 1962. From a 57.4°C soil collected from a vent above the fire, we isolated 25 unique aerobic As resistant bacterial strains spanning seven genera. We examined their diversity, resistance gene content, transformation abilities, inhibitory concentrations, and growth phenotypes. Although As concentrations were low at the time of soil collection (2.58 ppm), isolates had high minimum inhibitory concentrations (MICs) of arsenate and arsenite (>300 mM and 20 mM respectively), and most isolates were capable of arsenate reduction. We screened isolates (PCR and sequencing) using 12 published primer sets for six As resistance genes (AsRGs). Genes encoding arsenate reductase (arsC) and arsenite efflux pumps (arsB, ACR3(2)) were present, and phylogenetic incongruence between 16S rRNA genes and AsRGs provided evidence for horizontal gene transfer. A detailed investigation of differences in isolate growth phenotypes across As concentrations (lag time to exponential growth, maximum growth rate, and maximum OD590) showed a relationship with taxonomy, providing information that could help to predict an isolate’s performance given As exposure in situ. Our results suggest that microbiological management and remediation of environmental As could be informed by taxonomically-linked As tolerance, potential for resistance gene transferability, and the rare biosphere. PMID:29370270

A Bayesian model for estimating population means using a link-tracing sampling design.

PubMed

St Clair, Katherine; O'Connell, Daniel

2012-03-01

Link-tracing sampling designs can be used to study human populations that contain "hidden" groups who tend to be linked together by a common social trait. These links can be used to increase the sampling intensity of a hidden domain by tracing links from individuals selected in an initial wave of sampling to additional domain members. Chow and Thompson (2003, Survey Methodology 29, 197-205) derived a Bayesian model to estimate the size or proportion of individuals in the hidden population for certain link-tracing designs. We propose an addition to their model that will allow for the modeling of a quantitative response. We assess properties of our model using a constructed population and a real population of at-risk individuals, both of which contain two domains of hidden and nonhidden individuals. Our results show that our model can produce good point and interval estimates of the population mean and domain means when our population assumptions are satisfied. © 2011, The International Biometric Society.

Obstructive Sleep Apnea Syndrome: From Phenotype to Genetic Basis

PubMed Central

Casale, M; Pappacena, M; Rinaldi, V; Bressi, F; Baptista, P; Salvinelli, F

2009-01-01

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity. PMID:19794884

Improving Power System Modeling. A Tool to Link Capacity Expansion and Production Cost Models

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

Diakov, Victor; Cole, Wesley; Sullivan, Patrick

2015-11-01

Capacity expansion models (CEM) provide a high-level long-term view at the prospects of the evolving power system. In simulating the possibilities of long-term capacity expansion, it is important to maintain the viability of power system operation in the short-term (daily, hourly and sub-hourly) scales. Production-cost models (PCM) simulate routine power system operation on these shorter time scales using detailed load, transmission and generation fleet data by minimizing production costs and following reliability requirements. When based on CEM 'predictions' about generating unit retirements and buildup, PCM provide more detailed simulation for the short-term system operation and, consequently, may confirm the validitymore » of capacity expansion predictions. Further, production cost model simulations of a system that is based on capacity expansion model solution are 'evolutionary' sound: the generator mix is the result of logical sequence of unit retirement and buildup resulting from policy and incentives. The above has motivated us to bridge CEM with PCM by building a capacity expansion - to - production cost model Linking Tool (CEPCoLT). The Linking Tool is built to onset capacity expansion model prescriptions onto production cost model inputs. NREL's ReEDS and Energy Examplar's PLEXOS are the capacity expansion and the production cost models, respectively. Via the Linking Tool, PLEXOS provides details of operation for the regionally-defined ReEDS scenarios.« less

Measures for interoperability of phenotypic data: minimum information requirements and formatting.

PubMed

Ćwiek-Kupczyńska, Hanna; Altmann, Thomas; Arend, Daniel; Arnaud, Elizabeth; Chen, Dijun; Cornut, Guillaume; Fiorani, Fabio; Frohmberg, Wojciech; Junker, Astrid; Klukas, Christian; Lange, Matthias; Mazurek, Cezary; Nafissi, Anahita; Neveu, Pascal; van Oeveren, Jan; Pommier, Cyril; Poorter, Hendrik; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Scholz, Uwe; van Schriek, Marco; Seren, Ümit; Usadel, Björn; Weise, Stephan; Kersey, Paul; Krajewski, Paweł

2016-01-01

Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

Towards a reference plant trait ontology for modeling knowledge of plant traits and phenotypes

USDA-ARS?s Scientific Manuscript database

Ontology engineering and knowledge modeling for the plant sciences is expected to contribute to the understanding of the basis of plant traits that determine phenotypic expression in a given environment. Several crop- or clade-specific plant trait ontologies have been developed to describe plant tr...

Disease phenotype of a ferret CFTR-knockout model of cystic fibrosis

PubMed Central

Sun, Xingshen; Sui, Hongshu; Fisher, John T.; Yan, Ziying; Liu, Xiaoming; Cho, Hyung-Ju; Joo, Nam Soo; Zhang, Yulong; Zhou, Weihong; Yi, Yaling; Kinyon, Joann M.; Lei-Butters, Diana C.; Griffin, Michelle A.; Naumann, Paul; Luo, Meihui; Ascher, Jill; Wang, Kai; Frana, Timothy; Wine, Jeffrey J.; Meyerholz, David K.; Engelhardt, John F.

2010-01-01

Cystic fibrosis (CF) is a recessive disease that affects multiple organs. It is caused by mutations in CFTR. Animal modeling of this disease has been challenging, with species- and strain-specific differences in organ biology and CFTR function influencing the emergence of disease pathology. Here, we report the phenotype of a CFTR-knockout ferret model of CF. Neonatal CFTR-knockout ferrets demonstrated many of the characteristics of human CF disease, including defective airway chloride transport and submucosal gland fluid secretion; variably penetrant meconium ileus (MI); pancreatic, liver, and vas deferens disease; and a predisposition to lung infection in the early postnatal period. Severe malabsorption by the gastrointestinal (GI) tract was the primary cause of death in CFTR-knockout kits that escaped MI. Elevated liver function tests in CFTR-knockout kits were corrected by oral administration of ursodeoxycholic acid, and the addition of an oral proton-pump inhibitor improved weight gain and survival. To overcome the limitations imposed by the severe intestinal phenotype, we cloned 4 gut-corrected transgenic CFTR-knockout kits that expressed ferret CFTR specifically in the intestine. One clone passed feces normally and demonstrated no detectable ferret CFTR expression in the lung or liver. The animals described in this study are likely to be useful tools for dissecting CF disease pathogenesis and developing treatments. PMID:20739752

Disease phenotype of a ferret CFTR-knockout model of cystic fibrosis.

PubMed

Sun, Xingshen; Sui, Hongshu; Fisher, John T; Yan, Ziying; Liu, Xiaoming; Cho, Hyung-Ju; Joo, Nam Soo; Zhang, Yulong; Zhou, Weihong; Yi, Yaling; Kinyon, Joann M; Lei-Butters, Diana C; Griffin, Michelle A; Naumann, Paul; Luo, Meihui; Ascher, Jill; Wang, Kai; Frana, Timothy; Wine, Jeffrey J; Meyerholz, David K; Engelhardt, John F

2010-09-01

Cystic fibrosis (CF) is a recessive disease that affects multiple organs. It is caused by mutations in CFTR. Animal modeling of this disease has been challenging, with species- and strain-specific differences in organ biology and CFTR function influencing the emergence of disease pathology. Here, we report the phenotype of a CFTR-knockout ferret model of CF. Neonatal CFTR-knockout ferrets demonstrated many of the characteristics of human CF disease, including defective airway chloride transport and submucosal gland fluid secretion; variably penetrant meconium ileus (MI); pancreatic, liver, and vas deferens disease; and a predisposition to lung infection in the early postnatal period. Severe malabsorption by the gastrointestinal (GI) tract was the primary cause of death in CFTR-knockout kits that escaped MI. Elevated liver function tests in CFTR-knockout kits were corrected by oral administration of ursodeoxycholic acid, and the addition of an oral proton-pump inhibitor improved weight gain and survival. To overcome the limitations imposed by the severe intestinal phenotype, we cloned 4 gut-corrected transgenic CFTR-knockout kits that expressed ferret CFTR specifically in the intestine. One clone passed feces normally and demonstrated no detectable ferret CFTR expression in the lung or liver. The animals described in this study are likely to be useful tools for dissecting CF disease pathogenesis and developing treatments.

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients.

PubMed

Ibrahim, El Chérif; Guillemot, Vincent; Comte, Magali; Tenenhaus, Arthur; Zendjidjian, Xavier Yves; Cancel, Aida; Belzeaux, Raoul; Sauvanaud, Florence; Blin, Olivier; Frouin, Vincent; Fakra, Eric

2017-09-07

Hundreds of genetic loci participate to schizophrenia liability. It is also known that impaired cerebral connectivity is directly related to the cognitive and affective disturbances in schizophrenia. How genetic susceptibility and brain neural networks interact to specify a pathological phenotype in schizophrenia remains elusive. Imaging genetics, highlighting brain variations, has proven effective to establish links between vulnerability loci and associated clinical traits. As previous imaging genetics works in schizophrenia have essentially focused on structural DNA variants, these findings could be blurred by epigenetic mechanisms taking place during gene expression. We explored the meaningful links between genetic data from peripheral blood tissues on one hand, and regional brain reactivity to emotion task assayed by blood oxygen level-dependent functional magnetic resonance imaging on the other hand, in schizophrenia patients and matched healthy volunteers. We applied Sparse Generalized Canonical Correlation Analysis to identify joint signals between two blocks of variables: (i) the transcriptional expression of 33 candidate genes, and (ii) the blood oxygen level-dependent activity in 16 region of interest. Results suggested that peripheral transcriptional expression is related to brain imaging variations through a sequential pathway, ending with the schizophrenia phenotype. Generalization of such an approach to larger data sets should thus help in outlining the pathways involved in psychiatric illnesses such as schizophrenia. SEARCHING FOR LINKS TO AID DIAGNOSIS: Researchers explore links between the expression of genes associated with schizophrenia in blood cells and variations in brain activity during emotion processing. El Chérif Ibrahim and Eric Fakra at Aix-Marseille Université, France, and colleagues have developed a method to relate the expression levels of 33 schizophrenia susceptibility genes in blood cells and functional magnetic resonance imaging

Linking knowledge and action through mental models of sustainable agriculture

PubMed Central

Hoffman, Matthew; Lubell, Mark; Hillis, Vicken

2014-01-01

Linking knowledge to action requires understanding how decision-makers conceptualize sustainability. This paper empirically analyzes farmer “mental models” of sustainability from three winegrape-growing regions of California where local extension programs have focused on sustainable agriculture. The mental models are represented as networks where sustainability concepts are nodes, and links are established when a farmer mentions two concepts in their stated definition of sustainability. The results suggest that winegrape grower mental models of sustainability are hierarchically structured, relatively similar across regions, and strongly linked to participation in extension programs and adoption of sustainable farm practices. We discuss the implications of our findings for the debate over the meaning of sustainability, and the role of local extension programs in managing knowledge systems. PMID:25157158

Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

DOE PAGES

Sánchez, Benjamín J.; Zhang, Cheng; Nilsson, Avlant; ...

2017-03-08

Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We appliedmore » GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.« less

Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

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

Sánchez, Benjamín J.; Zhang, Cheng; Nilsson, Avlant

Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We appliedmore » GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.« less

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

PubMed

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

2018-05-04

Researchers are developing methods to automatically extract clinically relevant and useful patient characteristics from raw healthcare datasets. These characteristics, often capturing essential properties of patients with common medical conditions, are called computational phenotypes. Being generated by automated or semiautomated, data-driven methods, such potential phenotypes need to be validated as clinically meaningful (or not) before they are acceptable for use in decision making. The objective of this study was to present Phenotype Instance Verification and Evaluation Tool (PIVET), a framework that uses co-occurrence analysis on an online corpus of publically available medical journal articles to build clinical relevance evidence sets for user-supplied phenotypes. PIVET adopts a conceptual framework similar to the pioneering prototype tool PheKnow-Cloud that was developed for the phenotype validation task. PIVET completely refactors each part of the PheKnow-Cloud pipeline to deliver vast improvements in speed without sacrificing the quality of the insights PheKnow-Cloud achieved. PIVET leverages indexing in NoSQL databases to efficiently generate evidence sets. Specifically, PIVET uses a succinct representation of the phenotypes that corresponds to the index on the corpus database and an optimized co-occurrence algorithm inspired by the Aho-Corasick algorithm. We compare PIVET's phenotype representation with PheKnow-Cloud's by using PheKnow-Cloud's experimental setup. In PIVET's framework, we also introduce a statistical model trained on domain expert-verified phenotypes to automatically classify phenotypes as clinically relevant or not. Additionally, we show how the classification model can be used to examine user-supplied phenotypes in an online, rather than batch, manner. PIVET maintains the discriminative power of PheKnow-Cloud in terms of identifying clinically relevant phenotypes for the same corpus with which PheKnow-Cloud was originally developed, but

Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

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

Murphy, Cheryl; Nisbet, Roger; Antczak, Philipp

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) thatmore » link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

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

Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype

DOE PAGES

Patti, Gary J.; Tautenhahn, Ralf; Fonslow, Bryan R.; ...

2011-01-01

Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiplemore » pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.« less

Genetic and Phenotypic Characterization of a Salmonella enterica serovar Enteritidis Emerging Strain with Superior Intra-macrophage Replication Phenotype

PubMed Central

Shomer, Inna; Avisar, Alon; Desai, Prerak; Azriel, Shalhevet; Smollan, Gill; Belausov, Natasha; Keller, Nathan; Glikman, Daniel; Maor, Yasmin; Peretz, Avi; McClelland, Michael; Rahav, Galia; Gal-Mor, Ohad

2016-01-01

Salmonella enterica serovar Enteritidis (S. Enteritidis) is one of the ubiquitous Salmonella serovars worldwide and a major cause of food-born outbreaks, which are often associated with poultry and poultry derivatives. Here we report a nation-wide S. Enteritidis clonal outbreak that occurred in Israel during the last third of 2015. Pulsed field gel electrophoresis and whole genome sequencing identified genetically related strains that were circulating in Israel as early as 2008. Global comparison linked this outbreak strain to several clinical and marine environmental isolates that were previously isolated in California and Canada, indicating that similar strains are prevalent outside of Israel. Phenotypic comparison between the 2015 outbreak strain and other clinical and reference S. Enteritidis strains showed only limited intra-serovar phenotypic variation in growth in rich medium, invasion into Caco-2 cells, uptake by J774.1A macrophages, and host cell cytotoxicity. In contrast, significant phenotypic variation was shown among different S. Enteritidis isolates when biofilm-formation, motility, invasion into HeLa cells and uptake by THP-1 human macrophages were studied. Interestingly, the 2015 outbreak clone was found to possess superior intra-macrophage replication ability within both murine and human macrophages in comparison to the other S. Enteritidis strains studied. This phenotype is likely to play a role in the virulence and host-pathogen interactions of this emerging clone. PMID:27695450

Ordinal probability effect measures for group comparisons in multinomial cumulative link models.

PubMed

Agresti, Alan; Kateri, Maria

2017-03-01

We consider simple ordinal model-based probability effect measures for comparing distributions of two groups, adjusted for explanatory variables. An "ordinal superiority" measure summarizes the probability that an observation from one distribution falls above an independent observation from the other distribution, adjusted for explanatory variables in a model. The measure applies directly to normal linear models and to a normal latent variable model for ordinal response variables. It equals Φ(β/2) for the corresponding ordinal model that applies a probit link function to cumulative multinomial probabilities, for standard normal cdf Φ and effect β that is the coefficient of the group indicator variable. For the more general latent variable model for ordinal responses that corresponds to a linear model with other possible error distributions and corresponding link functions for cumulative multinomial probabilities, the ordinal superiority measure equals exp(β)/[1+exp(β)] with the log-log link and equals approximately exp(β/2)/[1+exp(β/2)] with the logit link, where β is the group effect. Another ordinal superiority measure generalizes the difference of proportions from binary to ordinal responses. We also present related measures directly for ordinal models for the observed response that need not assume corresponding latent response models. We present confidence intervals for the measures and illustrate with an example. © 2016, The International Biometric Society.

Obesity and Asthma: A Missing Link.

PubMed

Gomez-Llorente, Mª Amelia; Romero, Raquel; Chueca, Natalia; Martinez-Cañavate, Ana; Gomez-Llorente, Carolina

2017-07-11

Obesity and asthma are two chronic conditions that affect millions of people. Genetic and lifestyle factors such as diet, physical activity, and early exposure to micro-organisms are important factors that may contribute to the escalating prevalence of both conditions. The prevalence of asthma is higher in obese individuals. Recently, two major phenotypes of asthma with obesity have been described: one phenotype of early-onset asthma that is aggravated by obesity, and a second phenotype of later-onset asthma that predominantly affects women. Systemic inflammation and mechanical effect, both due to the expansion of the adipose tissue, have been proposed as the main reasons for the association between obesity and asthma. However, the mechanisms involved are not yet fully understood. Moreover, it has also been suggested that insulin resistance syndrome can have a role in the association between these conditions. The intestinal microbiota is an important factor in the development of the immune system, and can be considered a link between obesity and asthma. In the obese state, higher lipopolysaccharide (LPS) serum levels as a consequence of a microbiota dysbiosis have been found. In addition, changes in microbiota composition result in a modification of carbohydrate fermentation capacity, therefore modifying short chain fatty acid (SCFA) levels. The main objective of this review is to summarize the principal findings that link obesity and asthma.

Obesity and Asthma: A Missing Link

PubMed Central

Gomez-Llorente, Mª Amelia; Romero, Raquel; Chueca, Natalia; Martinez-Cañavate, Ana

2017-01-01

Obesity and asthma are two chronic conditions that affect millions of people. Genetic and lifestyle factors such as diet, physical activity, and early exposure to micro-organisms are important factors that may contribute to the escalating prevalence of both conditions. The prevalence of asthma is higher in obese individuals. Recently, two major phenotypes of asthma with obesity have been described: one phenotype of early-onset asthma that is aggravated by obesity, and a second phenotype of later-onset asthma that predominantly affects women. Systemic inflammation and mechanical effect, both due to the expansion of the adipose tissue, have been proposed as the main reasons for the association between obesity and asthma. However, the mechanisms involved are not yet fully understood. Moreover, it has also been suggested that insulin resistance syndrome can have a role in the association between these conditions. The intestinal microbiota is an important factor in the development of the immune system, and can be considered a link between obesity and asthma. In the obese state, higher lipopolysaccharide (LPS) serum levels as a consequence of a microbiota dysbiosis have been found. In addition, changes in microbiota composition result in a modification of carbohydrate fermentation capacity, therefore modifying short chain fatty acid (SCFA) levels. The main objective of this review is to summarize the principal findings that link obesity and asthma. PMID:28696379

Shuttle Communications and Tracking Systems Modeling and TDRSS Link Simulations Studies

NASA Technical Reports Server (NTRS)

Chie, C. M.; Dessouky, K.; Lindsey, W. C.; Tsang, C. S.; Su, Y. T.

1985-01-01

An analytical simulation package (LinCsim) which allows the analytical verification of data transmission performance through TDRSS satellites was modified. The work involved the modeling of the user transponder, TDRS, TDRS ground terminal, and link dynamics for forward and return links based on the TDRSS performance specifications (4) and the critical design reviews. The scope of this effort has recently been expanded to include the effects of radio frequency interference (RFI) on the bit error rate (BER) performance of the S-band return links. The RFI environment and the modified TDRSS satellite and ground station hardware are being modeled in accordance with their description in the applicable documents.

Decomposing phenotype descriptions for the human skeletal phenome.

PubMed

Groza, Tudor; Hunter, Jane; Zankl, Andreas

2013-01-01

Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. The intrinsic value and knowledge captured within such descriptions can only be expressed by taking advantage of their inner structure that implicitly combines qualities and anatomical entities. We present a meta-model (the Phenotype Fragment Ontology) and a processing pipeline that enable together the automatic decomposition and conceptualization of phenotype descriptions for the human skeletal phenome. We use this approach to showcase the usefulness of the generic concept of phenotype decomposition by performing an experimental study on all skeletal phenotype concepts defined in the Human Phenotype Ontology.

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

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Diverse Application of Magnetic Resonance Imaging for Mouse Phenotyping

PubMed Central

Wu, Yijen L.; Lo, Cecilia W.

2017-01-01

Small animal models, particularly mouse models, of human diseases are becoming an indispensable tool for biomedical research. Studies in animal models have provided important insights into the etiology of diseases and accelerated the development of therapeutic strategies. Detailed phenotypic characterization is essential, both for the development of such animal models and mechanistic studies into disease pathogenesis and testing the efficacy of experimental therapeutics. Magnetic Resonance Imaging (MRI) is a versatile and non-invasive imaging modality with excellent penetration depth, tissue coverage, and soft tissue contrast. MRI, being a multi-modal imaging modality, together with proven imaging protocols and availability of good contrast agents, is ideally suited for phenotyping mutant mouse models. Here we describe the applications of MRI for phenotyping structural birth defects involving the brain, heart, and kidney in mice. The versatility of MRI and its ease of use are well suited to meet the rapidly increasing demands for mouse phenotyping in the coming age of functional genomics. PMID:28544650

Towards recommendations for metadata and data handling in plant phenotyping.

PubMed

Krajewski, Paweł; Chen, Dijun; Ćwiek, Hanna; van Dijk, Aalt D J; Fiorani, Fabio; Kersey, Paul; Klukas, Christian; Lange, Matthias; Markiewicz, Augustyn; Nap, Jan Peter; van Oeveren, Jan; Pommier, Cyril; Scholz, Uwe; van Schriek, Marco; Usadel, Björn; Weise, Stephan

2015-09-01

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The effects of graded levels of calorie restriction: IV. Non-linear change in behavioural phenotype of mice in response to short-term calorie restriction.

PubMed

Lusseau, David; Mitchell, Sharon E; Barros, Ceres; Derous, Davina; Green, Cara; Chen, Luonan; Han, Jing-Dong Jackie; Wang, Yingchun; Promislow, Daniel E L; Douglas, Alex; Speakman, John R

2015-08-25

Animals have to adjust their activities when faced with caloric restriction (CR) to deal with reduced energy intake. If CR is pronounced, allostasis can push individuals into alternate physiological states which can result in important health benefits across a wide range of taxa. Here we developed a new approach to determine the changes in behavioural phenotype associated with different levels of CR. We exposed C57BL/6 male mice to graded CR (from 0 to 40%) for three months and defined their behavioural phenotype using hidden Markov models of their movement and body temperature. All 40% CR mice exhibited a state-shift in behavioural phenotype and only some exposed to 30% CR did. We show for the first time that mice changed their activity characteristics rather than changed their activities. This new phenotyping approach provides an avenue to determine the mechanisms linking CR to healthspan.

Skin phenotypes can offer some insight about the association between telomere length and cancer susceptibility.

PubMed

Ribero, S; Mangino, M; Bataille, V

2016-12-01

The role of telomere biology in cancer has been studied for a wide variety of different cancers but the association with telomere length has been controversial. This is because some cancers have been found to be associated with longer telomeres in circulating white cells whilst other cancer types are more common in individuals with shorter telomeres. Hence, there has been some skepticism as to whether telomere length may be helpful in estimating cancer risk. For melanoma, however, results have been fairly consistent showing that longer telomeres are associated with an increased risk. This link was first discovered because of a link between longer telomeres and a high number of naevi. In contrast, for cutaneous squamous cell carcinomas, the relationship is reversed with higher risk in individuals with shorter telomeres. Differences in skin phenotypes with the presence of high number of naevi versus photoageing with solar elastosis and solar keratoses have already been valuable for dermatologists as the former phenotype is associated with melanoma whilst the latter is more common in patients with squamous cell carcinoma of the skin. The hypothesis is that the differences in cutaneous phenotypes already observed by dermatologists for skin cancers may, in fact, be useful as well for cancer prediction in general as it may reflect underlying telomere biology. This manuscript will address the evidence for links between telomere biology, skin phenotypes and cancer risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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

PubMed

Niu, Yuanling; Wang, Yue; Zhou, Da

2015-12-07

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

Conceptual framework for drought phenotyping during molecular breeding.

PubMed

Salekdeh, Ghasem Hosseini; Reynolds, Matthew; Bennett, John; Boyer, John

2009-09-01

Drought is a major threat to agricultural production and drought tolerance is a prime target for molecular approaches to crop improvement. To achieve meaningful results, these approaches must be linked with suitable phenotyping protocols at all stages, such as the screening of germplasm collections, mutant libraries, mapping populations, transgenic lines and breeding materials and the design of OMICS and quantitative trait loci (QTLs) experiments. Here we present a conceptual framework for molecular breeding for drought tolerance based on the Passioura equation of expressing yield as the product of water use (WU), water use efficiency (WUE) and harvest index (HI). We identify phenotyping protocols that address each of these factors, describe their key features and illustrate their integration with different molecular approaches.

Modeling and control of a hydraulically actuated flexible-prismatic link robot

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

Love, L.; Kress, R.; Jansen, J.

1996-12-01

Most of the research related to flexible link manipulators to date has focused on single link, fixed length, single plane of vibration test beds. In addition, actuation has been predominantly based upon electromagnetic motors. Ironically, these elements are rarely found in the existing industrial long reach systems. This manuscript describes a new hydraulically actuated, long reach manipulator with a flexible prismatic link at Oak Ridge National Laboratory (ORNL). Focus is directed towards both modeling and control of hydraulic actuators as well as flexible links that have variable natural frequencies.

O-Linked β-N-Acetylglucosaminylation (O-GlcNAcylation) in Primary and Metastatic Colorectal Cancer Clones and Effect of N-Acetyl-β-d-glucosaminidase Silencing on Cell Phenotype and Transcriptome*

PubMed Central

Yehezkel, Galit; Cohen, Liz; Kliger, Adi; Manor, Esther; Khalaila, Isam

2012-01-01

O-Linked β-N-acetylglucosamine (O-GlcNAc) glycosylation is a regulatory post-translational modification occurring on the serine or threonine residues of nucleocytoplasmic proteins. O-GlcNAcylation is dynamically regulated by O-GlcNAc transferase and O-GlcNAcase (OGA), which are responsible for O-GlcNAc addition and removal, respectively. Although O-GlcNAcylation was found to play a significant role in several pathologies such as type II diabetes and neurodegenerative diseases, the role of O-GlcNAcylation in the etiology and progression of cancer remains vague. Here, we followed O-GlcNAcylation and its catalytic machinery in metastatic clones of human colorectal cancer and the effect of OGA knockdown on cellular phenotype and on the transcriptome. The colorectal cancer SW620 metastatic clone exhibited increased O-GlcNAcylation and decreased OGA expression compared with its primary clone, SW480. O-GlcNAcylation elevation in SW620 cells, through RNA interference of OGA, resulted in phenotypic alterations that included acquisition of a fibroblast-like morphology, which coincides with epithelial metastatic progression and growth retardation. Microarray analysis revealed that OGA silencing altered the expression of about 1300 genes, mostly involved in cell movement and growth, and specifically affected metabolic pathways of lipids and carbohydrates. These findings support the involvement of O-GlcNAcylation in various aspects of tumor cell physiology and suggest that this modification may serve as a link between metabolic changes and cancer. PMID:22730328

Taste phenotype associates with cardiovascular disease risk factors via diet quality in multivariate modeling.

PubMed

Sharafi, Mastaneh; Rawal, Shristi; Fernandez, Maria Luz; Huedo-Medina, Tania B; Duffy, Valerie B

2018-05-08

Sensations from foods and beverages drive dietary choices, which in turn, affect risk of diet-related diseases. Perception of these sensation varies with environmental and genetic influences. This observational study aimed to examine associations between chemosensory phenotype, diet and cardiovascular disease (CVD) risk. Reportedly healthy women (n = 110, average age 45 ± 9 years) participated in laboratory-based measures of chemosensory phenotype (taste and smell function, propylthiouracil (PROP) bitterness) and CVD risk factors (waist circumference, blood pressure, serum lipids). Diet variables included preference and intake of sweet/high-fat foods, dietary restraint, and diet quality based on reported preference (Healthy Eating Preference Index-HEPI) and intake (Healthy Eating Index-HEI). We found that females who reported high preference yet low consumption of sweet/high-fat foods had the highest dietary restraint and depressed quinine taste function. PROP nontasters were more likely to report lower diet quality; PROP supertasters more likely to consume but not like a healthy diet. Multivariate structural models were fitted to identify predictors of CVD risk factors. Reliable latent taste (quinine taste function, PROP tasting) and smell (odor intensity) variables were identified, with taste explaining more variance in the CVD risk factors. Lower bitter taste perception was associated with elevated risk. In multivariate models, the HEPI completely mediated the taste-adiposity and taste-HDL associations and partially mediated the taste-triglyceride or taste-systolic blood pressure associations. The taste-LDL pathway was significant and direct. The HEI could not replace HEPI in adequate models. However, using a latent diet quality variable with HEPI and HEI, increased the strength of association between diet quality and adiposity or CVD risk factors. In conclusion, bitter taste phenotype was associated with CVD risk factors via diet quality

Phenotypic plasticity with instantaneous but delayed switches.

PubMed

Utz, Margarete; Jeschke, Jonathan M; Loeschcke, Volker; Gabriel, Wilfried

2014-01-07

Phenotypic plasticity is a widespread phenomenon, allowing organisms to better adapt to changing environments. Most empirical and theoretical studies are restricted to irreversible plasticity where the expression of a specific phenotype is mostly determined during development. However, reversible plasticity is not uncommon; here, organisms are able to switch back and forth between phenotypes. We present two optimization models for the fitness of (i) non-plastic, (ii) irreversibly plastic, and (iii) reversibly plastic genotypes in a fluctuating environment. In one model, the fitness values of an organism during different life phases act together multiplicatively (so as to consider traits that are related to survival). The other model additionally considers additive effects (corresponding to traits related to fecundity). Both models yield qualitatively similar results. If the only costs of reversible plasticity are due to temporal maladaptation while switching between phenotypes, reversibility is virtually always advantageous over irreversibility, especially for slow environmental fluctuations. If reversibility implies an overall decreased fitness, then irreversibility is advantageous if the environment fluctuates quickly or if stress events last relatively short. Our results are supported by observations from different types of organisms and have implications for many basic and applied research questions, e.g., on invasive alien species. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

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

Obesity-Linked Mouse Models of Liver Cancer | Center for Cancer Research

Cancer.gov

Jimmy Stauffer, Ph.D., and colleagues working with Robert  Wiltrout, Ph.D., in CCR’s Cancer and Inflammation Program, along with collaborators in the Laboratory of Human Carcinogenesis, have developed a novel mouse model that demonstrates how fat-producing phenotypes can influence the development of hepatic cancer.   The team recently reported their findings in Cancer Research.

Phase Diagram of the Bose Hubbard Model with Weak Links

NASA Astrophysics Data System (ADS)

Hettiarachchilage, Kalani; Rousseau, Valy; Tam, Ka-Ming; Moreno, Juana; Jarrell, Mark; Sheehy, Daniel

2012-02-01

We study the ground state phase diagram of strongly interacting ultracold Bose gas in a one-dimensional optical lattice with a tunable weak link, by means of Quantum Monte Carlo simulation. This model contains an on-site repulsive interaction (U) and two different near-neighbor hopping terms, J and t, for the weak link and the remainder of the chain, respectively. We show that by reducing the strength of J, a novel intermediate phase develops which is compressible and non-superfluid. This novel phase is identified as a Normal Bose Liquid (NBL) which does not appear in the phase diagram of the homogeneous bosonic Hubbard model. Further, we find a linear variation of the phase boundary of Normal Bose Liquid (NBL) to SuperFluid (SF) as a function of the strength of the weak link. These results may provide a new path to design advanced atomtronic devices in the future.

Dystrophic Cardiomyopathy: Complex Pathobiological Processes to Generate Clinical Phenotype

PubMed Central

Tsuda, Takeshi; Fitzgerald, Kristi K.

2017-01-01

Duchenne muscular dystrophy (DMD), Becker muscular dystrophy (BMD), and X-linked dilated cardiomyopathy (XL-DCM) consist of a unique clinical entity, the dystrophinopathies, which are due to variable mutations in the dystrophin gene. Dilated cardiomyopathy (DCM) is a common complication of dystrophinopathies, but the onset, progression, and severity of heart disease differ among these subgroups. Extensive molecular genetic studies have been conducted to assess genotype-phenotype correlation in DMD, BMD, and XL-DCM to understand the underlying mechanisms of these diseases, but the results are not always conclusive, suggesting the involvement of complex multi-layers of pathological processes that generate the final clinical phenotype. Dystrophin protein is a part of dystrophin-glycoprotein complex (DGC) that is localized in skeletal muscles, myocardium, smooth muscles, and neuronal tissues. Diversity of cardiac phenotype in dystrophinopathies suggests multiple layers of pathogenetic mechanisms in forming dystrophic cardiomyopathy. In this review article, we review the complex molecular interactions involving the pathogenesis of dystrophic cardiomyopathy, including primary gene mutations and loss of structural integrity, secondary cellular responses, and certain epigenetic and other factors that modulate gene expressions. Involvement of epigenetic gene regulation appears to lead to specific cardiac phenotypes in dystrophic hearts. PMID:29367543

A Novel Letrozole Model Recapitulates Both the Reproductive and Metabolic Phenotypes of Polycystic Ovary Syndrome in Female Mice1

PubMed Central

Kauffman, Alexander S.; Thackray, Varykina G.; Ryan, Genevieve E.; Tolson, Kristen P.; Glidewell-Kenney, Christine A.; Semaan, Sheila J.; Poling, Matthew C.; Iwata, Nahoko; Breen, Kellie M.; Duleba, Antoni J.; Stener-Victorin, Elisabet; Shimasaki, Shunichi; Webster, Nicholas J.; Mellon, Pamela L.

2015-01-01

Polycystic ovary syndrome (PCOS) pathophysiology is poorly understood, due partly to lack of PCOS animal models fully recapitulating this complex disorder. Recently, a PCOS rat model using letrozole (LET), a nonsteroidal aromatase inhibitor, mimicked multiple PCOS phenotypes, including metabolic features absent in other models. Given the advantages of using genetic and transgenic mouse models, we investigated whether LET produces a similar PCOS phenotype in mice. Pubertal female C57BL/6N mice were treated for 5 wk with LET, which resulted in increased serum testosterone and normal diestrus levels of estradiol, similar to the hyperandrogenemia and follicular phase estrogen levels of PCOS women. As in PCOS, ovaries from LET mice were larger, polycystic, and lacked corpora lutea versus controls. Most LET females were acyclic, and all were infertile. LET females displayed elevated serum LH levels and higher Lhb mRNA in the pituitary. In contrast, serum FSH and Fshb were significantly reduced in LET females, demonstrating differential effects on gonadotropins, as in PCOS. Within the ovary, LET females had higher Cyp17, Cyp19, and Fsh receptor mRNA expression. In the hypothalamus, LET females had higher kisspeptin receptor mRNA expression but lower progesterone receptor mRNA levels. LET females also gained more weight than controls, had increased abdominal adiposity and adipocyte size, elevated adipose inflammatory mRNA levels, and impaired glucose tolerance, mirroring the metabolic phenotype in PCOS women. This is the first report of a LET paradigm in mice that recapitulates both reproductive and metabolic PCOS phenotypes and will be useful to genetically probe the PCOS condition. PMID:26203175

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders

2007-01-01

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models,…

The central nervous system phenotype of X-linked Charcot-Marie-Tooth disease: a transient disorder of children and young adults.

PubMed

Al-Mateen, Majeed; Craig, Alexa Kanwit; Chance, Phillip F

2014-03-01

We describe 2 patients with X-linked Charcot-Marie-Tooth disease, type 1 (CMTX1) disease and central nervous system manifestations and review 19 cases from the literature. Our first case had not been previously diagnosed with Charcot-Marie-Tooth disease, and the second case, although known to have Charcot-Marie-Tooth disease, was suspected of having CMTX1 after presentation with central nervous system manifestations. The most common central nervous system manifestations were transient and included dysarthria, ataxia, hemiparesis, and tetraparesis resembling periodic paralysis. Of the 21 patients, 19 presented at 21 years of age or younger, implicating CMTX1 with transient central nervous system manifestations as a disorder that predominantly affects children and adolescents. CMTX1 should be included in the differential diagnosis of patients who present with transient central nervous system phenomena, including stroke-like episodes, tetraparesis suggestive of periodic paralysis, dysarthria, ataxia, or combinations of these deficits. Reversible, bilateral, nonenhancing white matter lesions and restricted diffusion on magnetic resonance imaging are characteristic features of the central nervous system phenotype of CMTX1.

Phenotypic and genotypic data integration and exploration through a web-service architecture.

PubMed

Nuzzo, Angelo; Riva, Alberto; Bellazzi, Riccardo

2009-10-15

Linking genotypic and phenotypic information is one of the greatest challenges of current genetics research. The definition of an Information Technology infrastructure to support this kind of studies, and in particular studies aimed at the analysis of complex traits, which require the definition of multifaceted phenotypes and the integration genotypic information to discover the most prevalent diseases, is a paradigmatic goal of Biomedical Informatics. This paper describes the use of Information Technology methods and tools to develop a system for the management, inspection and integration of phenotypic and genotypic data. We present the design and architecture of the Phenotype Miner, a software system able to flexibly manage phenotypic information, and its extended functionalities to retrieve genotype information from external repositories and to relate it to phenotypic data. For this purpose we developed a module to allow customized data upload by the user and a SOAP-based communications layer to retrieve data from existing biomedical knowledge management tools. In this paper we also demonstrate the system functionality by an example application of the system in which we analyze two related genomic datasets. In this paper we show how a comprehensive, integrated and automated workbench for genotype and phenotype integration can facilitate and improve the hypothesis generation process underlying modern genetic studies.

EM Adaptive LASSO—A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes

PubMed Central

Mallick, Himel; Tiwari, Hemant K.

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice

EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

Mallick, Himel; Tiwari, Hemant K

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.

A Spatio-Temporal Model of Phenotypic Evolution in the Atlantic Silverside (Menidia menidia) and Its Implications for Size-Selective Fishing in a Warmer World

NASA Astrophysics Data System (ADS)

Sbrocco, E. J.

2016-02-01

A pervasive phenotypic pattern observed across marine fishes is that vertebral number increases with latitude. Jordan's Rule, as it is known, holds true both within and across species, and like other ecogeographic principles (e.g., Bergmann's Rule), it is presumed to be an adaptive response to latitudinal gradients in temperature. As such, future ocean warming is expected to impact not only the geographic range limits of marine fishes that conform to Jordan's Rule, but also their phenotype, with warmer waters selecting for fish with fewer vertebrae at any given latitude. Here I present a model of phenotypic evolution over space and time for the Atlantic silverside (Menidia menidia), a common marine fish found in coastal waters along the western North Atlantic. This species has long served as a model organism for the study of fisheries-induced selection and exhibits numerous latitudinal clines in phenotypic and life-history traits, including vertebral number. Common garden experiments have shown that vertebral number is genetically determined in this species, but correlative models of observed vertebral counts and climate reveal that SST is the single strongest predictor of phenotype, even after accounting for gene flow. This result indicates that natural selection is responsible for maintaining vertebral clines in the silverside, and allows for the prediction of phenotypic responses to ocean warming. By integrating genetic estimates of population connectivity, species distribution models, and statistical models, I find that by the end of the 21st century, ocean warming will select for silversides with up to 8% fewer vertebrae. Mid-Atlantic populations are the most mal-adapted for future conditions, but may be rescued by migration from small-phenotype southern neighbors or by directional selection. Despite smaller temperature anomalies, the strongest impacts of warming will be felt at both northern and southern edges of the distribution, where genetic rescue from

Living long and ageing well: is epigenomics the missing link between nature and nurture?

PubMed

Rea, Irene Maeve; Dellet, Margaret; Mills, Ken I

2016-02-01

Human longevity is a complex trait and increasingly we understand that both genes and lifestyle interact in the longevity phenotype. Non-genetic factors, including diet, physical activity, health habits, and psychosocial factors contribute approximately 50% of the variability in human lifespan with another 25% explained by genetic differences. Family clusters of nonagenarian and centenarian siblings, who show both exceptional age-span and health-span, are likely to have inherited facilitatory gene groups, but also have nine decades of life experiences and behaviours which have interacted with their genetic profiles. Identification of their shared genes is just one small step in the link from genes to their physical and psychological profiles. Behavioural genomics is beginning to demonstrate links to biological mechanisms through regulation of gene expression, which directs the proteome and influences the personal phenotype. Epigenetics has been considered the missing link between nature and nurture. Although there is much that remains to be discovered, this article will discuss some of genetic and environmental factors which appear important in good quality longevity and link known epigenetic mechanisms to themes identified by nonagenarians themselves related to their longevity. Here we suggest that exceptional 90-year old siblings have adopted a range of behaviours and life-styles which have contributed to their ageing-well-phenotype and which link with important public health messages.

The Janus-faced role of ezrin in "linking" cells to either normal or metastatic phenotype.

PubMed

Brambilla, Daria; Fais, Stefano

2009-11-15

In the majority of eukaryotic cells, the ezrin, radixin and moesin (ERM) proteins are involved in many physiologic functions including regulation of actin cytoskeleton, control of cell shape, adhesion, motility and modulation of signal transduction pathways. In a previous study, we used a dominant negative ezrin-mutant to address ezrin involvement in remodeling of actin cytoskeleton and subsequently we depicted ezrin key role in melanoma cell migration and progression. Herein, we highlight recent advances on ezrin involvement in the metastatic phenomenon, including also some more neglected ezrin-related functions. Novel molecular processes driven by ezrin activation include: phagocytosis, acquisition of resistance to chemotherapeutics and triggering of programmed cell death signals. Recent data support an integrated role of ezrin also in development of tumor malignancy. On one hand, ezrin may be responsible of deranged execution of specific known functions such as adhesion and motility and on the other, it may also participate to unique metastatic determinants, through the establishment of aberrant linkages with tumor-related proteins. For instance, ezrin misslocalization, absence or deranged activity has started to be correlated with tumor progression in many tumors of different species, including humans. Concomitantly, ezrin may act simultaneously as a regulatory or deregulatory chaperon in both normal and tumor cells. It is still to be established whether this Janus-faced feature of ezrin is due to some unknown transforming Zelig-like property or to the fact that a tumor-associated molecule preferentially links to ezrin thus distracting it from its normal connections. However, the contribution of ezrin functional deregulation to the acquisition of the metastatic phenotype appears clear and ezrin or ezrin aberrant associations may represent good candidates for future anti-tumor therapies.

Data and animal management software for large-scale phenotype screening.

PubMed

Ching, Keith A; Cooke, Michael P; Tarantino, Lisa M; Lapp, Hilmar

2006-04-01

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

Phenotypic Analysis Reveals that the 2010 Haiti Cholera Epidemic Is Linked to a Hypervirulent Strain

PubMed Central

Jones, Christopher J.; Wong, Jennifer; Queen, Jessica; Agarwal, Shivani; Yildiz, Fitnat H.

2016-01-01

Vibrio cholerae O1 El Tor strains have been responsible for pandemic cholera since 1961. These strains have evolved over time, spreading globally in three separate waves. Wave 3 is caused by altered El Tor (AET) variant strains, which include the strain with the signature ctxB7 allele that was introduced in 2010 into Haiti, where it caused a devastating epidemic. In this study, we used phenotypic analysis to compare an early isolate from the Haiti epidemic to wave 1 El Tor isolates commonly used for research. It is demonstrated that the Haiti isolate has increased production of cholera toxin (CT) and hemolysin, increased motility, and a reduced ability to form biofilms. This strain also outcompetes common wave 1 El Tor isolates for colonization of infant mice, indicating that it has increased virulence. Monitoring of CT production and motility in additional wave 3 isolates revealed that this phenotypic variation likely evolved over time rather than in a single genetic event. Analysis of available whole-genome sequences and phylogenetic analyses suggested that increased virulence arose from positive selection for mutations found in known and putative regulatory genes, including hns and vieA, diguanylate cyclase genes, and genes belonging to the lysR and gntR regulatory families. Overall, the studies presented here revealed that V. cholerae virulence potential can evolve and that the currently prevalent wave 3 AET strains are both phenotypically distinct from and more virulent than many El Tor isolates. PMID:27297393

Quantitative Modeling of Entangled Polymer Rheology: Experiments, Tube Models and Slip-Link Simulations

NASA Astrophysics Data System (ADS)

Desai, Priyanka Subhash

Rheology properties are sensitive indicators of molecular structure and dynamics. The relationship between rheology and polymer dynamics is captured in the constitutive model, which, if accurate and robust, would greatly aid molecular design and polymer processing. This dissertation is thus focused on building accurate and quantitative constitutive models that can help predict linear and non-linear viscoelasticity. In this work, we have used a multi-pronged approach based on the tube theory, coarse-grained slip-link simulations, and advanced polymeric synthetic and characterization techniques, to confront some of the outstanding problems in entangled polymer rheology. First, we modified simple tube based constitutive equations in extensional rheology and developed functional forms to test the effect of Kuhn segment alignment on a) tube diameter enlargement and b) monomeric friction reduction between subchains. We, then, used these functional forms to model extensional viscosity data for polystyrene (PS) melts and solutions. We demonstrated that the idea of reduction in segmental friction due to Kuhn alignment is successful in explaining the qualitative difference between melts and solutions in extension as revealed by recent experiments on PS. Second, we compiled literature data and used it to develop a universal tube model parameter set and prescribed their values and uncertainties for 1,4-PBd by comparing linear viscoelastic G' and G" mastercurves for 1,4-PBds of various branching architectures. The high frequency transition region of the mastercurves superposed very well for all the 1,4-PBds irrespective of their molecular weight and architecture, indicating universality in high frequency behavior. Therefore, all three parameters of the tube model were extracted from this high frequency transition region alone. Third, we compared predictions of two versions of the tube model, Hierarchical model and BoB model against linear viscoelastic data of blends of 1,4-PBd

Moving Contact Lines: Linking Molecular Dynamics and Continuum-Scale Modeling.

PubMed

Smith, Edward R; Theodorakis, Panagiotis E; Craster, Richard V; Matar, Omar K

2018-05-17

Despite decades of research, the modeling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily life applications. On the one hand, molecular dynamics (MD) simulation has the ability to provide unique insight into the microscopic details that determine the dynamic behavior of the contact line, which is not possible with either continuum-scale simulations or experiments. On the other hand, continuum-based models provide a link to the macroscopic description of the system. In this Feature Article, we explore the complex range of physical factors, including the presence of surfactants, which governs the contact line motion through MD simulations. We also discuss links between continuum- and molecular-scale modeling and highlight the opportunities for future developments in this area.

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Linking human beta retrovirus infection with primary biliary cirrhosis.

PubMed

Mason, A L; Zhang, G

2010-01-01

Several environmental agents have been linked with primary biliary cirrhosis (PBC) that include bacteria, xenobiotics and viruses. A human beta retrovirus (HBRV) related to mouse mammary tumor virus has been cloned and characterized from patients with PBC. This agent can be detected in the majority of patients' perihepatic lymph nodes by immunochemistry and RT-PCR. The HBRV has recently been isolated in culture and integration sites have been identified in the genome of patients to provide convincing evidence of beta retrovirus infection in patients. Three lines of evidence support a role for the virus in PBC. First, the beta retrovirus is linked with aberrant expression of mitochondrial protein(s) on the biliary epithelium cell (BEC) surface, a disease specific phenotype. Second, the related agent, mouse mammary tumor virus has been linked with autoimmune biliary disease in the NOD.c3c4 mouse model for PBC. In this mouse model, the virus is localized to diseased biliary epithelium that also display aberrant expression of the mitochondrial autoantigens. In translational studies, both patients with PBC and NOD.c3c4 mice demonstrate significant improvement in biliary disease with combination antiviral therapy. An overview of the biological relevance of the beta retrovirus infection in PBC will be discussed in this review. Copyright 2010 Elsevier Masson SAS. All rights reserved.

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

PubMed

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

2014-07-01

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

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

PubMed

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

2002-01-01

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

Recombination and phenotype evolution dynamics of Helicobacter pylori in colonized hosts.

PubMed

Shafiee, Ahmad; Amini, Massoud; Emamirad, Hassan; Abadi, Amin Talebi Bezmin

2016-07-01

The ample genetic diversity and variability of Helicobater pylori, and therefore its phenotypic evolution, relate not only to frequent mutation and selection but also to intra-specific recombination. Webb and Blaser applied a mathematical model to distinguish the role of selection and mutation for Lewis antigen phenotype evolution during long-term gastric colonization in infected animal hosts (mice and gerbils). To investigate the role of recombination in Lewis antigen phenotype evolution, we have developed a prior population dynamic by adding recombination term to the model. We simulate and interpret the new model simulation's results with a comparative analysis of biological aspects. The main conclusions are as follows: (i) the models and consequently the hosts with higher recombination rate require a longer time for stabilization; and (ii) recombination and mutation have opposite effects on the size of H. pylori populations with phenotypes in the range of the most-fit ones (i.e. those that have a selective advantage) due to natural selection, although both can increase phenotypic diversity.

Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon

DTIC Science & Technology

2016-07-01

was used to drive the transport and water quality kinetics for the simulation of 2007–2009. The sand berm, which controlled the opening/closure of...TECHNICAL REPORT 3015 July 2016 Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei...Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei-Fang Wang Chuck Katz Ripan Barua SSC Pacific James

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

PubMed

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

2008-01-01

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

Using Mouse Models to Explore Genotype-Phenotype Relationship in Down Syndrome

ERIC Educational Resources Information Center

Salehi, Ahmad; Faizi, Mehrdad; Belichenko, Pavel V.; Mobley, William C.

2007-01-01

Down Syndrome (DS) caused by trisomy 21 is characterized by a variety of phenotypes and involves multiple organs. Sequencing of human chromosome 21 (HSA21) and subsequently of its orthologues on mouse chromosome 16 have created an unprecedented opportunity to explore the complex relationship between various DS phenotypes and the extra copy of…

CKD Self-management: Phenotypes and Associations With Clinical Outcomes.

PubMed

Schrauben, Sarah J; Hsu, Jesse Y; Rosas, Sylvia E; Jaar, Bernard G; Zhang, Xiaoming; Deo, Rajat; Saab, Georges; Chen, Jing; Lederer, Swati; Kanthety, Radhika; Hamm, L Lee; Ricardo, Ana C; Lash, James P; Feldman, Harold I; Anderson, Amanda H

2018-03-24

To slow chronic kidney disease (CKD) progression and its complications, patients need to engage in self-management behaviors. The objective of this study was to classify CKD self-management behaviors into phenotypes and assess the association of these phenotypes with clinical outcomes. Prospective cohort study. Adults with mild to moderate CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study. 3,939 participants in the CRIC Study recruited between 2003 and 2008 served as the derivation cohort and 1,560 participants recruited between 2013 and 2015 served as the validation cohort. CKD self-management behavior phenotypes. CKD progression, atherosclerotic events, heart failure events, death from any cause. Latent class analysis stratified by diabetes was used to identify CKD self-management phenotypes based on measures of body mass index, diet, physical activity, blood pressure, smoking status, and hemoglobin A 1c concentration (if diabetic); Cox proportional hazards models. 3 identified phenotypes varied according to the extent of implementation of recommended CKD self-management behaviors: phenotype I characterized study participants with the most recommended behaviors; phenotype II, participants with a mixture of recommended and not recommended behaviors; and phenotype III, participants with minimal recommended behaviors. In multivariable-adjusted models for those with and without diabetes, phenotype III was strongly associated with CKD progression (HRs of 1.82 and 1.49), death (HRs of 1.95 and 4.14), and atherosclerotic events (HRs of 2.54 and 1.90; each P < 0.05). Phenotype II was associated with atherosclerotic events and death among those with and without diabetes. No consensus definition of CKD self-management; limited to baseline behavior data. There are potentially 3 CKD self-management behavior phenotypes that distinguish risk for clinical outcomes. These phenotypes may inform the development of studies and guidelines regarding optimal self

A Linked Model for Simulating Stand Development and Growth Processes of Loblolly Pine

Treesearch

V. Clark Baldwin; Phillip M. Dougherty; Harold E. Burkhart

1998-01-01

Linking models of different scales (e.g., process, tree-stand-ecosystem) is essential for furthering our understanding of stand, climatic, and edaphic effects on tree growth and forest productivity. Moreover, linking existing models that differ in scale and levels of resolution quickly identifies knowledge gaps in information required to scale from one level to another...

Modeling of the ground-to-SSFMB link networking features using SPW

NASA Technical Reports Server (NTRS)

Watson, John C.

1993-01-01

This report describes the modeling and simulation of the networking features of the ground-to-Space Station Freedom manned base (SSFMB) link using COMDISCO signal processing work-system (SPW). The networking features modeled include the implementation of Consultative Committee for Space Data Systems (CCSDS) protocols in the multiplexing of digitized audio and core data into virtual channel data units (VCDU's) in the control center complex and the demultiplexing of VCDU's in the onboard baseband signal processor. The emphasis of this work has been placed on techniques for modeling the CCSDS networking features using SPW. The objectives for developing the SPW models are to test the suitability of SPW for modeling networking features and to develop SPW simulation models of the control center complex and space station baseband signal processor for use in end-to-end testing of the ground-to-SSFMB S-band single access forward (SSAF) link.

Phenotypic screening in cancer drug discovery - past, present and future.

PubMed

Moffat, John G; Rudolph, Joachim; Bailey, David

2014-08-01

There has been a resurgence of interest in the use of phenotypic screens in drug discovery as an alternative to target-focused approaches. Given that oncology is currently the most active therapeutic area, and also one in which target-focused approaches have been particularly prominent in the past two decades, we investigated the contribution of phenotypic assays to oncology drug discovery by analysing the origins of all new small-molecule cancer drugs approved by the US Food and Drug Administration (FDA) over the past 15 years and those currently in clinical development. Although the majority of these drugs originated from target-based discovery, we identified a significant number whose discovery depended on phenotypic screening approaches. We postulate that the contribution of phenotypic screening to cancer drug discovery has been hampered by a reliance on 'classical' nonspecific drug effects such as cytotoxicity and mitotic arrest, exacerbated by a paucity of mechanistically defined cellular models for therapeutically translatable cancer phenotypes. However, technical and biological advances that enable such mechanistically informed phenotypic models have the potential to empower phenotypic drug discovery in oncology.

Metabolic phenotype in the mouse model of osteogenesis imperfecta.

PubMed

Boraschi-Diaz, Iris; Tauer, Josephine T; El-Rifai, Omar; Guillemette, Delphine; Lefebvre, Geneviève; Rauch, Frank; Ferron, Mathieu; Komarova, Svetlana V

2017-09-01

Osteogenesis imperfecta (OI) is the most common heritable bone fragility disorder, usually caused by dominant mutations in genes coding for collagen type I alpha chains, COL1A1 or COL1A2 Osteocalcin (OCN) is now recognized as a bone-derived regulator of insulin secretion and sensitivity and glucose homeostasis. Since OI is associated with increased rates of bone formation and resorption, we hypothesized that the levels of undercarboxylated OCN are increased in OI. The objective of this study was to determine changes in OCN and to elucidate the metabolic phenotype in the Col1a1 Jrt/+ mouse, a model of dominant OI caused by a Col1a1 mutation. Circulating levels of undercarboxylated OCN were higher in 4-week-old OI mice and normal by 8 weeks of age. Young OI animals exhibited a sex-dependent metabolic phenotype, including increased insulin levels in males, improved glucose tolerance in females, lower levels of random glucose and low adiposity in both sexes. The rates of O 2 consumption and CO 2 production, as well as energy expenditure assessed using indirect calorimetry were significantly increased in OI animals of both sexes, whereas respiratory exchange ratio was significantly higher in OI males only. Although OI mice have significant physical impairment that may contribute to metabolic differences, we specifically accounted for movement and compared OI and WT animals during the periods of similar activity levels. Taken together, our data strongly suggest that OI animals have alterations in whole body energy metabolism that are consistent with the action of undercarboxylated osteocalcin. © 2017 Society for Endocrinology.

Dynamics of phenotypic switching of bacterial cells with temporal fluctuations in pressure

NASA Astrophysics Data System (ADS)

Nepal, Sudip; Kumar, Pradeep

2018-05-01

Phenotypic switching is one of the mechanisms by which bacteria thrive in ever changing environmental conditions around them. Earlier studies have shown that the application of steady high hydrostatic pressure leads to stochastic switching of mesophilic bacteria from a cellular phenotype having a normal cell cycle to another phenotype lacking cell division. Here, we have studied the dynamics of this phenotypic switching with fluctuating periodic pressure using a set of experiments and a theoretical model. Our results suggest that the phenotypic switching rate from high-pressure phenotype to low-pressure phenotype in the reversible regime is larger as compared to the switching rate from low-pressure phenotype to high-pressure phenotype. Furthermore, we find that even though the cell division and elongation are presumably regulated by a large number of genes the underlying physics of the dynamics of stochastic switching at high pressure is captured reasonably well by a simple two-state model.

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102

X-linked Charcot-Marie-Tooth (CMT) neuropathies (CMTX1, CMTX2, CMTX3) show different clinical phenotype and molecular genetics

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

Ionasescu, V.V.; Searby, C.C.; Ionasescu, R.

1994-09-01

The purpose of this study was to compare the X-linked dominant type CMTX1 (20 families) with X-linked recessive types CMTX2 and CMTX3 (2 families). The clinical phenotype was consistent with CMT peripheral neuropathy in all cases including distal weakness, atrophy and sensory loss, pes cavus and areflexia. Additional clinicial involvement of the central nervous system was present in one family with CMTX2 (mental retardation) and one family with CMTX3 (spastic paraparesis). Tight genetic linkage to Xq13.1 was present in 20 families with CMTX1 (Z=34.07 at {theta}=0) for the marker DXS453. Fifteen of the CMTX1 families showed point mutations of themore » connexin 32 coding region (5 nonsense mutations, 8 missense mutations, 2 deletions). Five CMTX1 neuropathy families showed no evidence of point mutations of the CX32 coding sequence. These findings suggest that the CMTX1 neuropathy genotype in these families may be the result of promoter mutations, 3{prime}-untranslated region mutations or exon/intron splice site mutations or a mutation with a different type of connexin but which has close structural similarities to CX32. No mutations of the CX32 coding region were found in the CMTX2 or CMTX3 families. Linkage to Xq13.1 was excluded in both families. Genetic linkage to Xp22.2 was present in the CMTX2 family (Z=3.54 at {theta}=0) for the markers DXS987 and DXS999. Suggestion of linkage to Xq26 (Z=1.81 at {theta}=0) for the marker DXS86 was present in the CMTX3 family.« less

Robust and Sensitive Analysis of Mouse Knockout Phenotypes

PubMed Central

Karp, Natasha A.; Melvin, David; Mott, Richard F.

2012-01-01

A significant challenge of in-vivo studies is the identification of phenotypes with a method that is robust and reliable. The challenge arises from practical issues that lead to experimental designs which are not ideal. Breeding issues, particularly in the presence of fertility or fecundity problems, frequently lead to data being collected in multiple batches. This problem is acute in high throughput phenotyping programs. In addition, in a high throughput environment operational issues lead to controls not being measured on the same day as knockouts. We highlight how application of traditional methods, such as a Student’s t-Test or a 2-way ANOVA, in these situations give flawed results and should not be used. We explore the use of mixed models using worked examples from Sanger Mouse Genome Project focusing on Dual-Energy X-Ray Absorptiometry data for the analysis of mouse knockout data and compare to a reference range approach. We show that mixed model analysis is more sensitive and less prone to artefacts allowing the discovery of subtle quantitative phenotypes essential for correlating a gene’s function to human disease. We demonstrate how a mixed model approach has the additional advantage of being able to include covariates, such as body weight, to separate effect of genotype from these covariates. This is a particular issue in knockout studies, where body weight is a common phenotype and will enhance the precision of assigning phenotypes and the subsequent selection of lines for secondary phenotyping. The use of mixed models with in-vivo studies has value not only in improving the quality and sensitivity of the data analysis but also ethically as a method suitable for small batches which reduces the breeding burden of a colony. This will reduce the use of animals, increase throughput, and decrease cost whilst improving the quality and depth of knowledge gained. PMID:23300663

Semi-supervised Learning for Phenotyping Tasks.

PubMed

Dligach, Dmitriy; Miller, Timothy; Savova, Guergana K

2015-01-01

Supervised learning is the dominant approach to automatic electronic health records-based phenotyping, but it is expensive due to the cost of manual chart review. Semi-supervised learning takes advantage of both scarce labeled and plentiful unlabeled data. In this work, we study a family of semi-supervised learning algorithms based on Expectation Maximization (EM) in the context of several phenotyping tasks. We first experiment with the basic EM algorithm. When the modeling assumptions are violated, basic EM leads to inaccurate parameter estimation. Augmented EM attenuates this shortcoming by introducing a weighting factor that downweights the unlabeled data. Cross-validation does not always lead to the best setting of the weighting factor and other heuristic methods may be preferred. We show that accurate phenotyping models can be trained with only a few hundred labeled (and a large number of unlabeled) examples, potentially providing substantial savings in the amount of the required manual chart review.

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures.

PubMed

Colen, Rivka; Foster, Ian; Gatenby, Robert; Giger, Mary Ellen; Gillies, Robert; Gutman, David; Heller, Matthew; Jain, Rajan; Madabhushi, Anant; Madhavan, Subha; Napel, Sandy; Rao, Arvind; Saltz, Joel; Tatum, James; Verhaak, Roeland; Whitman, Gary

2014-10-01

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Medaka as a model for studying environmentally induced epigenetic transgenerational inheritance of phenotypes

PubMed Central

2016-01-01

Abstract Ability of environmental stressors to induce transgenerational diseases has been experimentally demonstrated in plants, worms, fish, and mammals, indicating that exposures affect not only human health but also fish and ecosystem health. Small aquarium fish have been reliable model to study genetic and epigenetic basis of development and disease. Additionally, fish can also provide better, economic opportunity to study transgenerational inheritance of adverse health and epigenetic mechanisms. Molecular mechanisms underlying germ cell development in fish are comparable to those in mammals and humans. This review will provide a short overview of long-term effects of environmental chemical contaminant exposure in various models, associated epigenetic mechanisms, and a perspective on fish as model to study environmentally induced transgenerational inheritance of altered phenotypes. PMID:29492282

Epistasis and Pleiotropy Affect the Modularity of the Genotype-Phenotype Map of Cross-Resistance in HIV-1.

PubMed

Polster, Robert; Petropoulos, Christos J; Bonhoeffer, Sebastian; Guillaume, Frédéric

2016-12-01

The genotype-phenotype (GP) map is a central concept in evolutionary biology as it describes the mapping of molecular genetic variation onto phenotypic trait variation. Our understanding of that mapping remains partial, especially when trying to link functional clustering of pleiotropic gene effects with patterns of phenotypic trait co-variation. Only on rare occasions have studies been able to fully explore that link and tend to show poor correspondence between modular structures within the GP map and among phenotypes. By dissecting the structure of the GP map of the replicative capacity of HIV-1 in 15 drug environments, we provide a detailed view of that mapping from mutational pleiotropic variation to phenotypic co-variation, including epistatic effects of a set of amino-acid substitutions in the reverse transcriptase and protease genes. We show that epistasis increases the pleiotropic degree of single mutations and provides modularity to the GP map of drug resistance in HIV-1. Moreover, modules of epistatic pleiotropic effects within the GP map match the phenotypic modules of correlated replicative capacity among drug classes. Epistasis thus increases the evolvability of cross-resistance in HIV by providing more drug- and class-specific pleiotropic profiles to the main effects of the mutations. We discuss the implications for the evolution of cross-resistance in HIV. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Quantitative genetic models of sexual conflict based on interacting phenotypes.

PubMed

Moore, Allen J; Pizzari, Tommaso

2005-05-01

Evolutionary conflict arises between reproductive partners when alternative reproductive opportunities are available. Sexual conflict can generate sexually antagonistic selection, which mediates sexual selection and intersexual coevolution. However, despite intense interest, the evolutionary implications of sexual conflict remain unresolved. We propose a novel theoretical approach to study the evolution of sexually antagonistic phenotypes based on quantitative genetics and the measure of social selection arising from male-female interactions. We consider the phenotype of one sex as both a genetically influenced evolving trait as well as the (evolving) social environment in which the phenotype of the opposite sex evolves. Several important points emerge from our analysis, including the relationship between direct selection on one sex and indirect effects through selection on the opposite sex. We suggest that the proposed approach may be a valuable tool to complement other theoretical approaches currently used to study sexual conflict. Most importantly, our approach highlights areas where additional empirical data can help clarify the role of sexual conflict in the evolutionary process.

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.

Reduced sympathetic innervation after alteration of target cell neurotransmitter phenotype in transgenic mice.

PubMed Central

Cho, S; Son, J H; Park, D H; Aoki, C; Song, X; Smith, G P; Joh, T H

1996-01-01

Neurotransmitters play a variety of important roles during nervous system development. In the present study, we hypothesized that neurotransmitter phenotype of both projecting and target cells is an important factor for the final synaptic linkage and its specificity. To test this hypothesis, we used transgenic techniques to convert serotonin/melatonin-producing cells of the pineal gland into cells that also produce dopamine and investigated the innervation of the phenotypically altered target cells. This phenotypic alteration markedly reduced the noradrenergic innervation originating from the superior cervical ganglia. Although the mechanism by which the reduction occurs is presently unknown, quantitative enzyme-linked immunoassay showed the presence of the equivalent amounts of nerve growth factor (NGF) in the control and transgenic pineal glands, suggesting that it occurred in a NGF-independent manner. The results suggest that target neurotransmitter phenotype influences the formation of afferent connections during development. Images Fig. 3 Fig. 4 PMID:8610132

EHR-based phenotyping: Bulk learning and evaluation.

PubMed

Chiu, Po-Hsiang; Hripcsak, George

2017-06-01

In data-driven phenotyping, a core computational task is to identify medical concepts and their variations from sources of electronic health records (EHR) to stratify phenotypic cohorts. A conventional analytic framework for phenotyping largely uses a manual knowledge engineering approach or a supervised learning approach where clinical cases are represented by variables encompassing diagnoses, medicinal treatments and laboratory tests, among others. In such a framework, tasks associated with feature engineering and data annotation remain a tedious and expensive exercise, resulting in poor scalability. In addition, certain clinical conditions, such as those that are rare and acute in nature, may never accumulate sufficient data over time, which poses a challenge to establishing accurate and informative statistical models. In this paper, we use infectious diseases as the domain of study to demonstrate a hierarchical learning method based on ensemble learning that attempts to address these issues through feature abstraction. We use a sparse annotation set to train and evaluate many phenotypes at once, which we call bulk learning. In this batch-phenotyping framework, disease cohort definitions can be learned from within the abstract feature space established by using multiple diseases as a substrate and diagnostic codes as surrogates. In particular, using surrogate labels for model training renders possible its subsequent evaluation using only a sparse annotated sample. Moreover, statistical models can be trained and evaluated, using the same sparse annotation, from within the abstract feature space of low dimensionality that encapsulates the shared clinical traits of these target diseases, collectively referred to as the bulk learning set. Copyright © 2017 Elsevier Inc. All rights reserved.

Desiderata for computable representations of electronic health records-driven phenotype algorithms

PubMed Central

Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A

2015-01-01

Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. PMID:26342218

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

PubMed Central

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

2017-01-01

Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

Sqstm1 knock-down causes a locomotor phenotype ameliorated by rapamycin in a zebrafish model of ALS/FTLD.

PubMed

Lattante, Serena; de Calbiac, Hortense; Le Ber, Isabelle; Brice, Alexis; Ciura, Sorana; Kabashi, Edor

2015-03-15

Mutations in SQSTM1, encoding for the protein SQSTM1/p62, have been recently reported in 1-3.5% of patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration (ALS/FTLD). Inclusions positive for SQSTM1/p62 have been detected in patients with neurodegenerative disorders, including ALS/FTLD. In order to investigate the pathogenic mechanisms induced by SQSTM1 mutations in ALS/FTLD, we developed a zebrafish model. Knock-down of the sqstm1 zebrafish ortholog, as well as impairment of its splicing, led to a specific phenotype, consisting of behavioral and axonal anomalies. Here, we report swimming deficits associated with shorter motor neuronal axons that could be rescued by the overexpression of wild-type human SQSTM1. Interestingly, no rescue of the loss-of-function phenotype was observed when overexpressing human SQSTM1 constructs carrying ALS/FTLD-related mutations. Consistent with its role in autophagy regulation, we found increased mTOR levels upon knock-down of sqstm1. Furthermore, treatment of zebrafish embryos with rapamycin, a known inhibitor of the mTOR pathway, yielded an amelioration of the locomotor phenotype in the sqstm1 knock-down model. Our results suggest that loss-of-function of SQSTM1 causes phenotypic features characterized by locomotor deficits and motor neuron axonal defects that are associated with a misregulation of autophagic processes. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Expression of ALS/FTD-linked mutant CCNF in zebrafish leads to increased cell death in the spinal cord and an aberrant motor phenotype.

PubMed

Hogan, Alison L; Don, Emily K; Rayner, Stephanie L; Lee, Albert; Laird, Angela S; Watchon, Maxinne; Winnick, Claire; Tarr, Ingrid S; Morsch, Marco; Fifita, Jennifer A; Gwee, Serene S L; Formella, Isabel; Hortle, Elinor; Yuan, Kristy C; Molloy, Mark P; Williams, Kelly L; Nicholson, Garth A; Chung, Roger S; Blair, Ian P; Cole, Nicholas J

2017-07-15

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive, fatal neurodegenerative disease characterised by the death of upper and lower motor neurons. Approximately 10% of cases have a known family history of ALS and disease-linked mutations in multiple genes have been identified. ALS-linked mutations in CCNF were recently reported, however the pathogenic mechanisms associated with these mutations are yet to be established. To investigate possible disease mechanisms, we developed in vitro and in vivo models based on an ALS-linked missense mutation in CCNF. Proteomic analysis of the in vitro models identified the disruption of several cellular pathways in the mutant model, including caspase-3 mediated cell death. Transient overexpression of human CCNF in zebrafish embryos supported this finding, with fish expressing the mutant protein found to have increased levels of cleaved (activated) caspase-3 and increased cell death in the spinal cord. The mutant CCNF fish also developed a motor neuron axonopathy consisting of shortened primary motor axons and increased frequency of aberrant axonal branching. Importantly, we demonstrated a significant correlation between the severity of the CCNF-induced axonopathy and a reduced motor response to a light stimulus (photomotor response). This is the first report of an ALS-linked CCNF mutation in vivo and taken together with the in vitro model identifies the disruption of cell death pathways as a significant consequence of this mutation. Additionally, this study presents a valuable new tool for use in ongoing studies investigating the pathobiology of ALS-linked CCNF mutations. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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 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

Human SOD1 ALS Mutations in a Drosophila Knock-In Model Cause Severe Phenotypes and Reveal Dosage-Sensitive Gain- and Loss-of-Function Components.

PubMed

Şahin, Aslı; Held, Aaron; Bredvik, Kirsten; Major, Paxton; Achilli, Toni-Marie; Kerson, Abigail G; Wharton, Kristi; Stilwell, Geoff; Reenan, Robert

2017-02-01

Amyotrophic Lateral Sclerosis (ALS) is the most common adult-onset motor neuron disease and familial forms can be caused by numerous dominant mutations of the copper-zinc superoxide dismutase 1 (SOD1) gene. Substantial efforts have been invested in studying SOD1-ALS transgenic animal models; yet, the molecular mechanisms by which ALS-mutant SOD1 protein acquires toxicity are not well understood. ALS-like phenotypes in animal models are highly dependent on transgene dosage. Thus, issues of whether the ALS-like phenotypes of these models stem from overexpression of mutant alleles or from aspects of the SOD1 mutation itself are not easily deconvolved. To address concerns about levels of mutant SOD1 in disease pathogenesis, we have genetically engineered four human ALS-causing SOD1 point mutations (G37R, H48R, H71Y, and G85R) into the endogenous locus of Drosophila SOD1 (dsod) via ends-out homologous recombination and analyzed the resulting molecular, biochemical, and behavioral phenotypes. Contrary to previous transgenic models, we have recapitulated ALS-like phenotypes without overexpression of the mutant protein. Drosophila carrying homozygous mutations rendering SOD1 protein enzymatically inactive (G85R, H48R, and H71Y) exhibited neurodegeneration, locomotor deficits, and shortened life span. The mutation retaining enzymatic activity (G37R) was phenotypically indistinguishable from controls. While the observed mutant dsod phenotypes were recessive, a gain-of-function component was uncovered through dosage studies and comparisons with age-matched dsod null animals, which failed to show severe locomotor defects or nerve degeneration. We conclude that the Drosophila knock-in model captures important aspects of human SOD1-based ALS and provides a powerful and useful tool for further genetic studies. Copyright © 2017 by the Genetics Society of America.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

PubMed

Zhao, Jiangsan; Bodner, Gernot; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A; Nakhforoosh, Alireza

2017-02-01

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems

PubMed Central

Zhao, Jiangsan; Rewald, Boris; Leitner, Daniel; Nagel, Kerstin A.; Nakhforoosh, Alireza

2017-01-01

Abstract Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research. PMID:28168270

Generation of induced pluripotent stem cells from a patient with X-linked juvenile retinoschisis.

PubMed

Peng, Chi-Hsien; Huang, Kang-Chieh; Lu, Huai-En; Syu, Shih-Han; Yarmishyn, Aliaksandr A; Lu, Jyh-Feng; Buddhakosai, Waradee; Lin, Tai-Chi; Hsu, Chih-Chien; Hwang, De-Kuang; Shen, Chia-Ning; Chen, Shih-Jen; Chiou, Shih-Hwa

2018-05-01

X-linked juvenile retinoschisis (XLRS) is a hereditary retinal dystrophy manifested as splitting of anatomical layers of retina. In this report, we generated a patient-specific induced pluripotent stem cell (iPSC) line, TVGH-iPSC-013-05, from the peripheral blood mononuclear cells of a male patient with XLRS by using the Sendai-virus delivery system. We believe that XLRS patient-specific iPSCs provide a powerful in vitro model for evaluating the pathological phenotypes of the disease. Copyright © 2018. Published by Elsevier B.V.

A linked hydrodynamic and water quality model for the Salton Sea

USGS Publications Warehouse

Chung, E.G.; Schladow, S.G.; Perez-Losada, J.; Robertson, Dale M.

2008-01-01

A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the one-dimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO4-3, NO3-1 and NH4+1, DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented. ?? 2008 Springer Science+Business Media B.V.

Red hair is the null phenotype of MC1R.

PubMed

Beaumont, Kimberley A; Shekar, Sri N; Cook, Anthony L; Duffy, David L; Sturm, Richard A

2008-08-01

The Melanocortin-1 Receptor (MC1R) is a G-protein coupled receptor, which is responsible for production of the darker eumelanin pigment and the tanning response. The MC1R gene has many polymorphisms, some of which have been linked to variation in pigmentation phenotypes within human populations. In particular, the p.D84E, p.R151C, p.R160W and p.D294 H alleles have been strongly associated with red hair, fair skin and increased skin cancer risk. These red hair colour (RHC) variants are relatively well described and are thought to result in altered receptor function, while still retaining varying levels of signaling ability in vitro. The mouse Mc1r null phenotype is yellow fur colour, the p.R151C, p.R160W and p.D294 H alleles were able to partially rescue this phenotype, leading to the question of what the true null phenotype of MC1R would be in humans. Due to the rarity of MC1R null alleles in human populations, they have only been found in the heterozygous state until now. We report here the first case of a homozygous MC1R null individual, phenotypic analysis indicates that red hair and fair skin is found in the absence of MC1R function.

Forensic DNA phenotyping: Developing a model privacy impact assessment.

PubMed

Scudder, Nathan; McNevin, Dennis; Kelty, Sally F; Walsh, Simon J; Robertson, James

2018-05-01

Forensic scientists around the world are adopting new technology platforms capable of efficiently analysing a larger proportion of the human genome. Undertaking this analysis could provide significant operational benefits, particularly in giving investigators more information about the donor of genetic material, a particularly useful investigative lead. Such information could include predicting externally visible characteristics such as eye and hair colour, as well as biogeographical ancestry. This article looks at the adoption of this new technology from a privacy perspective, using this to inform and critique the application of a Privacy Impact Assessment to this emerging technology. Noting the benefits and limitations, the article develops a number of themes that would influence a model Privacy Impact Assessment as a contextual framework for forensic laboratories and law enforcement agencies considering implementing forensic DNA phenotyping for operational use. Copyright © 2018 Elsevier B.V. All rights reserved.

Phenotypic characterization of the Komeda miniature rat Ishikawa, an animal model of dwarfism caused by a mutation in Prkg2.

PubMed

Tsuchida, Atsuko; Yokoi, Norihide; Namae, Misako; Fuse, Masanori; Masuyama, Taku; Sasaki, Masashi; Kawazu, Shoji; Komeda, Kajuro

2008-12-01

The Komeda miniature rat Ishikawa (KMI) is a spontaneous animal model of dwarfism caused by a mutation in Prkg2, which encodes cGMP-dependent protein kinase type II (cGKII). This strain has been maintained as a segregating inbred strain for the mutated allele mri. In this study, we characterized the phenotype of the KMI strain, particularly growth traits, craniofacial measurements, and organ weights. The homozygous mutant (mri/mri) animals were approximately 70% to 80% of the size of normal, heterozygous (mri/+) animals in regard to body length, weight, and naso-occipital length of the calvarium, and the retroperitoneal fat of mri/mri rats was reduced greatly. In addition, among progeny of the (BNxKMI-mri/mri)F1xKMI-mri/mri backcross, animals with the KMI phenotype (mri/mri) were easily distinguished from those showing the wild-type phenotype (mri/+) by using growth traits such as body length and weight. Genetic analysis revealed that all of the backcrossed progeny exhibiting the KMI phenotype were homozygous for the KMI allele in the 1.2-cM region between D14Rat5 and D14Rat80 on chromosome 14, suggesting strongly that mri acts in a completely recessive manner. The KMI strain is the first and only rat model with a confirmed mutation in Prkg2 and is a valuable model for studying dwarfism and longitudinal growth traits in humans and for functional studies of cGKII.

Phenotypic Characterization of the Komeda Miniature Rat Ishikawa, an Animal Model of Dwarfism Caused by a Mutation in Prkg2

PubMed Central

Tsuchida, Atsuko; Yokoi, Norihide; Namae, Misako; Fuse, Masanori; Masuyama, Taku; Sasaki, Masashi; Kawazu, Shoji; Komeda, Kajuro

2008-01-01

The Komeda miniature rat Ishikawa (KMI) is a spontaneous animal model of dwarfism caused by a mutation in Prkg2, which encodes cGMP-dependent protein kinase type II (cGKII). This strain has been maintained as a segregating inbred strain for the mutated allele mri. In this study, we characterized the phenotype of the KMI strain, particularly growth traits, craniofacial measurements, and organ weights. The homozygous mutant (mri/mri) animals were approximately 70% to 80% of the size of normal, heterozygous (mri/+) animals in regard to body length, weight, and naso-occipital length of the calvarium, and the retroperitoneal fat of mri/mri rats was reduced greatly. In addition, among progeny of the (BN×KMI-mri/mri)F1×KMI-mri/mri backcross, animals with the KMI phenotype (mri/mri) were easily distinguished from those showing the wild-type phenotype (mri/+) by using growth traits such as body length and weight. Genetic analysis revealed that all of the backcrossed progeny exhibiting the KMI phenotype were homozygous for the KMI allele in the 1.2-cM region between D14Rat5 and D14Rat80 on chromosome 14, suggesting strongly that mri acts in a completely recessive manner. The KMI strain is the first and only rat model with a confirmed mutation in Prkg2 and is a valuable model for studying dwarfism and longitudinal growth traits in humans and for functional studies of cGKII. PMID:19149413

Proportional exponentiated link transformed hazards (ELTH) models for discrete time survival data with application

PubMed Central

Joeng, Hee-Koung; Chen, Ming-Hui; Kang, Sangwook

2015-01-01

Discrete survival data are routinely encountered in many fields of study including behavior science, economics, epidemiology, medicine, and social science. In this paper, we develop a class of proportional exponentiated link transformed hazards (ELTH) models. We carry out a detailed examination of the role of links in fitting discrete survival data and estimating regression coefficients. Several interesting results are established regarding the choice of links and baseline hazards. We also characterize the conditions for improper survival functions and the conditions for existence of the maximum likelihood estimates under the proposed ELTH models. An extensive simulation study is conducted to examine the empirical performance of the parameter estimates under the Cox proportional hazards model by treating discrete survival times as continuous survival times, and the model comparison criteria, AIC and BIC, in determining links and baseline hazards. A SEER breast cancer dataset is analyzed in details to further demonstrate the proposed methodology. PMID:25772374

Mechanical phenotype of cancer cells: cell softening and loss of stiffness sensing.

PubMed

Lin, Hsi-Hui; Lin, Hsiu-Kuan; Lin, I-Hsuan; Chiou, Yu-Wei; Chen, Horn-Wei; Liu, Ching-Yi; Harn, Hans I-Chen; Chiu, Wen-Tai; Wang, Yang-Kao; Shen, Meng-Ru; Tang, Ming-Jer

2015-08-28

The stiffness sensing ability is required to respond to the stiffness of the matrix. Here we determined whether normal cells and cancer cells display distinct mechanical phenotypes. Cancer cells were softer than their normal counterparts, regardless of the type of cancer (breast, bladder, cervix, pancreas, or Ha-RasV12-transformed cells). When cultured on matrices of varying stiffness, low stiffness decreased proliferation in normal cells, while cancer cells and transformed cells lost this response. Thus, cancer cells undergo a change in their mechanical phenotype that includes cell softening and loss of stiffness sensing. Caveolin-1, which is suppressed in many tumor cells and in oncogene-transformed cells, regulates the mechanical phenotype. Caveolin-1-upregulated RhoA activity and Y397FAK phosphorylation directed actin cap formation, which was positively correlated with cell elasticity and stiffness sensing in fibroblasts. Ha-RasV12-induced transformation and changes in the mechanical phenotypes were reversed by re-expression of caveolin-1 and mimicked by the suppression of caveolin-1 in normal fibroblasts. This is the first study to describe this novel role for caveolin-1, linking mechanical phenotype to cell transformation. Furthermore, mechanical characteristics may serve as biomarkers for cell transformation.

The Hairless Stem Phenotype of Cotton (Gossypium barbadense) Is Linked to a Copia-Like Retrotransposon Insertion in a Homeodomain-Leucine Zipper Gene (HD1)

PubMed Central

Ding, Mingquan; Ye, Wuwei; Lin, Lifeng; He, Shae; Du, Xiongming; Chen, Aiqun; Cao, Yuefen; Qin, Yuan; Yang, Fen; Jiang, Yurong; Zhang, Hua; Wang, Xiyin; Paterson, Andrew H.; Rong, Junkang

2015-01-01

Cotton (Gossypium) stem trichomes are mostly single cells that arise from stem epidermal cells. In this study, a homeodomain-leucine zipper gene (HD1) was found to cosegregate with the dominant trichome locus previously designated as T1 and mapped to chromosome 6. Characterization of HD1 orthologs revealed that the absence of stem trichomes in modern Gossypium barbadense varieties is linked to a large retrotransposon insertion in the ninth exon, 2565 bp downstream from the initial codon in the At subgenome HD1 gene (At-GbHD1). In both the At and Dt subgenomes, reduced transcription of GbHD1 genes is caused by this insertion. The disruption of At-HD1 further affects the expression of downstream GbMYB25 and GbHOX3 genes. Analyses of primitive cultivated accessions identified another retrotransposon insertion event in the sixth exon of At-GbHD1 that might predate the previously identified retrotransposon in modern varieties. Although both retrotransposon insertions results in similar phenotypic changes, the timing of these two retrotransposon insertion events fits well with our current understanding of the history of cotton speciation and dispersal. Taken together, the results of genetics mapping, gene expression and association analyses suggest that GbHD1 is an important component that controls stem trichome development and is a promising candidate gene for the T1 locus. The interspecific phenotypic difference in stem trichome traits also may be attributable to HD1 inactivation associated with retrotransposon insertion. PMID:26133897

Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks

PubMed Central

Ronellenfitsch, Henrik; Lasser, Jana; Daly, Douglas C.; Katifori, Eleni

2015-01-01

The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a “leaf venation fingerprint” from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain. PMID:26700471

The division of labor: genotypic versus phenotypic specialization.

PubMed

Wahl, L M

2002-07-01

A model of the division of labor in simple evolving systems is explored to compare two strategies evident in natural populations: phenotypic specialization (such as differentiation by regulated gene expression) and genotypic specialization (such as co-infection by complementary covirus populations). While genotypic specialization is vulnerable to the chance extinction of an essential specialist type and to parasitism, phenotypic specialization is able to overcome these hurdles. When simple spatial effects are included, phenotypic specialization has further benefits, protecting against destructive dynamic patterns. Many of the advantages of phenotypic specialization, however, can only be realized when a high degree of relatedness within groups is ensured.

HMGB1 targeting by ethyl pyruvate suppresses malignant phenotype of human mesothelioma.

PubMed

Pellegrini, Laura; Xue, Jiaming; Larson, David; Pastorino, Sandra; Jube, Sandro; Forest, Kelly H; Saad-Jube, Zeyana Salim; Napolitano, Andrea; Pagano, Ian; Negi, Vishal S; Bianchi, Marco E; Morris, Paul; Pass, Harvey I; Gaudino, Giovanni; Carbone, Michele; Yang, Haining

2017-04-04

Human malignant mesothelioma (MM) is an aggressive cancer linked to asbestos and erionite exposure. We previously reported that High-Mobility Group Box-1 protein (HMGB1), a prototypic damage-associated molecular pattern, drives MM development and sustains MM progression. Moreover, we demonstrated that targeting HMGB1 inhibited MM cell growth and motility in vitro, reduced tumor growth in vivo, and prolonged survival of MM-bearing mice. Ethyl pyruvate (EP), the ethyl ester of pyruvic acid, has been shown to be an effective HMGB1 inhibitor in inflammation-related diseases and several cancers. Here, we studied the effect of EP on the malignant phenotype of MM cells in tissue culture and on tumor growth in vivo using an orthotopic MM xenograft model. We found that EP impairs HMGB1 secretion by MM cells leading to reduced RAGE expression and NF-κB activation. As a consequence, EP impaired cell motility, cell proliferation, and anchorage-independent growth of MM cells. Moreover, EP reduced HMGB1 serum levels in mice and inhibited the growth of MM xenografts.Our results indicate that EP effectively hampers the malignant phenotype of MM, offering a novel potential therapeutic approach to patients afflicted with this dismal disease.

Prevalence of unilateral and bilateral deafness in border collies and association with phenotype.

PubMed

Platt, Simon; Freeman, Julia; di Stefani, Alberta; Wieczorek, Lara; Henley, William

2006-01-01

Congenital sensorineural deafness (CSD) occurs in Border Collies, but its prevalence and inheritance are unknown. This study estimated the prevalence of CSD in Border Collies and investigated its association with phenotypic attributes linked to the merle gene, including coat pigmentation and iris color. Deafness in Border Collies is associated with pigmentation patterns linked to the merle gene. A total of 2597 Border Collies from the United Kingdom. A retrospective study of Border Collies tested, during 1994-2002, by using brainstem auditory evoked responses. Associations between deafness and phenotypic attributes were assessed by using generalized logistic regression. The prevalence of CSD in puppies was estimated as 2.8%. The corresponding rates of unilateral and bilateral CSD were 2.3 and 0.5%, respectively. Adjustment for clustering of hearing status by litter reduced the overall prevalence estimate to 1.6%. There was no association between CSD and sex (P = .2). Deaf Border Collies had higher rates of merle coat pigmentation, blue iris pigment, and excess white on the head than normal hearing Border Collies (all P < .001). The odds of deafness were increased by a factor of 14 for Border Collies with deaf dams, relative to the odds for dogs with normal dams (P = .007), after adjustment for phenotypic attributes. Associations between CSD and pigmentation patterns linked to the merle gene were demonstrated for Border Collies. Evidence for an inherited component to CSD in Border Collies supports selective breeding from only tested and normal parents to reduce the prevalence of this disease.

Defining the cause of skewed X-chromosome inactivation in X-linked mental retardation by use of a mouse model.

PubMed

Muers, Mary R; Sharpe, Jacqueline A; Garrick, David; Sloane-Stanley, Jacqueline; Nolan, Patrick M; Hacker, Terry; Wood, William G; Higgs, Douglas R; Gibbons, Richard J

2007-06-01

Extreme skewing of X-chromosome inactivation (XCI) is rare in the normal female population but is observed frequently in carriers of some X-linked mutations. Recently, it has been shown that various forms of X-linked mental retardation (XLMR) have a strong association with skewed XCI in female carriers, but the mechanisms underlying this skewing are unknown. ATR-X syndrome, caused by mutations in a ubiquitously expressed, chromatin-associated protein, provides a clear example of XLMR in which phenotypically normal female carriers virtually all have highly skewed XCI biased against the X chromosome that harbors the mutant allele. Here, we have used a mouse model to understand the processes causing skewed XCI. In female mice heterozygous for a null Atrx allele, we found that XCI is balanced early in embryogenesis but becomes skewed over the course of development, because of selection favoring cells expressing the wild-type Atrx allele. Unexpectedly, selection does not appear to be the result of general cellular-viability defects in Atrx-deficient cells, since it is restricted to specific stages of development and is not ongoing throughout the life of the animal. Instead, there is evidence that selection results from independent tissue-specific effects. This illustrates an important mechanism by which skewed XCI may occur in carriers of XLMR and provides insight into the normal role of ATRX in regulating cell fate.

Fanconi anemia links reactive oxygen species to insulin resistance and obesity.

PubMed

Li, Jie; Sipple, Jared; Maynard, Suzette; Mehta, Parinda A; Rose, Susan R; Davies, Stella M; Pang, Qishen

2012-10-15

Insulin resistance is a hallmark of obesity and type 2 diabetes. Reactive oxygen species (ROS) have been proposed to play a causal role in insulin resistance. However, evidence linking ROS to insulin resistance in disease settings has been scant. Since both oxidative stress and diabetes have been observed in patients with the Fanconi anemia (FA), we sought to investigate the link between ROS and insulin resistance in this unique disease model. Mice deficient for the Fanconi anemia complementation group A (Fanca) or Fanconi anemia complementation group C (Fancc) gene seem to be diabetes-prone, as manifested by significant hyperglycemia and hyperinsulinemia, and rapid weight gain when fed with a high-fat diet. These phenotypic features of insulin resistance are characterized by two critical events in insulin signaling: a reduction in tyrosine phosphorylation of the insulin receptor (IR) and an increase in inhibitory serine phosphorylation of the IR substrate-1 in the liver, muscle, and fat tissues from the insulin-challenged FA mice. High levels of ROS, spontaneously accumulated or generated by tumor necrosis factor alpha in these insulin-sensitive tissues of FA mice, were shown to underlie the FA insulin resistance. Treatment of FA mice with the natural anti-oxidant Quercetin restores IR signaling and ameliorates the diabetes- and obesity-prone phenotypes. Finally, pairwise screen identifies protein-tyrosine phosphatase (PTP)-α and stress kinase double-stranded RNA-dependent protein kinase (PKR) that mediate the ROS effect on FA insulin resistance. These findings establish a pathogenic and mechanistic link between ROS and insulin resistance in a unique human disease setting. ROS accumulation contributes to the insulin resistance in FA deficiency by targeting both PTP-α and PKR.

Topological versus rheological entanglement length in primitive-path analysis protocols, tube models, and slip-link models

NASA Astrophysics Data System (ADS)

Everaers, Ralf

2012-08-01

We show that the front factor appearing in the shear modulus of a phantom network, Gph=(1-2/f)(ρkBT)/Ns, also controls the ratio of the strand length, Ns, and the number of monomers per Kuhn length of the primitive paths, NphPPKuhn, characterizing the average network conformation. In particular, NphPPKuhn=Ns/(1-2/f) and Gph=(ρkBT)/NphPPKuhn. Neglecting the difference between cross-links and slip-links, these results can be transferred to entangled systems and the interpretation of primitive path analysis data. In agreement with the tube model, the analogy to phantom networks suggest that the rheological entanglement length, Nerheo=(ρkBT)/Ge, should equal NePPKuhn. Assuming binary entanglements with f=4 functional junctions, we expect that Nerheo should be twice as large as the topological entanglement length, Netopo. These results are in good agreement with reported primitive path analysis results for model systems and a wide range of polymeric materials. Implications for tube and slip-link models are discussed.

Mouse breast cancer model-dependent changes in metabolic syndrome-associated phenotypes caused by maternal dioxin exposure and dietary fat

PubMed Central

La Merrill, Michele; Baston, David S.; Denison, Michael S.; Birnbaum, Linda S.; Pomp, Daniel; Threadgill, David W.

2009-01-01

Diets high in fat are associated with increased susceptibility to obesity and metabolic syndrome. Increased adipose tissue that is caused by high-fat diets (HFD) results in altered storage of lipophilic toxicants like 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), which may further increase susceptibility to metabolic syndrome. Because both TCDD and HFD are associated with increased breast cancer risk, we examined their effects on metabolic syndrome-associated phenotypes in three mouse models of breast cancer: 7,12-dimethylbenz[a]anthracene (DMBA), Tg(MMTV-Neu)202Mul/J (HER2), and TgN(MMTV-PyMT)634Mul/J (PyMT), all on an FVB/N genetic background. Pregnant mice dosed with 1 μg/kg of TCDD or vehicle on gestational day 12.5 were placed on a HFD or low-fat diet (LFD) at parturition. Body weights, percent body fat, and fasting blood glucose were measured longitudinally, and triglycerides were measured at study termination. On HFD, all cancer models reached the pubertal growth spurt ahead of FVB controls. Among mice fed HFD, the HER2 model had a greater increase in body weight and adipose tissue from puberty through adulthood compared with the PyMT and DMBA models. However, the DMBA model consistently had higher fasting blood glucose levels than the PyMT and HER2 models. TCDD only impacted serum triglycerides in the PyMT model maintained on HFD. Because the estrogenic activity of the HFD was three times lower than that of the LFD, differential dietary estrogenic activities did not drive the observed phenotypic differences. Rather, the HFD-dependent changes were cancer model dependent. These results show that cancer models can have differential effects on metabolic syndrome-associated phenotypes even before cancers arise. PMID:18840765

Pricing of premiums for equity-linked life insurance based on joint mortality models

NASA Astrophysics Data System (ADS)

Riaman; Parmikanti, K.; Irianingsih, I.; Supian, S.

2018-03-01

Life insurance equity - linked is a financial product that not only offers protection, but also investment. The calculation of equity-linked life insurance premiums generally uses mortality tables. Because of advances in medical technology and reduced birth rates, it appears that the use of mortality tables is less relevant in the calculation of premiums. To overcome this problem, we use a combination mortality model which in this study is determined based on Indonesian Mortality table 2011 to determine the chances of death and survival. In this research, we use the Combined Mortality Model of the Weibull, Inverse-Weibull, and Gompertz Mortality Model. After determining the Combined Mortality Model, simulators calculate the value of the claim to be given and the premium price numerically. By calculating equity-linked life insurance premiums well, it is expected that no party will be disadvantaged due to the inaccuracy of the calculation result

Desiderata for computable representations of electronic health records-driven phenotype algorithms.

PubMed

Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Denny, Joshua C; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A

2015-11-01

Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. © The Author 2015. Published by Oxford University Press on behalf of the American Medical

The Evolution of Phenotypic Switching in Subdivided Populations

PubMed Central

Carja, Oana; Liberman, Uri; Feldman, Marcus W.

2014-01-01

Stochastic switching is an example of phenotypic bet hedging, where offspring can express a phenotype different from that of their parents. Phenotypic switching is well documented in viruses, yeast, and bacteria and has been extensively studied when the selection pressures vary through time. However, there has been little work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in determining the evolutionary dynamics of phenotypic switching. We find that the stable switching rate is mainly determined by the rate of environmental change and the migration rate. This stable rate is also a decreasing function of the recombination rate, although this is a weaker effect than those of either the period of environmental change or the migration rate. This study highlights the interplay of spatial and temporal environmental variability, offering new insights into how migration can influence the evolution of phenotypic switching rates, mutation rates, or other sources of phenotypic variation. PMID:24496012

Analysis of N- and O-linked protein glycosylation in children with Prader-Willi syndrome.

PubMed

Munce, T; Heussler, H S; Bowling, F G

2010-10-01

Current genotype-phenotype correlations in Prader-Willi syndrome (PWS) are struggling to give an explanation of the diversity in phenotype and there is a need to move towards a molecular understanding of PWS. A range of functions related to glycoproteins are involved in the pathophysiology of PWS and it may be that abnormal glycosylation is contributing to the biological phenotype. The objective of this study was to investigate the state of N- and O-linked glycosylation in children with Prader-Willi syndrome. Twenty-three children with PWS and 20 non-PWS controls were included in the study. Protein N-linked glycosylation was assessed by analysing serum transferrin through mass spectrometry and protein O-linked through isoelectric focusing (IEF) of serum apolipoprotein C-III (apoC-III), confirmed by mass spectrometry. The results of this analysis indicated that the N-linked glycosylation pathway in PWS is normal. A subgroup of PWS individuals was found to have a hyposialylated pattern of apoC-III isoforms. This was independent of the underlying genetic mechanism and is the first report of an apoC-III IEF abnormality in PWS. This is the first report of apoC-III hyposialylation in PWS. As this field is in its infancy, additional study is required before these findings may be used in clinical settings. © 2010 The Authors. Journal of Intellectual Disability Research © 2010 Blackwell Publishing Ltd.

Tag-mediated cooperation with non-deterministic genotype-phenotype mapping

NASA Astrophysics Data System (ADS)

Zhang, Hong; Chen, Shu

2016-01-01

Tag-mediated cooperation provides a helpful framework for resolving evolutionary social dilemmas. However, most of the previous studies have not taken into account genotype-phenotype distinction in tags, which may play an important role in the process of evolution. To take this into consideration, we introduce non-deterministic genotype-phenotype mapping into a tag-based model with spatial prisoner's dilemma. By our definition, the similarity between genotypic tags does not directly imply the similarity between phenotypic tags. We find that the non-deterministic mapping from genotypic tag to phenotypic tag has non-trivial effects on tag-mediated cooperation. Although we observe that high levels of cooperation can be established under a wide variety of conditions especially when the decisiveness is moderate, the uncertainty in the determination of phenotypic tags may have a detrimental effect on the tag mechanism by disturbing the homophilic interaction structure which can explain the promotion of cooperation in tag systems. Furthermore, the non-deterministic mapping may undermine the robustness of the tag mechanism with respect to various factors such as the structure of the tag space and the tag flexibility. This observation warns us about the danger of applying the classical tag-based models to the analysis of empirical phenomena if genotype-phenotype distinction is significant in real world. Non-deterministic genotype-phenotype mapping thus provides a new perspective to the understanding of tag-mediated cooperation.

Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

PubMed Central

Umek, Lan; Fonseca, Elza; Drumonde-Neves, João; Dequin, Sylvie; Zupan, Blaz; Schuller, Dorit

2013-01-01

Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40°C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection

Linking disease symptoms and subtypes with personalized systems-based phenotypes: A proof of concept study

PubMed Central

Aschbacher, Kirstin; Adam, Emma K.; Crofford, Leslie J.; Kemeny, Margaret E.; Demitrack, Mark A.; Ben-Zvi, Amos

2012-01-01

A dynamic systems model was used to generate parameters describing a phenotype of Hypothalamic–Pituitary–Adrenal (HPA) behavior in a sample of 36 patients with chronic fatigue syndrome (CFS) and/ or fibromyalgia (FM) and 36 case-matched healthy controls. Altered neuroendocrine function, particularly in relation to somatic symptoms and poor sleep quality, may contribute to the pathophysiology of these disorders. Blood plasma was assayed for cortisol and ACTH every 10 min for 24 h. The dynamic model was specified with an ordinary differential equation using three parameters: (1) ACTH-adrenal signaling, (2) inhibitory feedback, and (3) non-ACTH influences. The model was ‘‘personalized’’ by estimating an individualized set of parameters from each participant’s data. Day and nighttime parameters were assessed separately. Two nocturnal parameters (ACTH-adrenal signaling and inhibitory feedback) significantly differentiated the two patient subgroups (“fatigue-predominant” patients with CFS only versus ‘‘pain-predominant’’ patients with FM and comorbid chronic fatigue) from controls (allp’s < .05), whereas daytime parameters and diurnal/nocturnal slopes did not. The same nocturnal parameters were significantly associated with somatic symptoms among patients (p’s < .05). There was a significantly different pattern of association between nocturnal non-ACTH influences and sleep quality among patients versus controls (p < .05). Although speculative, the finding that patient somatic symptoms decreased when more cortisol was produced per unit ACTH, is consistent with cortisol’s anti-inflammatory and sleep-modulatory effects. Patients’ HPA systems may compensate by promoting more rapid or sustained cortisol production. Mapping “behavioral phenotypes” of stress–arousal systems onto symptom clusters may help disentangle the pathophysiology of complex disorders with frequent comorbidity. PMID:22687333

Recurrent postural vasovagal syncope: sympathetic nervous system phenotypes.

PubMed

Vaddadi, Gautam; Guo, Ling; Esler, Murray; Socratous, Florentia; Schlaich, Markus; Chopra, Reena; Eikelis, Nina; Lambert, Gavin; Trauer, Thomas; Lambert, Elisabeth

2011-10-01

The pathophysiology of vasovagal syncope is poorly understood, and the treatment usually ineffective. Our clinical experience is that patients with vasovagal syncope fall into 2 groups, based on their supine systolic blood pressure, which is either normal (>100 mm Hg) or low (70-100 mm Hg). We investigated neural circulatory control in these 2 phenotypes. Sympathetic nervous testing was at 3 levels: electric, measuring sympathetic nerve firing (microneurography); neurochemical, quantifying norepinephrine spillover to plasma; and cellular, with Western blot analysis of sympathetic nerve proteins. Testing was done during head-up tilt (HUT), simulating the gravitational stress of standing, in 18 healthy control subjects and 36 patients with vasovagal syncope, 15 with the low blood pressure phenotype and 21 with normal blood pressure. Microneurography and norepinephrine spillover increased significantly during HUT in healthy subjects. The microneurography response during HUT was normal in normal blood pressure and accentuated in low blood pressure phenotype (P=0.05). Norepinephrine spillover response was paradoxically subnormal during HUT in both patient groups (P=0.001), who thus exhibited disjunction between nerve firing and neurotransmitter release; this lowered norepinephrine availability, impairing the neural circulatory response. Subnormal norepinephrine spillover in low blood pressure phenotype was linked to low tyrosine hydroxylase (43.7% normal, P=0.001), rate-limiting in norepinephrine synthesis, and in normal blood pressure to increased levels of the norepinephrine transporter (135% normal, P=0.019), augmenting transmitter reuptake. Patients with recurrent vasovagal syncope, when phenotyped into 2 clinical groups based on their supine blood pressure, show unique sympathetic nervous system abnormalities. It is predicted that future therapy targeting the specific mechanisms identified in the present report should translate into more effective treatment.

Phenotypic modulation of corpus cavernosum smooth muscle cells in a rat model of cavernous neurectomy.

PubMed

Yang, Fan; Zhao, Jian F; Shou, Qi Y; Huang, Xiao J; Chen, Gang; Yang, Ke B; Zhang, Shi G; Lv, Bo D; Fu, Hui Y

2014-01-01

Patients undergoing radical prostatectomy (RP) are at high risk for erectile dysfunction (ED) due to potential cavernous nerve (CN) damage during surgery. Penile hypoxia after RP is thought to significantly contribute to ED pathogenesis. We previously showed that corpora cavernosum smooth muscle cells (CCSMCs) undergo phenotypic modulation under hypoxic conditions in vitro. Here, we studied such changes in an in vivo post-RP ED model by investigating CCSMCs in bilateral cavernous neurectomy (BCN) rats. Sprague-Dawley rats underwent sham (n = 12) or BCN (n = 12) surgery. After 12 weeks, they were injected with apomorphine to determine erectile function. The penile tissues were harvested and assessed for fibrosis using Masson trichrome staining and for molecular markers of phenotypic modulation using immunohistochemistry and western blotting. CCSMC morphological structure was evaluated by hematoxylin-eosin (H&E) staining and transmission electron microscopy (TEM). Erectile function was significantly lower in BCN rats than in sham rats. BCN increased hypoxia-inducible factor-1α and collagen protein expression in corpora cavernous tissue. H&E staining and TEM showed that CCSMCs in BCN rats underwent hypertrophy and showed rough endoplasmic reticulum formation. The expression of CCSMC phenotypic markers, such as smooth muscle α-actin, smooth muscle myosin heavy chain, and desmin, was markedly lower, whereas vimentin protein expression was significantly higher in BCN rats than in control rats. CCSMCs undergo phenotype modulation in rats with cavernous neurectomy. The results have unveiled physiological transformations that occur at the cellular and molecular levels and have helped characterize CN injury-induced ED.

Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype.

PubMed

Fernandez-de-Cossio-Diaz, Jorge; De Martino, Andrea; Mulet, Roberto

2017-06-08

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient reservoir (the blood), aimed at characterizing the role of the microenvironment for aberrant growth. Accounting for cellular metabolic activity, competition for nutrients, spatial diffusion and their feedbacks on aberrant replication and death rates, we obtain a phase portrait where distinct asymptotic whole-tissue states are found upon varying the tissue-blood turnover rate and the level of blood-borne primary nutrient. Over a broad range of parameters, the spreading dynamics is bistable as random fluctuations can impact the final state of the tissue. Such a behaviour turns out to be linked to the re-cycling of overflow products by non-aberrant cells. Quantitative insight on the overall emerging picture is provided by a spatially homogeneous version of the model.

Physical Model of the Genotype-to-Phenotype Map of Proteins

NASA Astrophysics Data System (ADS)

Tlusty, Tsvi; Libchaber, Albert; Eckmann, Jean-Pierre

2017-04-01

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to function. We therefore treat protein as learning amorphous matter that evolves towards such a mechanical function: Genes are binary sequences that encode the connectivity of the amino acid network that makes a protein. The gene is evolved until the network forms a shear band across the protein, which allows for long-range, soft modes required for protein function. The evolution reduces the high-dimensional sequence space to a low-dimensional space of mechanical modes, in accord with the observed dimensional reduction between genotype and phenotype of proteins. Spectral analysis of the space of 1 06 solutions shows a strong correspondence between localization around the shear band of both mechanical modes and the sequence structure. Specifically, our model shows how mutations are correlated among amino acids whose interactions determine the functional mode.

Identification of Genetic Loci Underlying the Phenotypic Constructs of Autism Spectrum Disorders

ERIC Educational Resources Information Center

Liu, Xiao-Qing; Georgiades, Stelios; Duku, Eric; Thompson, Ann; Devlin, Bernie; Cook, Edwin H.; Wijsman, Ellen M.; Paterson, Andrew D.; Szatmari, Peter

2011-01-01

Objective: To investigate the underlying phenotypic constructs in autism spectrum disorders (ASD) and to identify genetic loci that are linked to these empirically derived factors. Method: Exploratory factor analysis was applied to two datasets with 28 selected Autism Diagnostic Interview-Revised (ADI-R) algorithm items. The first dataset was from…

Vision-based stress estimation model for steel frame structures with rigid links

NASA Astrophysics Data System (ADS)

Park, Hyo Seon; Park, Jun Su; Oh, Byung Kwan

2017-07-01

This paper presents a stress estimation model for the safety evaluation of steel frame structures with rigid links using a vision-based monitoring system. In this model, the deformed shape of a structure under external loads is estimated via displacements measured by a motion capture system (MCS), which is a non-contact displacement measurement device. During the estimation of the deformed shape, the effective lengths of the rigid link ranges in the frame structure are identified. The radius of the curvature of the structural member to be monitored is calculated using the estimated deformed shape and is employed to estimate stress. Using MCS in the presented model, the safety of a structure can be assessed gauge-freely. In addition, because the stress is directly extracted from the radius of the curvature obtained from the measured deformed shape, information on the loadings and boundary conditions of the structure are not required. Furthermore, the model, which includes the identification of the effective lengths of the rigid links, can consider the influences of the stiffness of the connection and support on the deformation in the stress estimation. To verify the applicability of the presented model, static loading tests for a steel frame specimen were conducted. By comparing the stress estimated by the model with the measured stress, the validity of the model was confirmed.

Linking Air Quality and Watershed Models for Environmental Assessments: Analysis of the Effects of Model-Specific Precipitation Estimates on Calculated Water Flux

EPA Science Inventory

Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each mod...

Accuracy test for link prediction in terms of similarity index: The case of WS and BA models

NASA Astrophysics Data System (ADS)

Ahn, Min-Woo; Jung, Woo-Sung

2015-07-01

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barabási-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

SIRT1 overexpression ameliorates a mouse model of SOD1-linked amyotrophic lateral sclerosis via HSF1/HSP70i chaperone system.

PubMed

Watanabe, Seiji; Ageta-Ishihara, Natsumi; Nagatsu, Shinji; Takao, Keizo; Komine, Okiru; Endo, Fumito; Miyakawa, Tsuyoshi; Misawa, Hidemi; Takahashi, Ryosuke; Kinoshita, Makoto; Yamanaka, Koji

2014-08-29

Dominant mutations in superoxide dismutase 1 (SOD1) cause degeneration of motor neurons in a subset of inherited amyotrophic lateral sclerosis (ALS). The pathogenetic process mediated by misfolded and/or aggregated mutant SOD1 polypeptides is hypothesized to be suppressed by protein refolding. This genetic study is aimed to test whether mutant SOD1-mediated ALS pathology recapitulated in mice could be alleviated by overexpressing a longevity-related deacetylase SIRT1 whose substrates include a transcription factor heat shock factor 1 (HSF1), the master regulator of the chaperone system. We established a line of transgenic mice that chronically overexpress SIRT1 in the brain and spinal cord. While inducible HSP70 (HSP70i) was upregulated in the spinal cord of SIRT1 transgenic mice (PrP-Sirt1), no neurological and behavioral alterations were detected. To test hypothetical benefits of SIRT1 overexpression, we crossbred PrP-Sirt1 mice with two lines of ALS model mice: A high expression line that exhibits a severe phenotype (SOD1G93A-H) or a low expression line with a milder phenotype (SOD1G93A-L). The Sirt1 transgene conferred longer lifespan without altering the time of symptomatic onset in SOD1G93A-L. Biochemical analysis of the spinal cord revealed that SIRT1 induced HSP70i expression through deacetylation of HSF1 and that SOD1G93A-L/PrP-Sirt1 double transgenic mice contained less insoluble SOD1 than SOD1G93A-L mice. Parallel experiments showed that Sirt1 transgene could not rescue a more severe phenotype of SOD1G93A-H transgenic mice partly because their HSP70i level had peaked out. The genetic supplementation of SIRT1 can ameliorate a mutant SOD1-linked ALS mouse model partly through the activation of the HSF1/HSP70i chaperone system. Future studies shall include testing potential benefits of pharmacological enhancement of the deacetylation activity of SIRT1 after the onset of the symptom.

The Immature Fiber Mutant Phenotype of Cotton (Gossypium hirsutum) Is Linked to a 22-bp Frame-Shift Deletion in a Mitochondria Targeted Pentatricopeptide Repeat Gene.

PubMed

Thyssen, Gregory N; Fang, David D; Zeng, Linghe; Song, Xianliang; Delhom, Christopher D; Condon, Tracy L; Li, Ping; Kim, Hee Jin

2016-06-01

Cotton seed trichomes are the most important source of natural fibers globally. The major fiber thickness properties influence the price of the raw material, and the quality of the finished product. The recessive immature fiber (im) gene reduces the degree of fiber cell wall thickening by a process that was previously shown to involve mitochondrial function in allotetraploid Gossypium hirsutum Here, we present the fine genetic mapping of the im locus, gene expression analysis of annotated proteins near the locus, and association analysis of the linked markers. Mapping-by-sequencing identified a 22-bp deletion in a pentatricopeptide repeat (PPR) gene that is completely linked to the immature fiber phenotype in 2837 F2 plants, and is absent from all 163 cultivated varieties tested, although other closely linked marker polymorphisms are prevalent in the diversity panel. This frame-shift mutation results in a transcript with two long open reading frames: one containing the N-terminal transit peptide that targets mitochondria, the other containing only the RNA-binding PPR domains, suggesting that a functional PPR protein cannot be targeted to mitochondria in the im mutant. Taken together, these results suggest that PPR gene Gh_A03G0489 is involved in the cotton fiber wall thickening process, and is a promising candidate gene at the im locus. Our findings expand our understanding of the molecular mechanisms that modulate cotton fiber fineness and maturity, and may facilitate the development of cotton varieties with superior fiber attributes. Copyright © 2016 Thyssen et al.

Linking agent-based models and stochastic models of financial markets

PubMed Central

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

2012-01-01

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

Linking agent-based models and stochastic models of financial markets.

PubMed

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Accelerating glioblastoma drug discovery: Convergence of patient-derived models, genome editing and phenotypic screening.

PubMed

O'Duibhir, Eoghan; Carragher, Neil O; Pollard, Steven M

2017-04-01

Patients diagnosed with glioblastoma (GBM) continue to face a bleak prognosis. It is critical that new effective therapeutic strategies are developed. GBM stem cells have molecular hallmarks of neural stem and progenitor cells and it is possible to propagate both non-transformed normal neural stem cells and GBM stem cells, in defined, feeder-free, adherent culture. These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities. For many solid tumours, including GBM, the genetic disruptions that drive tumour initiation and growth have now been catalogued. CRISPR/Cas-based genome editing technologies have recently emerged, transforming our ability to functionally annotate the human genome. Genome editing opens prospects for engineering precise genetic changes in normal and GBM-derived neural stem cells, which will provide more defined and reliable genetic models, with critical matched pairs of isogenic cell lines. Generation of more complex alleles such as knock in tags or fluorescent reporters is also now possible. These new cellular models can be deployed in cell-based phenotypic drug discovery (PDD). Here we discuss the convergence of these advanced technologies (iPS cells, neural stem cell culture, genome editing and high content phenotypic screening) and how they herald a new era in human cellular genetics that should have a major impact in accelerating glioblastoma drug discovery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Mutations in chromatin regulators functionally link Cornelia de Lange syndrome and clinically overlapping phenotypes.

PubMed

Parenti, Ilaria; Teresa-Rodrigo, María E; Pozojevic, Jelena; Ruiz Gil, Sara; Bader, Ingrid; Braunholz, Diana; Bramswig, Nuria C; Gervasini, Cristina; Larizza, Lidia; Pfeiffer, Lutz; Ozkinay, Ferda; Ramos, Feliciano; Reiz, Benedikt; Rittinger, Olaf; Strom, Tim M; Watrin, Erwan; Wendt, Kerstin; Wieczorek, Dagmar; Wollnik, Bernd; Baquero-Montoya, Carolina; Pié, Juan; Deardorff, Matthew A; Gillessen-Kaesbach, Gabriele; Kaiser, Frank J

2017-03-01

The coordinated tissue-specific regulation of gene expression is essential for the proper development of all organisms. Mutations in multiple transcriptional regulators cause a group of neurodevelopmental disorders termed "transcriptomopathies" that share core phenotypical features including growth retardation, developmental delay, intellectual disability and facial dysmorphism. Cornelia de Lange syndrome (CdLS) belongs to this class of disorders and is caused by mutations in different subunits or regulators of the cohesin complex. Herein, we report on the clinical and molecular characterization of seven patients with features overlapping with CdLS who were found to carry mutations in chromatin regulators previously associated to other neurodevelopmental disorders that are frequently considered in the differential diagnosis of CdLS. The identified mutations affect the methyltransferase-encoding genes KMT2A and SETD5 and different subunits of the SWI/SNF chromatin-remodeling complex. Complementary to this, a patient with Coffin-Siris syndrome was found to carry a missense substitution in NIPBL. Our findings indicate that mutations in a variety of chromatin-associated factors result in overlapping clinical phenotypes, underscoring the genetic heterogeneity that should be considered when assessing the clinical and molecular diagnosis of neurodevelopmental syndromes. It is clear that emerging molecular mechanisms of chromatin dysregulation are central to understanding the pathogenesis of these clinically overlapping genetic disorders.

PHENOPSIS DB: an Information System for Arabidopsis thaliana phenotypic data in an environmental context

PubMed Central

2011-01-01

Background Renewed interest in plant × environment interactions has risen in the post-genomic era. In this context, high-throughput phenotyping platforms have been developed to create reproducible environmental scenarios in which the phenotypic responses of multiple genotypes can be analysed in a reproducible way. These platforms benefit hugely from the development of suitable databases for storage, sharing and analysis of the large amount of data collected. In the model plant Arabidopsis thaliana, most databases available to the scientific community contain data related to genetic and molecular biology and are characterised by an inadequacy in the description of plant developmental stages and experimental metadata such as environmental conditions. Our goal was to develop a comprehensive information system for sharing of the data collected in PHENOPSIS, an automated platform for Arabidopsis thaliana phenotyping, with the scientific community. Description PHENOPSIS DB is a publicly available (URL: http://bioweb.supagro.inra.fr/phenopsis/) information system developed for storage, browsing and sharing of online data generated by the PHENOPSIS platform and offline data collected by experimenters and experimental metadata. It provides modules coupled to a Web interface for (i) the visualisation of environmental data of an experiment, (ii) the visualisation and statistical analysis of phenotypic data, and (iii) the analysis of Arabidopsis thaliana plant images. Conclusions Firstly, data stored in the PHENOPSIS DB are of interest to the Arabidopsis thaliana community, particularly in allowing phenotypic meta-analyses directly linked to environmental conditions on which publications are still scarce. Secondly, data or image analysis modules can be downloaded from the Web interface for direct usage or as the basis for modifications according to new requirements. Finally, the structure of PHENOPSIS DB provides a useful template for the development of other similar

Metabolic parameters linked by Phenotype MicroArray to acid resistance profiles of poultry-associated Salmonella enterica.

USDA-ARS?s Scientific Manuscript database

Phenotype microarrays were analyzed for 51 datasets derived from Salmonella enterica. The top 4 serovars associated with poultry products and one associated with turkey, respectively Typhimurium, Enteritidis, Heidelberg, Infantis and Senftenberg, were represented. Datasets were clustered into two ...

Vitamin D treatment during pregnancy prevents autism-related phenotypes in a mouse model of maternal immune activation.

PubMed

Vuillermot, Stephanie; Luan, Wei; Meyer, Urs; Eyles, Darryl

2017-01-01

Prenatal exposure to infection is a recognized environmental risk factor for neuropsychiatric disorders of developmental origins such as autism or schizophrenia. Experimental work in animals indicates that this link is mediated by maternal immune activation (MIA) involving interactions between cytokine-associated inflammatory events, oxidative stress, and other pathophysiological processes such as hypoferremia and zinc deficiency. Maternal administration of the viral mimic polyriboinosinic-polyribocytidylic acid (poly(I:C)) in mice produces several behavioral phenotypes in adult offspring of relevance to autism spectrum disorder (ASD) and other neurodevelopmental disorders. Here, we investigated whether some of these phenotypes might also present in juveniles. In addition, given the known immunomodulatory and neuroprotective effects of vitamin D, we also investigated whether the co-administration of vitamin D could block MIA-induced ASD-related behaviors. We co-administered the hormonally active form of vitamin D, 1α,25 dihydroxy vitamin D3 (1,25OHD), simultaneously with poly(I:C) and examined (i) social interaction, stereotyped behavior, emotional learning and memory, and innate anxiety-like behavior in juveniles and (ii) the levels of the pro-inflammatory cytokines IL-1β, IL-6 and TNF-α in maternal plasma and fetal brains. We show that like adult offspring that were exposed to MIA, juveniles display similar deficits in social approach behavior. Juvenile MIA offspring also show abnormal stereotyped digging and impaired acquisition and expression of tone-cued fear conditioning. Importantly, our study reveals that prenatal administration of 1,25OHD abolishes all these behavioral deficits in poly(I:C)-treated juveniles. However, prenatal administration of vitamin D had no effect on pro-inflammatory cytokine levels in dams or in fetal brains suggesting the anti-inflammatory actions of vitamin D are not the critical mechanism for its preventive actions in this ASD

Creation of a national resource with linked genealogy and phenotypic data: the Veterans Genealogy Project.

PubMed

Cannon-Albright, Lisa A; Dintelman, Sue; Maness, Tim; Backus, Steve; Thomas, Alun; Meyer, Laurence J

2013-07-01

Creation of a genealogy of the United States and its ancestral populations is under way. When complete, this US genealogy will be record linked to the National Veteran's Health Administration medical data representing more than 8 million US veterans. Genealogical data are gathered from public sources, primarily the Internet. Record linking using data from relatives is accomplished to integrate multiple data sources and then to link genealogical data to the veteran's demographic data. This resource currently includes genealogy for more than 22 million individuals representing the Intermountain West and the East Coast. The demographic data for more than 40,000 veteran patients using Veterans Hospital Administration services in Utah and Massachusetts have already been record linked. The resource is only in its second year of creation and already represents the largest such combination of genealogy and medical data in the world. The data sources, the creation of the genealogy, record-linking methods and results, proposed genetic analyses, and future directions are discussed.

Wine Expertise Predicts Taste Phenotype.

PubMed

Hayes, John E; Pickering, Gary J

2012-03-01

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

LINKING THE CMAQ AND HYSPLIT MODELING SYSTEM INTERFACE PROGRAM AND EXAMPLE APPLICATION

EPA Science Inventory

A new software tool has been developed to link the Eulerian-based Community Multiscale Air Quality (CMAQ) modeling system with the Lagrangian-based HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model. Both models require many of the same hourly meteorological...

Advanced transgenic approaches to understand alcohol-related phenotypes in animals.

PubMed

Bilbao, Ainhoa

2013-01-01

During the past two decades, the use of genetically manipulated animal models in alcohol research has greatly improved the understanding of the mechanisms underlying alcohol addiction. In this chapter, we present an overview of the progress made in this field by summarizing findings obtained from studies of mice harboring global and conditional mutations in genes that influence alcohol-related phenotypes. The first part reviews behavioral paradigms for modeling the different phases of the alcohol addiction cycle and other alcohol-induced behavioral phenotypes in mice. The second part reviews the current data available using genetic models targeting the main neurotransmitter and neuropeptide systems involved in the reinforcement and stress pathways, focusing on the phenotypes modeling the alcohol addiction cycle. Finally, the third part will discuss the current findings and future directions, and proposes advanced transgenic mouse models for their potential use in alcohol research.

Random phenotypic variation of yeast (Saccharomyces cerevisiae) single-gene knockouts fits a double pareto-lognormal distribution.

PubMed

Graham, John H; Robb, Daniel T; Poe, Amy R

2012-01-01

Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighboring nodes. This suggests a probability distribution approximating an inverse power-law of random phenotypic variation. Zero phenotypic variation, however, is impossible, because random molecular and cellular processes are essential to normal development. Consequently, a more realistic distribution should have a y-intercept close to zero in the lower tail, a mode greater than zero, and a long (fat) upper tail. The double Pareto-lognormal (DPLN) distribution is an ideal candidate distribution. It consists of a mixture of a lognormal body and upper and lower power-law tails. If our assumptions are true, the DPLN distribution should provide a better fit to random phenotypic variation in a large series of single-gene knockout lines than other skewed or symmetrical distributions. We fit a large published data set of single-gene knockout lines in Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal (RPLN), left Pareto-lognormal (LPLN), normal, lognormal, exponential, and Pareto. The best model was judged by the Akaike Information Criterion (AIC). Phenotypic variation among gene knockouts in S. cerevisiae fits a double Pareto-lognormal (DPLN) distribution better than any of the alternative distributions, including the right Pareto-lognormal and lognormal distributions. A DPLN distribution is consistent with the hypothesis that developmental stability is mediated, in part, by distributed robustness, the resilience of gene regulatory, metabolic, and protein-protein interaction networks. Alternatively, multiplicative cell growth, and the mixing of

New phenotypes for new breeding goals in pigs.

PubMed

Merks, J W M; Mathur, P K; Knol, E F

2012-04-01

Pig breeders in the past have adopted their breeding goals according to the needs of the producers, processors and consumers and have made remarkable genetic improvements in the traits of interest. However, it is becoming more and more challenging to meet the market needs and expectations of consumers and in general of the citizens. In view of the current and future trends, the breeding goals have to include several additional traits and new phenotypes. These phenotypes include (a) vitality from birth to slaughter, (b) uniformity at different levels of production, (c) robustness, (d) welfare and health and (e) phenotypes to reduce carbon footprint. Advancements in management, genomics, statistical models and other technologies provide opportunities for recording these phenotypes. These new developments also provide opportunities for making effective use of the new phenotypes for faster genetic improvement to meet the newly adapted breeding goals.

Swine Influenza Virus PA and Neuraminidase Gene Reassortment into Human H1N1 Influenza Virus Is Associated with an Altered Pathogenic Phenotype Linked to Increased MIP-2 Expression.

PubMed

Dlugolenski, Daniel; Jones, Les; Howerth, Elizabeth; Wentworth, David; Tompkins, S Mark; Tripp, Ralph A

2015-05-01

Swine are susceptible to infection by both avian and human influenza viruses, and this feature is thought to contribute to novel reassortant influenza viruses. In this study, the influenza virus reassortment rate in swine and human cells was determined. Coinfection of swine cells with 2009 pandemic H1N1 virus (huH1N1) and an endemic swine H1N2 (A/swine/Illinois/02860/09) virus (swH1N2) resulted in a 23% reassortment rate that was independent of α2,3- or α2,6-sialic acid distribution on the cells. The reassortants had altered pathogenic phenotypes linked to introduction of the swine virus PA and neuraminidase (NA) into huH1N1. In mice, the huH1N1 PA and NA mediated increased MIP-2 expression early postinfection, resulting in substantial pulmonary neutrophilia with enhanced lung pathology and disease. The findings support the notion that swine are a mixing vessel for influenza virus reassortants independent of sialic acid distribution. These results show the potential for continued reassortment of the 2009 pandemic H1N1 virus with endemic swine viruses and for reassortants to have increased pathogenicity linked to the swine virus NA and PA genes which are associated with increased pulmonary neutrophil trafficking that is related to MIP-2 expression. Influenza A viruses can change rapidly via reassortment to create a novel virus, and reassortment can result in possible pandemics. Reassortments among subtypes from avian and human viruses led to the 1957 (H2N2 subtype) and 1968 (H3N2 subtype) human influenza pandemics. Recent analyses of circulating isolates have shown that multiple genes can be recombined from human, avian, and swine influenza viruses, leading to triple reassortants. Understanding the factors that can affect influenza A virus reassortment is needed for the establishment of disease intervention strategies that may reduce or preclude pandemics. The findings from this study show that swine cells provide a mixing vessel for influenza virus reassortment

Swine Influenza Virus PA and Neuraminidase Gene Reassortment into Human H1N1 Influenza Virus Is Associated with an Altered Pathogenic Phenotype Linked to Increased MIP-2 Expression

PubMed Central

Dlugolenski, Daniel; Jones, Les; Howerth, Elizabeth; Wentworth, David; Tompkins, S. Mark

2015-01-01

ABSTRACT Swine are susceptible to infection by both avian and human influenza viruses, and this feature is thought to contribute to novel reassortant influenza viruses. In this study, the influenza virus reassortment rate in swine and human cells was determined. Coinfection of swine cells with 2009 pandemic H1N1 virus (huH1N1) and an endemic swine H1N2 (A/swine/Illinois/02860/09) virus (swH1N2) resulted in a 23% reassortment rate that was independent of α2,3- or α2,6-sialic acid distribution on the cells. The reassortants had altered pathogenic phenotypes linked to introduction of the swine virus PA and neuraminidase (NA) into huH1N1. In mice, the huH1N1 PA and NA mediated increased MIP-2 expression early postinfection, resulting in substantial pulmonary neutrophilia with enhanced lung pathology and disease. The findings support the notion that swine are a mixing vessel for influenza virus reassortants independent of sialic acid distribution. These results show the potential for continued reassortment of the 2009 pandemic H1N1 virus with endemic swine viruses and for reassortants to have increased pathogenicity linked to the swine virus NA and PA genes which are associated with increased pulmonary neutrophil trafficking that is related to MIP-2 expression. IMPORTANCE Influenza A viruses can change rapidly via reassortment to create a novel virus, and reassortment can result in possible pandemics. Reassortments among subtypes from avian and human viruses led to the 1957 (H2N2 subtype) and 1968 (H3N2 subtype) human influenza pandemics. Recent analyses of circulating isolates have shown that multiple genes can be recombined from human, avian, and swine influenza viruses, leading to triple reassortants. Understanding the factors that can affect influenza A virus reassortment is needed for the establishment of disease intervention strategies that may reduce or preclude pandemics. The findings from this study show that swine cells provide a mixing vessel for influenza

DNA variant databases improve test accuracy and phenotype prediction in Alport syndrome.

PubMed

Savige, Judy; Ars, Elisabet; Cotton, Richard G H; Crockett, David; Dagher, Hayat; Deltas, Constantinos; Ding, Jie; Flinter, Frances; Pont-Kingdon, Genevieve; Smaoui, Nizar; Torra, Roser; Storey, Helen

2014-06-01

X-linked Alport syndrome is a form of progressive renal failure caused by pathogenic variants in the COL4A5 gene. More than 700 variants have been described and a further 400 are estimated to be known to individual laboratories but are unpublished. The major genetic testing laboratories for X-linked Alport syndrome worldwide have established a Web-based database for published and unpublished COL4A5 variants ( https://grenada.lumc.nl/LOVD2/COL4A/home.php?select_db=COL4A5 ). This conforms with the recommendations of the Human Variome Project: it uses the Leiden Open Variation Database (LOVD) format, describes variants according to the human reference sequence with standardized nomenclature, indicates likely pathogenicity and associated clinical features, and credits the submitting laboratory. The database includes non-pathogenic and recurrent variants, and is linked to another COL4A5 mutation database and relevant bioinformatics sites. Access is free. Increasing the number of COL4A5 variants in the public domain helps patients, diagnostic laboratories, clinicians, and researchers. The database improves the accuracy and efficiency of genetic testing because its variants are already categorized for pathogenicity. The description of further COL4A5 variants and clinical associations will improve our ability to predict phenotype and our understanding of collagen IV biochemistry. The database for X-linked Alport syndrome represents a model for databases in other inherited renal diseases.

GBM heterogeneity characterization by radiomic analysis of phenotype anatomical planes

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

Glioblastoma multiforme (GBM) is the most common malignant primary tumor of the central nervous system, characterized among other traits by rapid metastatis. Three tissue phenotypes closely associated with GBMs, namely, necrosis (N), contrast enhancement (CE), and edema/invasion (E), exhibit characteristic patterns of texture heterogeneity in magnetic resonance images (MRI). In this study, we propose a novel model to characterize GBM tissue phenotypes using gray level co-occurrence matrices (GLCM) in three anatomical planes. The GLCM encodes local image patches in terms of informative, orientation-invariant texture descriptors, which are used here to sub-classify GBM tissue phenotypes. Experiments demonstrate the model on MRI data of 41 GBM patients, obtained from the cancer genome atlas (TCGA). Intensity-based automatic image registration is applied to align corresponding pairs of fixed T1˗weighted (T1˗WI) post-contrast and fluid attenuated inversion recovery (FLAIR) images. GBM tissue regions are then segmented using the 3D Slicer tool. Texture features are computed from 12 quantifier functions operating on GLCM descriptors, that are generated from MRI intensities within segmented GBM tissue regions. Various classifier models are used to evaluate the effectiveness of texture features for discriminating between GBM phenotypes. Results based on T1-WI scans showed a phenotype classification accuracy of over 88.14%, a sensitivity of 85.37% and a specificity of 96.1%, using the linear discriminant analysis (LDA) classifier. This model has the potential to provide important characteristics of tumors, which can be used for the sub-classification of GBM phenotypes.

Zika Virus Exhibits Lineage-Specific Phenotypes in Cell Culture, in Aedes aegypti Mosquitoes, and in an Embryo Model

PubMed Central

Demakovsky, Leah; Tesla, Blanka; Goodfellow, Forrest T.; Stice, Steven L.; Murdock, Courtney C.

2017-01-01

Zika virus (ZIKV) has quietly circulated in Africa and Southeast Asia for the past 65 years. However, the recent ZIKV epidemic in the Americas propelled this mosquito-borne virus to the forefront of flavivirus research. Based on historical evidence, ZIKV infections in Africa were sporadic and caused mild symptoms such as fever, skin rash, and general malaise. In contrast, recent Asian-lineage ZIKV infections in the Pacific Islands and the Americas are linked to birth defects and neurological disorders. The aim of this study is to compare replication, pathogenicity, and transmission efficiency of two historic and two contemporary ZIKV isolates in cell culture, the mosquito host, and an embryo model to determine if genetic variation between the African and Asian lineages results in phenotypic differences. While all tested isolates replicated at similar rates in Vero cells, the African isolates displayed more rapid viral replication in the mosquito C6/36 cell line, yet they exhibited poor infection rates in Aedes aegypti mosquitoes compared to the contemporary Asian-lineage isolates. All isolates could infect chicken embryos; however, infection with African isolates resulted in higher embryo mortality than infection with Asian-lineage isolates. These results suggest that genetic variation between ZIKV isolates can significantly alter experimental outcomes. PMID:29258204

Connectome-Wide Phenotypical and Genotypical Associations in Focal Dystonia

PubMed Central

Fuertinger, Stefan

2017-01-01

Isolated focal dystonia is a debilitating movement disorder of unknown pathophysiology. Early studies in focal dystonias have pointed to segregated changes in brain activity and connectivity. Only recently has the notion that dystonia pathophysiology may lie in abnormalities of large-scale brain networks appeared in the literature. Here, we outline a novel concept of functional connectome-wide alterations that are linked to dystonia phenotype and genotype. Using a neural community detection strategy and graph theoretical analysis of functional MRI data in human patients with the laryngeal form of dystonia (LD) and healthy controls (both males and females), we identified an abnormally widespread hub formation in LD, which particularly affected the primary sensorimotor and parietal cortices and thalamus. Left thalamic regions formed a delineated functional community that highlighted differences in network topology between LD patients with and without family history of dystonia. Conversely, marked differences in the topological organization of parietal regions were found between phenotypically different forms of LD. The interface between sporadic genotype and adductor phenotype of LD yielded four functional communities that were primarily governed by intramodular hub regions. Conversely, the interface between familial genotype and abductor phenotype was associated with numerous long-range hub nodes and an abnormal integration of left thalamus and basal ganglia. Our findings provide the first comprehensive atlas of functional topology across different phenotypes and genotypes of focal dystonia. As such, this study constitutes an important step toward defining dystonia as a large-scale network disorder, understanding its causative pathophysiology, and identifying disorder-specific markers. SIGNIFICANCE STATEMENT The architecture of the functional connectome in focal dystonia was analyzed in a large population of patients with laryngeal dystonia. Breaking with the

Links between fluid mechanics and quantum mechanics: a model for information in economics?

PubMed

Haven, Emmanuel

2016-05-28

This paper tallies the links between fluid mechanics and quantum mechanics, and attempts to show whether those links can aid in beginning to build a formal template which is usable in economics models where time is (a)symmetric and memory is absent or present. An objective of this paper is to contemplate whether those formalisms can allow us to model information in economics in a novel way. © 2016 The Author(s).

Usher syndrome: molecular links of pathogenesis, proteins and pathways.

PubMed

Kremer, Hannie; van Wijk, Erwin; Märker, Tina; Wolfrum, Uwe; Roepman, Ronald

2006-10-15

Usher syndrome is the most common form of deaf-blindness. The syndrome is both clinically and genetically heterogeneous, and to date, eight causative genes have been identified. The proteins encoded by these genes are part of a dynamic protein complex that is present in hair cells of the inner ear and in photoreceptor cells of the retina. The localization of the Usher proteins and the phenotype in animal models indicate that the Usher protein complex is essential in the morphogenesis of the stereocilia bundle in hair cells and in the calycal processes of photoreceptor cells. In addition, the Usher proteins are important in the synaptic processes of both cell types. The association of other proteins with the complex indicates functional links to a number of basic cell-biological processes. Prominently present is the connection to the dynamics of the actin cytoskeleton, involved in cellular morphology, cell polarity and cell-cell interactions. The Usher protein complex can also be linked to the cadherins/catenins in the adherens junction-associated protein complexes, suggesting a role in cell polarity and tissue organization. A third link can be established to the integrin transmembrane signaling network. The Usher interactome, as outlined in this review, participates in pathways common in inner ear and retina that are disrupted in the Usher syndrome.

Reciprocal Effects on Neurocognitive and Metabolic Phenotypes in Mouse Models of 16p11.2 Deletion and Duplication Syndromes.

PubMed

Arbogast, Thomas; Ouagazzal, Abdel-Mouttalib; Chevalier, Claire; Kopanitsa, Maksym; Afinowi, Nurudeen; Migliavacca, Eugenia; Cowling, Belinda S; Birling, Marie-Christine; Champy, Marie-France; Reymond, Alexandre; Herault, Yann

2016-02-01

The 16p11.2 600 kb BP4-BP5 deletion and duplication syndromes have been associated with developmental delay; autism spectrum disorders; and reciprocal effects on the body mass index, head circumference and brain volumes. Here, we explored these relationships using novel engineered mouse models carrying a deletion (Del/+) or a duplication (Dup/+) of the Sult1a1-Spn region homologous to the human 16p11.2 BP4-BP5 locus. On a C57BL/6N inbred genetic background, Del/+ mice exhibited reduced weight and impaired adipogenesis, hyperactivity, repetitive behaviors, and recognition memory deficits. In contrast, Dup/+ mice showed largely opposite phenotypes. On a F1 C57BL/6N × C3B hybrid genetic background, we also observed alterations in social interaction in the Del/+ and the Dup/+ animals, with other robust phenotypes affecting recognition memory and weight. To explore the dosage effect of the 16p11.2 genes on metabolism, Del/+ and Dup/+ models were challenged with high fat and high sugar diet, which revealed opposite energy imbalance. Transcriptomic analysis revealed that the majority of the genes located in the Sult1a1-Spn region were sensitive to dosage with a major effect on several pathways associated with neurocognitive and metabolic phenotypes. Whereas the behavioral consequence of the 16p11 region genetic dosage was similar in mice and humans with activity and memory alterations, the metabolic defects were opposite: adult Del/+ mice are lean in comparison to the human obese phenotype and the Dup/+ mice are overweight in comparison to the human underweight phenotype. Together, these data indicate that the dosage imbalance at the 16p11.2 locus perturbs the expression of modifiers outside the CNV that can modulate the penetrance, expressivity and direction of effects in both humans and mice.

Linkage analysis of alternative anxiety phenotypes in multiply affected panic disorder families

PubMed Central

Fyer, Abby J.; Costa, Ramiro; Haghighi, Fatemeh; Logue, Mark W.; Knowles, James A.; Weissman, Myrna M.; Hodge, Susan E.; Hamilton, Steven P.

2013-01-01

Background The choice of phenotype definitions for genetic studies of panic and phobic disorders is complicated by family, twin and neurobiological data indicating both distinct and shared risk factors as well as heterogeneity within categories. We previously reported a genome scan in 120 multiplex panic disorder (PD) families using a phenotype that closely adhered to the DSM IV PD definition. Here we extend this work by conducting exploratory linkage analyses in this same pedigree set using ten additional literature- based panic and phobia-related phenotypes that take into account aspects of these hypothesized complexities. Methods Multiply affected families (> 2 individuals with PD) were recruited from clinical and non-clinical sources, evaluated by clinician administered semi-structured interview and subsequent blind consensus best estimate procedure. Each phenotype was analyzed under dominant and recessive models using parametric 2-point (homogeneity and heterogeneity), multipoint, and non-parametric methods. Empirically based permutations were used to estimate model specific and global (across all phenotypes) p-values. Results The highest score was a 2-point lod (4.27, global p < 0.08) on chromosome 13 (D13S793, 76cM) for the phenotype “specific or social phobia” under a recessive model and conditions of homogeneity. There was minimal support for linkage to any of the remaining nine phenotypes. Conclusions Though interpretation of findings is limited by sample size and the large number of phenotypes and models analyzed these data suggest a region on chromosome 13 as a potential site for further exploration in relation to risk for specific and social phobias. PMID:22525237

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Latent constructs model explaining the attachment-linked variation in autobiographical remembering.

PubMed

Öner, Sezin; Gülgöz, Sami

2016-01-01

In the current study, we proposed a latent constructs model to characterise the qualitative aspects of autobiographical remembering and investigated the structural relations in the model that may vary across individuals. Primarily, we focused on the memories of romantic relationships and argued that attachment anxiety and avoidance would be reflected in the ways that individuals encode, rehearse, or remember autobiographical memories in close relationships. Participants reported two positive and two negative relationship-specific memories and rated the characteristics for each memory. As predicted, the basic memory model yielded appropriate fit, indicating that event characteristics (EC) predicted the frequency of rehearsal (RC) and phenomenology at retrieval (PC). When attachment variables were integrated, the model showed that rehearsal mediated the link between anxiety and PC, especially for negative memories. On the other hand, for avoidance EC was the key factor mediating the link between avoidance and RC, as well as PC. Findings were discussed with respect to autobiographical memory functions emphasising a systematically, integrated framework.

Development of a Melanoma Risk Prediction Model Incorporating MC1R Genotype and Indoor Tanning Exposure: Impact of Mole Phenotype on Model Performance

PubMed Central

Penn, Lauren A.; Qian, Meng; Zhang, Enhan; Ng, Elise; Shao, Yongzhao; Berwick, Marianne; Lazovich, DeAnn; Polsky, David

2014-01-01

Background Identifying individuals at increased risk for melanoma could potentially improve public health through targeted surveillance and early detection. Studies have separately demonstrated significant associations between melanoma risk, melanocortin receptor (MC1R) polymorphisms, and indoor ultraviolet light (UV) exposure. Existing melanoma risk prediction models do not include these factors; therefore, we investigated their potential to improve the performance of a risk model. Methods Using 875 melanoma cases and 765 controls from the population-based Minnesota Skin Health Study we compared the predictive ability of a clinical melanoma risk model (Model A) to an enhanced model (Model F) using receiver operating characteristic (ROC) curves. Model A used self-reported conventional risk factors including mole phenotype categorized as “none”, “few”, “some” or “many” moles. Model F added MC1R genotype and measures of indoor and outdoor UV exposure to Model A. We also assessed the predictive ability of these models in subgroups stratified by mole phenotype (e.g. nevus-resistant (“none” and “few” moles) and nevus-prone (“some” and “many” moles)). Results Model A (the reference model) yielded an area under the ROC curve (AUC) of 0.72 (95% CI = 0.69, 0.74). Model F was improved with an AUC = 0.74 (95% CI = 0.71–0.76, p<0.01). We also observed substantial variations in the AUCs of Models A & F when examined in the nevus-prone and nevus-resistant subgroups. Conclusions These results demonstrate that adding genotypic information and environmental exposure data can increase the predictive ability of a clinical melanoma risk model, especially among nevus-prone individuals. PMID:25003831

Phenotypic Suppression of the Gibberellin-Insensitive Mutant (gai) of Arabidopsis.

PubMed Central

Wilson, R. N.; Somerville, C. R.

1995-01-01

The semidominant gibberellin-insensitive (gai) mutant of Arabidopsis thaliana shows impairment in multiple responses to the plant hormone gibberellin A3, which include effects on seed germination, stem elongation, apical dominance, and rapid flowering in short days. Results presented here show that the gai mutation also interferes with development of fertile flowers in continuous light. Mu-tagenesis of the gai mutant resulted in recovery of 17 independent mutants in which the gibberellin-insensitive phenotype is partially or completely suppressed. Sixteen of the suppressor mutations act semidominantly to restore gibberellin responsiveness. One representative of this class, the gar1 mutation, could not be genetically separated from the gai locus and is proposed to cause inactivation of the gai gene. The exceptional gar2 mutation partially suppresses the gai phenotype, is completely dominant, and is not linked to the gai locus. The gar2 mutation may define a new gene involved in gibberellin signaling. A recessive allele of the spindly (SPY) locus, spy-5, was also found to partially suppress the gai mutant phenotype. PMID:12228487

Estrogen Metabolism and Exposure in a Genotypic-Phenotypic Model for Breast Cancer Risk Prediction

PubMed Central

Crooke, Philip S.; Justenhoven, Christina; Brauch, Hiltrud; Dawling, Sheila; Roodi, Nady; Higginbotham, Kathryn S. P.; Plummer, W. Dale; Schuyler, Peggy A.; Sanders, Melinda E; Page, David L.; Smith, Jeffrey R.; Dupont, William D.; Parl, Fritz F.

2012-01-01

Background Current models of breast cancer risk prediction do not directly reflect mammary estrogen metabolism or genetic variability in exposure to carcinogenic estrogen metabolites. Methods We developed a model that simulates the kinetic effect of genetic variants of the enzymes CYP1A1, CYP1B1, and COMT on the production of the main carcinogenic estrogen metabolite, 4-hydroxyestradiol (4-OHE2), expressed as area under the curve metric (4-OHE2-AUC). The model also incorporates phenotypic factors (age, body mass index, hormone replacement therapy, oral contraceptives, family history), which plausibly influence estrogen metabolism and the production of 4-OHE2. We applied the model to two independent, population-based breast cancer case-control groups, the German GENICA study (967 cases, 971 controls) and the Nashville Breast Cohort (NBC; 465 cases, 885 controls). Results In the GENICA study, premenopausal women at the 90th percentile of 4-OHE2-AUC among control subjects had a risk of breast cancer that was 2.30 times that of women at the 10th control 4-OHE2-AUC percentile (95% CI 1.7 – 3.2, P = 2.9 × 10−7). This relative risk was 1.89 (95% CI 1.5 – 2.4, P = 2.2 × 10−8) in postmenopausal women. In the NBC, this relative risk in postmenopausal women was 1.81 (95% CI 1.3 – 2.6, P = 7.6 × 10−4), which increased to 1.83 (95% CI 1.4 – 2.3, P = 9.5 × 10−7) when a history of proliferative breast disease was included in the model. Conclusions The model combines genotypic and phenotypic factors involved in carcinogenic estrogen metabolite production and cumulative estrogen exposure to predict breast cancer risk. Impact The estrogen carcinogenesis-based model has the potential to provide personalized risk estimates. PMID:21610218

Metabolic phenotyping of a model of adipocyte differentiation

PubMed Central

Roberts, Lee D.; Virtue, Sam; Vidal-Puig, Antonio; Nicholls, Andrew W.

2009-01-01

The 3T3-L1 murine cell line is a robust and widely used model for the study of adipogenesis and processes occurring in mature adipocytes. The fibroblastic like cells can be induced by hormones to differentiate into mature adipocytes. In this study, the metabolic phenotype associated with differentiation of the 3T3-L1 cell line has been studied using gas chromatography-mass spectrometry, 1H nuclear magnetic resonance spectroscopy, liquid chromatography-mass spectrometry, direct infusion-mass spectrometry, and 13C substrate labeling in conjunction with multivariate statistics. The changes in metabolite concentrations at distinct periods during differentiation have been defined including alterations in the TCA cycle, glycolysis, the production of odd chain fatty acids by α-oxidation, fatty acid synthesis, fatty acid desaturation, polyamine biosynthesis, and trans-esterification to produce complex lipids. The metabolic changes induced during differentiation of the 3T3-L1 cell line were then compared with the metabolic differences between pre- and postdifferentiation primary adipocytes. These metabolic alterations reflect the changing role of the 3T3-L1 cells during differentiation, as well as possibly providing metabolic triggers to stimulate the processes which occur during differentiation. PMID:19602617

Changes in insulin-like growth factor signaling alter phenotypes in Fragile X Mice.

PubMed

Wise, T L

2017-02-01

Fragile X syndrome (FXS) is an inherited form of intellectual disability that is usually caused by expansion of a polymorphic CGG repeat in the 5' untranslated region of the X-linked FMR1 gene, which leads to hypermethylation and transcriptional silencing. Two non-neurological phenotypes of FXS are enlarged testes and connective tissue dysplasia, which could be caused by alterations in a growth factor signaling pathway. FXS patients also frequently have autistic-like symptoms, suggesting that the signaling pathways affected in FXS may overlap with those affected in autism. Identifying these pathways is important for both understanding the effects of FMR1 inactivation and developing treatments for both FXS and autism. Here we show that decreasing the levels of the insulin-like growth factor (Igf) receptor 1 corrects a number of phenotypes in the mouse model of FXS, including macro-orchidism, and that increasing the levels of IGF2 exacerbates the seizure susceptibility phenotype. These results suggest that the pathways altered by the loss of the FMR1-encoded protein (FMRP) may overlap with the pathways affected by changes in Igf signaling or that one or more of the proteins that play a role in Igf signaling could interact with FMRP. They also indicate a new set of potential targets for drug treatment of FXS and autism spectrum disorders. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

X-linked adrenoleukodystrophy in heterozygous female patients: women are not just carriers.

PubMed

Lourenço, Charles Marques; Simão, Gustavo Novelino; Santos, Antonio Carlos; Marques, Wilson

2012-07-01

X-linked adrenoleukodystrophy (X-ALD) is a recessive X-linked disorder associated with marked phenotypic variability. Female carriers are commonly thought to be normal or only mildly affected, but their disease still needs to be better described and systematized. To review and systematize the clinical features of heterozygous women followed in a Neurogenetics Clinic. We reviewed the clinical, biochemical, and neuroradiological data of all women known to have X-ADL. The nine women identified were classified into three groups: with severe and aggressive diseases; with slowly progressive, spastic paraplegia; and with mildly decreased vibratory sensation, brisk reflexes, and no complaints. Many of these women did not have a known family history of X-ALD. Heterozygous women with X-ADL have a wide spectrum of clinical manifestations, ranging from mild to severe phenotypes.

Linking an ecosystem model and a landscape model to study forest species response to climate warming

Treesearch

Hong S. He; David J. Mladenoff; Thomas R. Crow

1999-01-01

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model {LINKAGES) with a spatial landscape model (LANDIS) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was...

Identification of Nascent Memory CD8 T Cells and Modeling of Their Ontogeny.

PubMed

Crauste, Fabien; Mafille, Julien; Boucinha, Lilia; Djebali, Sophia; Gandrillon, Olivier; Marvel, Jacqueline; Arpin, Christophe

2017-03-22

Primary immune responses generate short-term effectors and long-term protective memory cells. The delineation of the genealogy linking naive, effector, and memory cells has been complicated by the lack of phenotypes discriminating effector from memory differentiation stages. Using transcriptomics and phenotypic analyses, we identify Bcl2 and Mki67 as a marker combination that enables the tracking of nascent memory cells within the effector phase. We then use a formal approach based on mathematical models describing the dynamics of population size evolution to test potential progeny links and demonstrate that most cells follow a linear naive→early effector→late effector→memory pathway. Moreover, our mathematical model allows long-term prediction of memory cell numbers from a few early experimental measurements. Our work thus provides a phenotypic means to identify effector and memory cells, as well as a mathematical framework to investigate their genealogy and to predict the outcome of immunization regimens in terms of memory cell numbers generated. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A Splice Defect in the EDA Gene in Dogs with an X-Linked Hypohidrotic Ectodermal Dysplasia (XLHED) Phenotype.

PubMed

Waluk, Dominik P; Zur, Gila; Kaufmann, Ronnie; Welle, Monika M; Jagannathan, Vidhya; Drögemüller, Cord; Müller, Eliane J; Leeb, Tosso; Galichet, Arnaud

2016-09-08

X-linked hypohidrotic ectodermal dysplasia (XLHED) caused by variants in the EDA gene represents the most common ectodermal dysplasia in humans. We investigated three male mixed-breed dogs with an ectodermal dysplasia phenotype characterized by marked hypotrichosis and multifocal complete alopecia, almost complete absence of sweat and sebaceous glands, and altered dentition with missing and abnormally shaped teeth. Analysis of SNP chip genotypes and whole genome sequence data from the three affected dogs revealed that the affected dogs shared the same haplotype on a large segment of the X-chromosome, including the EDA gene. Unexpectedly, the whole genome sequence data did not reveal any nonsynonymous EDA variant in the affected dogs. We therefore performed an RNA-seq experiment on skin biopsies to search for changes in the transcriptome. This analysis revealed that the EDA transcript in the affected dogs lacked 103 nucleotides encoded by exon 2. We speculate that this exon skipping is caused by a genetic variant located in one of the large introns flanking this exon, which was missed by whole genome sequencing with the illumina short read technology. The altered EDA transcript splicing most likely causes the observed ectodermal dysplasia in the affected dogs. These dogs thus offer an excellent opportunity to gain insights into the complex splicing processes required for expression of the EDA gene, and other genes with large introns. Copyright © 2016 Waluk et al.

The macroevolutionary consequences of phenotypic integration: from development to deep time.

PubMed

Goswami, A; Smaers, J B; Soligo, C; Polly, P D

2014-08-19

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

The macroevolutionary consequences of phenotypic integration: from development to deep time

PubMed Central

Goswami, A.; Smaers, J. B.; Soligo, C.; Polly, P. D.

2014-01-01

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution. PMID:25002699

Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2018-03-26

In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

Concordant but Varied Phenotypes among Duchenne Muscular Dystrophy Patient-Specific Myoblasts Derived using a Human iPSC-Based Model.

PubMed

Choi, In Young; Lim, HoTae; Estrellas, Kenneth; Mula, Jyothi; Cohen, Tatiana V; Zhang, Yuanfan; Donnelly, Christopher J; Richard, Jean-Philippe; Kim, Yong Jun; Kim, Hyesoo; Kazuki, Yasuhiro; Oshimura, Mitsuo; Li, Hongmei Lisa; Hotta, Akitsu; Rothstein, Jeffrey; Maragakis, Nicholas; Wagner, Kathryn R; Lee, Gabsang

2016-06-07

Duchenne muscular dystrophy (DMD) remains an intractable genetic disease. Althogh there are several animal models of DMD, there is no human cell model that carries patient-specific DYSTROPHIN mutations. Here, we present a human DMD model using human induced pluripotent stem cells (hiPSCs). Our model reveals concordant disease-related phenotypes with patient-dependent variation, which are partially reversed by genetic and pharmacological approaches. Our "chemical-compound-based" strategy successfully directs hiPSCs into expandable myoblasts, which exhibit a myogenic transcriptional program, forming striated contractile myofibers and participating in muscle regeneration in vivo. DMD-hiPSC-derived myoblasts show disease-related phenotypes with patient-to-patient variability, including aberrant expression of inflammation or immune-response genes and collagens, increased BMP/TGFβ signaling, and reduced fusion competence. Furthermore, by genetic correction and pharmacological "dual-SMAD" inhibition, the DMD-hiPSC-derived myoblasts and genetically corrected isogenic myoblasts form "rescued" multi-nucleated myotubes. In conclusion, our findings demonstrate the feasibility of establishing a human "DMD-in-a-dish" model using hiPSC-based disease modeling. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Evolution of cooperation in a multidimensional phenotype space.

PubMed

Kroumi, Dhaker; Lessard, Sabin

2015-06-01

The emergence of cooperation in populations of selfish individuals is a fascinating topic that has inspired much theoretical work. An important model to study cooperation is the phenotypic model, where individuals are characterized by phenotypic properties that are visible to others. The phenotype of an individual can be represented for instance by a vector x = (x1,…,xn), where x1,…,xn are integers. The population can be well mixed in the sense that everyone is equally likely to interact with everyone else, but the behavioral strategies of the individuals can depend on their distance in the phenotype space. A cooperator can choose to help other individuals exhibiting the same phenotype and defects otherwise. Cooperation is said to be favored by selection if it is more abundant than defection in the stationary state. This means that the average frequency of cooperators in the stationary state strictly exceeds 1/2. Antal et al. (2009c) found conditions that ensure that cooperation is more abundant than defection in a one-dimensional (i.e. n = 1) and an infinite-dimensional (i.e. n = ∞) phenotype space in the case of the Prisoner's Dilemma under weak selection. However, reality lies between these two limit cases. In this paper, we derive the corresponding condition in the case of a phenotype space of any finite dimension. This is done by applying a perturbation method to study a mutation-selection equilibrium under weak selection. This condition is obtained in the limit of a large population size by using the ancestral process. The best scenario for cooperation to be more likely to evolve is found to be a high population-scaled phenotype mutation rate, a low population-scaled strategy mutation rate and a high phenotype space dimension. The biological intuition is that a high population-scaled phenotype mutation rate reduces the quantity of interactions between cooperators and defectors, while a high population-scaled strategy mutation rate introduces newly

The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change.

PubMed

Valladares, Fernando; Matesanz, Silvia; Guilhaumon, François; Araújo, Miguel B; Balaguer, Luis; Benito-Garzón, Marta; Cornwell, Will; Gianoli, Ernesto; van Kleunen, Mark; Naya, Daniel E; Nicotra, Adrienne B; Poorter, Hendrik; Zavala, Miguel A

2014-11-01

Species are the unit of analysis in many global change and conservation biology studies; however, species are not uniform entities but are composed of different, sometimes locally adapted, populations differing in plasticity. We examined how intraspecific variation in thermal niches and phenotypic plasticity will affect species distributions in a warming climate. We first developed a conceptual model linking plasticity and niche breadth, providing five alternative intraspecific scenarios that are consistent with existing literature. Secondly, we used ecological niche-modeling techniques to quantify the impact of each intraspecific scenario on the distribution of a virtual species across a geographically realistic setting. Finally, we performed an analogous modeling exercise using real data on the climatic niches of different tree provenances. We show that when population differentiation is accounted for and dispersal is restricted, forecasts of species range shifts under climate change are even more pessimistic than those using the conventional assumption of homogeneously high plasticity across a species' range. Suitable population-level data are not available for most species so identifying general patterns of population differentiation could fill this gap. However, the literature review revealed contrasting patterns among species, urging greater levels of integration among empirical, modeling and theoretical research on intraspecific phenotypic variation. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

Comparison of Liver Cell Models Using the Basel Phenotyping Cocktail

PubMed Central

Berger, Benjamin; Donzelli, Massimiliano; Maseneni, Swarna; Boess, Franziska; Roth, Adrian; Krähenbühl, Stephan; Haschke, Manuel

2016-01-01

Currently used hepatocyte cell systems for in vitro assessment of drug metabolism include hepatoma cell lines and primary human hepatocyte (PHH) cultures. We investigated the suitability of the validated in vivo Basel phenotyping cocktail (caffeine [CYP1A2], efavirenz [CYP2B6], losartan [CYP2C9], omeprazole [CYP2C19], metoprolol [CYP2D6], midazolam [CYP3A4]) in vitro and characterized four hepatocyte cell systems (HepG2 cells, HepaRG cells, and primary cryopreserved human hepatocytes in 2-dimensional [2D] culture or in 3D-spheroid co-culture) regarding basal metabolism and CYP inducibility. Under non-induced conditions, all CYP activities could be determined in 3D-PHH, CYP2B6, CYP2C19, CYP2D6, and CYP3A4 in 2D-PHH and HepaRG, and CYP2C19 and CYP3A4 in HepG2 cells. The highest non-induced CYP activities were observed in 3D-PHH and HepaRG cells. mRNA expression was at least four-fold higher for all CYPs in 3D-PHH compared to the other cell systems. After treatment with 20 μM rifampicin, mRNA increased 3- to 50-fold for all CYPs except CYP1A2 and 2D6 for HepaRG and 3D-PHH, 4-fold (CYP2B6) and 17-fold (CYP3A4) for 2D-PHH and four-fold (CYP3A4) for HepG2. In 3D-PHH at least a two-fold increase in CYP activity was observed for all inducible CYP isoforms while CYP1A2 and CYP2C9 activity did not increase in 2D-PHH and HepaRG. CYP inducibility assessed in vivo using the same phenotyping probes was also best reflected by the 3D-PHH model. Our studies show that 3D-PHH and (with some limitations) HepaRG are suitable cell systems for assessing drug metabolism and CYP induction in vitro. HepG2 cells are less suited to assess CYP induction of the 2C and 3A family. The Basel phenotyping cocktail is suitable for the assessment of CYP activity and induction also in vitro. PMID:27917125

Comparison of Liver Cell Models Using the Basel Phenotyping Cocktail.

PubMed

Berger, Benjamin; Donzelli, Massimiliano; Maseneni, Swarna; Boess, Franziska; Roth, Adrian; Krähenbühl, Stephan; Haschke, Manuel

2016-01-01

Currently used hepatocyte cell systems for in vitro assessment of drug metabolism include hepatoma cell lines and primary human hepatocyte (PHH) cultures. We investigated the suitability of the validated in vivo Basel phenotyping cocktail (caffeine [CYP1A2], efavirenz [CYP2B6], losartan [CYP2C9], omeprazole [CYP2C19], metoprolol [CYP2D6], midazolam [CYP3A4]) in vitro and characterized four hepatocyte cell systems (HepG2 cells, HepaRG cells, and primary cryopreserved human hepatocytes in 2-dimensional [2D] culture or in 3D-spheroid co-culture) regarding basal metabolism and CYP inducibility. Under non-induced conditions, all CYP activities could be determined in 3D-PHH, CYP2B6, CYP2C19, CYP2D6, and CYP3A4 in 2D-PHH and HepaRG, and CYP2C19 and CYP3A4 in HepG2 cells. The highest non-induced CYP activities were observed in 3D-PHH and HepaRG cells. mRNA expression was at least four-fold higher for all CYPs in 3D-PHH compared to the other cell systems. After treatment with 20 μM rifampicin, mRNA increased 3- to 50-fold for all CYPs except CYP1A2 and 2D6 for HepaRG and 3D-PHH, 4-fold (CYP2B6) and 17-fold (CYP3A4) for 2D-PHH and four-fold (CYP3A4) for HepG2. In 3D-PHH at least a two-fold increase in CYP activity was observed for all inducible CYP isoforms while CYP1A2 and CYP2C9 activity did not increase in 2D-PHH and HepaRG. CYP inducibility assessed in vivo using the same phenotyping probes was also best reflected by the 3D-PHH model. Our studies show that 3D-PHH and (with some limitations) HepaRG are suitable cell systems for assessing drug metabolism and CYP induction in vitro . HepG2 cells are less suited to assess CYP induction of the 2C and 3A family. The Basel phenotyping cocktail is suitable for the assessment of CYP activity and induction also in vitro .

Wine Expertise Predicts Taste Phenotype

PubMed Central

Hayes, John E; Pickering, Gary J

2011-01-01

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

Fanconi Anemia Links Reactive Oxygen Species to Insulin Resistance and Obesity

PubMed Central

Li, Jie; Sipple, Jared; Maynard, Suzette; Mehta, Parinda A.; Rose, Susan R.; Davies, Stella M.

2012-01-01

Abstract Aims: Insulin resistance is a hallmark of obesity and type 2 diabetes. Reactive oxygen species (ROS) have been proposed to play a causal role in insulin resistance. However, evidence linking ROS to insulin resistance in disease settings has been scant. Since both oxidative stress and diabetes have been observed in patients with the Fanconi anemia (FA), we sought to investigate the link between ROS and insulin resistance in this unique disease model. Results: Mice deficient for the Fanconi anemia complementation group A (Fanca) or Fanconi anemia complementation group C (Fancc) gene seem to be diabetes-prone, as manifested by significant hyperglycemia and hyperinsulinemia, and rapid weight gain when fed with a high-fat diet. These phenotypic features of insulin resistance are characterized by two critical events in insulin signaling: a reduction in tyrosine phosphorylation of the insulin receptor (IR) and an increase in inhibitory serine phosphorylation of the IR substrate-1 in the liver, muscle, and fat tissues from the insulin-challenged FA mice. High levels of ROS, spontaneously accumulated or generated by tumor necrosis factor alpha in these insulin-sensitive tissues of FA mice, were shown to underlie the FA insulin resistance. Treatment of FA mice with the natural anti-oxidant Quercetin restores IR signaling and ameliorates the diabetes- and obesity-prone phenotypes. Finally, pairwise screen identifies protein-tyrosine phosphatase (PTP)-α and stress kinase double-stranded RNA-dependent protein kinase (PKR) that mediate the ROS effect on FA insulin resistance. Innovation: These findings establish a pathogenic and mechanistic link between ROS and insulin resistance in a unique human disease setting. Conclusion: ROS accumulation contributes to the insulin resistance in FA deficiency by targeting both PTP-α and PKR. Antioxid. Redox Signal. 00, 000–000. PMID:22482891

Modeling the population dynamics and community impacts of Ambystoma tigrinum: A case study of phenotype plasticity.

PubMed

McCarthy, Maeve L; Wallace, Dorothy; Whiteman, Howard H; Rheingold, Evan T; Dunham, Ann M; Prosper, Olivia; Chen, Michelle; Hu-Wang, Eileen

2017-06-01

Phenotypic plasticity is the ability of an organism to change its phenotype in response to changes in the environment. General mathematical descriptions of the phenomenon rely on an abstract measure of "viability" that, in this study, is instantiated in the case of the Tiger Salamander, Ambystoma tigrinum. This organism has a point in its development when, upon maturing, it may take two very different forms. One is a terrestrial salamander (metamorph)that visits ponds to reproduce and eat, while the other is an aquatic form (paedomorph) that remains in the pond to breed and which consumes a variety of prey including its own offspring. A seven dimensional nonlinear system of ordinary differential equations is developed, incorporating small (Z) and large (B) invertebrates, Ambystoma young of the year (Y), juveniles (J), terrestrial metamorphs (A) and aquatic paedomorphs (P). One parameter in the model controls the proportion of juveniles maturing into A versus P. Solutions are shown to remain non-negative. Every effort was made to justify parameters biologically through studies reported in the literature. A sensitivity analysis and equilibrium analysis of model parameters demonstrate that morphological choice is critical to the overall composition of the Ambystoma population. Various population viability measures were used to select optimal percentages of juveniles maturing into metamorphs, with optimal choices differing considerably depending on the viability measure. The model suggests that the criteria for viability for this organism vary, both from location to location and also in time. Thus, optimal responses change with spatiotemporal variation, which is consistent with other phenotypically plastic systems. Two competing hypotheses for the conditions under which metamorphosis occurs are examined in light of the model and data from an Ambystoma tigrinum population at Mexican Cut, Colorado. The model clearly supports one of these over the other for this data set

Justification of Fuzzy Declustering Vector Quantization Modeling in Classification of Genotype-Image Phenotypes

NASA Astrophysics Data System (ADS)

Ng, Theam Foo; Pham, Tuan D.; Zhou, Xiaobo

2010-01-01

With the fast development of multi-dimensional data compression and pattern classification techniques, vector quantization (VQ) has become a system that allows large reduction of data storage and computational effort. One of the most recent VQ techniques that handle the poor estimation of vector centroids due to biased data from undersampling is to use fuzzy declustering-based vector quantization (FDVQ) technique. Therefore, in this paper, we are motivated to propose a justification of FDVQ based hidden Markov model (HMM) for investigating its effectiveness and efficiency in classification of genotype-image phenotypes. The performance evaluation and comparison of the recognition accuracy between a proposed FDVQ based HMM (FDVQ-HMM) and a well-known LBG (Linde, Buzo, Gray) vector quantization based HMM (LBG-HMM) will be carried out. The experimental results show that the performances of both FDVQ-HMM and LBG-HMM are almost similar. Finally, we have justified the competitiveness of FDVQ-HMM in classification of cellular phenotype image database by using hypotheses t-test. As a result, we have validated that the FDVQ algorithm is a robust and an efficient classification technique in the application of RNAi genome-wide screening image data.

Neurophysiology of Drosophila Models of Parkinson's Disease

PubMed Central

West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

2015-01-01

We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing. PMID:25960916

Accessible, almost ab initio multi-scale modeling of entangled polymers via slip-links

NASA Astrophysics Data System (ADS)

Andreev, Marat

It is widely accepted that dynamics of entangled polymers can be described by the tube model. Here we advocate for an alternative approach to entanglement modeling known as slip-links. Recently, slip-links were shown to possess important advantages over tube models, namely they have strong connections to atomistic, multichain levels of description, agree with non-equilibrium thermodynamics, are applicable to any chain architecture and can be used in linear or non-linear rheology. We present a hierarchy of slip-link models that are connected to each other through successive coarse graining. Models in the hierarchy are consistent in their overlapping domains of applicability in order to allow a straightforward mapping of parameters. In particular, the most--detailed level of description has four parameters, three of which can be determined directly from atomistic simulations. On the other hand, the least--detailed member of the hierarchy is numerically accessible, and allows for non-equilibrium flow predictions of complex chain architectures. Using GPU implementation these predictions can be obtained in minutes of computational time on a single desktop equipped with a mainstream gaming GPU. The GPU code is available online for free download.

Peruvian Maca (Lepidium peruvianum): (I) Phytochemical and Genetic Differences in Three Maca Phenotypes.

PubMed

Meissner, Henry O; Mscisz, Alina; Mrozikiewicz, Mieczyslaw; Baraniak, Marek; Mielcarek, Sebastian; Kedzia, Bogdan; Piatkowska, Ewa; Jólkowska, Justyna; Pisulewski, Pawel

2015-09-01

Glucosinolates were previously reported as physiologically-important constituents present in Peruvian Maca (Lepidium peruvianum Chacon) and linked to various therapeutic functions of differently-colored Peruvian Maca hypocotyls. In two separate Trials, three colours of Maca hypocotyls "Black", "Red" and "Yellow" (termed "Maca phenotypes"), were selected from mixed crops of Peruvian Maca for laboratory studies as fresh and after being dried. Individual Maca phenotypes were cultivated in the highlands of the Peruvian Andes at 4,200m a.s.l. (Junin and Ninacaca). Glucosinolate levels, chromatographic HPLC profiles and DNA variability in the investigated Maca phenotypes are presented. Genotypic profiles were determined by the ISSR-PCR and RAPD techniques. Compared to the Black and Red phenotypes, the Yellow phenotype contained much lower Glucosinolate levels measured against Glucotropaeolin and m-methoxy-glucotropaeolin standards, and exhibited different RAPD and ISSR-PCR reactions. The Red Maca phenotype showed the highest concentrations of Glucosinolates as compared to the Black and Yellow Maca. It appears that the traditional system used by natives of the Peruvian Andean highlands in preparing Maca as a vegetable dish (boiling dried Maca after soaking in water), to supplement their daily meals, is as effective as laboratory methods - for extracting Glucosinolates, which are considered to be one of the key bioactive constituents responsible for therapeutic functions of Peruvian Maca phenotypes. It is reasonable to assume that the HPLC and DNA techniques combined, or separately, may assist in determining ID and "Fingerprints" identifying individual Peruvian Maca phenotypes, hence confirming the authenticity of marketable Maca products. The above assumptions warrant further laboratory testing.

Attrition in Models of Intergenerational Links Using the PSID with Extensions to Health and to Sibling Models*

PubMed Central

Fitzgerald, John M.

2012-01-01

Selective attrition potentially biases estimation of intergenerational links in health and economic status. This paper documents attrition in the PSID through 2007 for a cohort of children, and investigates attrition bias in intergenerational models predicting adult health, education and earnings, including models based on sibling differences. Although attrition affects unconditional means, the weighted PSID generally maintains its representativeness along key dimensions in comparison to the National Health Interview Survey. Using PSID, sibling correlations in outcomes and father-son correlations in earnings are not significantly affected by attrition. Models of intergenerational links with covariates yield more mixed results with females showing few robust impacts of attrition and males showing potential attrition bias for education and earnings outcomes. For adult health outcomes conditional on child background, neither gender shows significant impacts of attrition for the age ranges and models considered here. Sibling models do not produce robustly higher attrition impacts than individual models. PMID:22368743

X-linked gene expression in the Virginia opossum: differences between the paternally derived Gpd and Pgk-A loci

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

Samollow, P.B.; Ford, A.L.; VandeBerg, J.L.

1987-01-01

Expression of X-linked glucose-6-phosphate dehydrogenase (G6PD) and phosphoglycerate kinase-A (PGK-A) in the Virginia opossum (Didelphis virginiana) was studied electrophoretically in animals from natural populations and those produced through controlled laboratory crosses. Blood from most of the wild animals exhibited a common single-banded phenotype for both enzymes. Rare variant animals, regardless of sex, exhibited single-banded phenotypes different in mobility from the common mobility class of the respective enzyme. The laboratory crosses confirmed the allelic basis for the common and rare phenotypes. Transmission of PGK-A phenotypes followed the pattern of determinate (nonrandom) inactivation of the paternally derived Pgk-A allele, and transmission ofmore » G6PD also was consistent with this pattern. A survey of tissue-specific expression of G6PD phenotypes of heterozygous females revealed, in almost all tissues, three-banded patterns skewed in favor of the allele that was expressed in blood cells. Three-banded patterns were never observed in males or in putatively homozygous females. These patterns suggest simultaneous, but unequal, expression of the maternally and paternally derived Gpd alleles within individual cells. The absence of such partial expression was noted in a parallel survey of females heterozygous at the Pgd-A locus. Thus, it appears that Gpd and Pgk-A are X-linked in D. virginiana and subject to preferential paternal allele inactivation, but that dosage compensation may not be complete for all paternally derived X-linked genes.« less

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement.

PubMed

Cobb, Joshua N; Declerck, Genevieve; Greenberg, Anthony; Clark, Randy; McCouch, Susan

2013-04-01

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Post-transcriptional Mechanisms Contribute Little to Phenotypic Variation in Snake Venoms.

PubMed

Rokyta, Darin R; Margres, Mark J; Calvin, Kate

2015-09-09

Protein expression is a major link in the genotype-phenotype relationship, and processes affecting protein abundances, such as rates of transcription and translation, could contribute to phenotypic evolution if they generate heritable variation. Recent work has suggested that mRNA abundances do not accurately predict final protein abundances, which would imply that post-transcriptional regulatory processes contribute significantly to phenotypes. Post-transcriptional processes also appear to buffer changes in transcriptional patterns as species diverge, suggesting that the transcriptional changes have little or no effect on the phenotypes undergoing study. We tested for concordance between mRNA and protein expression levels in snake venoms by means of mRNA-seq and quantitative mass spectrometry for 11 snakes representing 10 species, six genera, and three families. In contrast to most previous work, we found high correlations between venom gland transcriptomes and venom proteomes for 10 of our 11 comparisons. We tested for protein-level buffering of transcriptional changes during species divergence by comparing the difference between transcript abundance and protein abundance for three pairs of species and one intraspecific pair. We found no evidence for buffering during divergence of our three species pairs but did find evidence for protein-level buffering for our single intraspecific comparison, suggesting that buffering, if present, was a transient phenomenon in venom divergence. Our results demonstrated that post-transcriptional mechanisms did not contribute significantly to phenotypic evolution in venoms and suggest a more prominent and direct role for cis-regulatory evolution in phenotypic variation, particularly for snake venoms. Copyright © 2015 Rokyta et al.

Hemopexin therapy reverts heme-induced proinflammatory phenotypic switching of macrophages in a mouse model of sickle cell disease.

PubMed

Vinchi, Francesca; Costa da Silva, Milene; Ingoglia, Giada; Petrillo, Sara; Brinkman, Nathan; Zuercher, Adrian; Cerwenka, Adelheid; Tolosano, Emanuela; Muckenthaler, Martina U

2016-01-28

Hemolytic diseases, such as sickle cell anemia and thalassemia, are characterized by enhanced release of hemoglobin and heme into the circulation, heme-iron loading of reticulo-endothelial system macrophages, and chronic inflammation. Here we show that in addition to activating the vascular endothelium, hemoglobin and heme excess alters the macrophage phenotype in sickle cell disease. We demonstrate that exposure of cultured macrophages to hemolytic aged red blood cells, heme, or iron causes their functional phenotypic change toward a proinflammatory state. In addition, hemolysis and macrophage heme/iron accumulation in a mouse model of sickle disease trigger similar proinflammatory phenotypic alterations in hepatic macrophages. On the mechanistic level, this critically depends on reactive oxygen species production and activation of the Toll-like receptor 4 signaling pathway. We further demonstrate that the heme scavenger hemopexin protects reticulo-endothelial macrophages from heme overload in heme-loaded Hx-null mice and reduces production of cytokines and reactive oxygen species. Importantly, in sickle mice, the administration of human exogenous hemopexin attenuates the inflammatory phenotype of macrophages. Taken together, our data suggest that therapeutic administration of hemopexin is beneficial to counteract heme-driven macrophage-mediated inflammation and its pathophysiologic consequences in sickle cell disease. © 2016 by The American Society of Hematology.

Response to Drs. Shastry and Trese: Phenotype-genotype correlations in X-linked retinitis pigmentosa

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

Kaplan, J.; Munnich, A.

1996-11-11

Shastry and Trese recently reported on a large kindred with X-linked retinitis pigmentosa (XLRP) characterized by a loss of central vision and preserved peripheral function. In their report, the disease had an early onset with severe myopia and a loss of central vision, while night blindness occurred later. Genetic analysis suggested that the disease was linked to the RP2 locus, and the authors raised the question of whether other cases linked to RP2 could display a similar loss of central vision. Three years ago, we reported on 4 large XLRP pedigrees with a very early onset with severe myopia andmore » early loss of visual acuity, while in 5 other families the disease started later with night blindness. We showed that the first clinical form was linked to RP2, while the second was linked to RP3. Thus, the major difference between the two forms concerns the initial symptom, information which can be obtained from the parents and patients after careful questioning. By contrast, in adult life, no difference in either severity of disease or aspect of the fundus was observed in our series, regardless of the clinical subtype of XLRP. Some months later, Jacobson et al. reported on a pedigree with an RP2 genotype, and their data support the notion that in XLRP of RP2 type 1, cone dysfunction takes place first, and as the disease advances both rods and cones are affected. We were very happy, therefore, to read that the study of Shastry and Trese fully confirmed our previous findings. 3 refs.« less

Host Genotype and Gut Microbiome Modulate Insulin Secretion and Diet-Induced Metabolic Phenotypes.

PubMed

Kreznar, Julia H; Keller, Mark P; Traeger, Lindsay L; Rabaglia, Mary E; Schueler, Kathryn L; Stapleton, Donald S; Zhao, Wen; Vivas, Eugenio I; Yandell, Brian S; Broman, Aimee Teo; Hagenbuch, Bruno; Attie, Alan D; Rey, Federico E

2017-02-14

Genetic variation drives phenotypic diversity and influences the predisposition to metabolic disease. Here, we characterize the metabolic phenotypes of eight genetically distinct inbred mouse strains in response to a high-fat/high-sucrose diet. We found significant variation in diabetes-related phenotypes and gut microbiota composition among the different mouse strains in response to the dietary challenge and identified taxa associated with these traits. Follow-up microbiota transplant experiments showed that altering the composition of the gut microbiota modifies strain-specific susceptibility to diet-induced metabolic disease. Animals harboring microbial communities with enhanced capacity for processing dietary sugars and for generating hydrophobic bile acids showed increased susceptibility to metabolic disease. Notably, differences in glucose-stimulated insulin secretion between different mouse strains were partially recapitulated via gut microbiota transfer. Our results suggest that the gut microbiome contributes to the genetic and phenotypic diversity observed among mouse strains and provide a link between the gut microbiome and insulin secretion. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Phenotype-limited distributions: short-billed birds move away during times that prey bury deeply.

PubMed

Duijns, Sjoerd; van Gils, Jan A; Smart, Jennifer; Piersma, Theunis

2015-06-01

In our seasonal world, animals face a variety of environmental conditions in the course of the year. To cope with such seasonality, animals may be phenotypically flexible, but some phenotypic traits are fixed. If fixed phenotypic traits are functionally linked to resource use, then animals should redistribute in response to seasonally changing resources, leading to a 'phenotype-limited' distribution. Here, we examine this possibility for a shorebird, the bar-tailed godwit (Limosa lapponica; a long-billed and sexually dimorphic shorebird), that has to reach buried prey with a probing bill of fixed length. The main prey of female bar-tailed godwits is buried deeper in winter than in summer. Using sightings of individually marked females, we found that in winter only longer-billed individuals remained in the Dutch Wadden Sea, while the shorter-billed individuals moved away to an estuary with a more benign climate such as the Wash. Although longer-billed individuals have the widest range of options in winter and could therefore be selected for, counterselection may occur during the breeding season on the tundra, where surface-living prey may be captured more easily with shorter bills. Phenotype-limited distributions could be a widespread phenomenon and, when associated with assortative migration and mating, it may act as a precursor of phenotypic evolution.

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Simulink models for performance analysis of high speed DQPSK modulated optical link

NASA Astrophysics Data System (ADS)