The spatial patterns of directional phenotypic selection.

Science.gov (United States)

Siepielski, Adam M; Gotanda, Kiyoko M; Morrissey, Michael B; Diamond, Sarah E; DiBattista, Joseph D; Carlson, Stephanie M

2013-11-01

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.

The spatial patterns of directional phenotypic selection

KAUST Repository

Siepielski, Adam M.

2013-09-12

Local adaptation, adaptive population divergence and speciation are often expected to result from populations evolving in response to spatial variation in selection. Yet, we lack a comprehensive understanding of the major features that characterise the spatial patterns of selection, namely the extent of variation among populations in the strength and direction of selection. Here, we analyse a data set of spatially replicated studies of directional phenotypic selection from natural populations. The data set includes 60 studies, consisting of 3937 estimates of selection across an average of five populations. We performed meta-analyses to explore features characterising spatial variation in directional selection. We found that selection tends to vary mainly in strength and less in direction among populations. Although differences in the direction of selection occur among populations they do so where selection is often weakest, which may limit the potential for ongoing adaptive population divergence. Overall, we also found that spatial variation in selection appears comparable to temporal (annual) variation in selection within populations; however, several deficiencies in available data currently complicate this comparison. We discuss future research needs to further advance our understanding of spatial variation in selection. © 2013 John Wiley & Sons Ltd/CNRS.

A “Forward Genomics” Approach Links Genotype to Phenotype using Independent Phenotypic Losses among Related Species

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Michael Hiller

2012-10-01

Full Text Available Genotype-phenotype mapping is hampered by countless genomic changes between species. We introduce a computational “forward genomics” strategy that—given only an independently lost phenotype and whole genomes—matches genomic and phenotypic loss patterns to associate specific genomic regions with this phenotype. We conducted genome-wide screens for two metabolic phenotypes. First, our approach correctly matches the inactivated Gulo gene exactly with the species that lost the ability to synthesize vitamin C. Second, we attribute naturally low biliary phospholipid levels in guinea pigs and horses to the inactivated phospholipid transporter Abcb4. Human ABCB4 mutations also result in low phospholipid levels but lead to severe liver disease, suggesting compensatory mechanisms in guinea pig and horse. Our simulation studies, counts of independent changes in existing phenotype surveys, and the forthcoming availability of many new genomes all suggest that forward genomics can be applied to many phenotypes, including those relevant for human evolution and disease.

Moving towards patient-centered medicine for COPD management: multidimensional approaches versus phenotype-based medicine--a critical view.

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Lopez-Campos, Jose Luis; Bustamante, Víctor; Muñoz, Xavier; Barreiro, Esther

2014-09-01

For decades, chronic obstructive pulmonary disease (COPD) has been considered a relentlessly progressive disease in which the deterioration of lung function is associated with an increase in symptoms, interrupted only by periods of exacerbation. However, this paradigm of COPD severity based on FEV1 has been challenged by currently available evidence. So far, three main approaches, though with contradictory aspects, have been proposed in order to address the complexity of COPD as well as to develop appropriate diagnostic, prognostic and therapeutic strategies for the disease: 1) the use of independent, clinically relevant variables, 2) the use of multidimensional indices, and 3) disease approaches based on clinical phenotypes. Multivariable systems seem superior to FEV1 in predicting prognosis and defining disease severity. However, selection of variables available from current literature must be confronted with issues of medical practice. Future evidence will be needed to reveal their effective relationship with disease long-term prognosis and to demonstrate the most adequate cutoff values to be used in clinical settings. Multidimensional scores provide a good prognostic instrument for the identification of patients with a particular degree of disease severity. Clinical phenotyping can help clinicians identify the patients who respond to specific pharmacological interventions; however, there is some controversy about the phenotypes to select and their long-term implications. Although these approaches are not perfect, they represent the first step towards patient-centered medicine for COPD. In the near-future, these different approaches should converge towards one new field to focus on the better management of COPD patients.

Hsp90 selectively modulates phenotype in vertebrate development.

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Patricia L Yeyati

2007-03-01

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

Digest: Plants adapt under attack: genotypic selection and phenotypic plasticity under herbivore pressure.

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Hawkins, Nichola J

2018-03-31

Plant species adapt to changing environmental conditions through phenotypic plasticity and natural selection. Agrawal et al. (2018) found that dandelions responded to the presence of insect pests by producing higher levels of defensive compounds. This defensive response resulted both from phenotypic plasticity, with individual plants' defenses triggered by insect attack, and from evolution by natural selection acting on genetic variation in the plant population. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

NARCIS (Netherlands)

Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

2015-01-01

Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

NARCIS (Netherlands)

Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

Combining phenotypic and proteomic approaches to identify membrane targets in a ‘triple negative’ breast cancer cell type

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Rust Steven

2013-02-01

Full Text Available Abstract Background The continued discovery of therapeutic antibodies, which address unmet medical needs, requires the continued discovery of tractable antibody targets. Multiple protein-level target discovery approaches are available and these can be used in combination to extensively survey relevant cell membranomes. In this study, the MDA-MB-231 cell line was selected for membranome survey as it is a ‘triple negative’ breast cancer cell line, which represents a cancer subtype that is aggressive and has few treatment options. Methods The MDA-MB-231 breast carcinoma cell line was used to explore three membranome target discovery approaches, which were used in parallel to cross-validate the significance of identified antigens. A proteomic approach, which used membrane protein enrichment followed by protein identification by mass spectrometry, was used alongside two phenotypic antibody screening approaches. The first phenotypic screening approach was based on hybridoma technology and the second was based on phage display technology. Antibodies isolated by the phenotypic approaches were tested for cell specificity as well as internalisation and the targets identified were compared to each other as well as those identified by the proteomic approach. An anti-CD73 antibody derived from the phage display-based phenotypic approach was tested for binding to other ‘triple negative’ breast cancer cell lines and tested for tumour growth inhibitory activity in a MDA-MB-231 xenograft model. Results All of the approaches identified multiple cell surface markers, including integrins, CD44, EGFR, CD71, galectin-3, CD73 and BCAM, some of which had been previously confirmed as being tractable to antibody therapy. In total, 40 cell surface markers were identified for further study. In addition to cell surface marker identification, the phenotypic antibody screening approaches provided reagent antibodies for target validation studies. This is illustrated

Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

DEFF Research Database (Denmark)

Ansari-Mahyari, S; Berg, P; Lund, M S

2009-01-01

disequilibrium-based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals...... for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across...... the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However...

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

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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.

Quantitative Seq-LGS: Genome-Wide Identification of Genetic Drivers of Multiple Phenotypes in Malaria Parasites

KAUST Repository

Abkallo, Hussein M.

2016-10-01

Identifying the genetic determinants of phenotypes that impact on disease severity is of fundamental importance for the design of new interventions against malaria. Traditionally, such discovery has relied on labor-intensive approaches that require significant investments of time and resources. By combining Linkage Group Selection (LGS), quantitative whole genome population sequencing and a novel mathematical modeling approach (qSeq-LGS), we simultaneously identified multiple genes underlying two distinct phenotypes, identifying novel alleles for growth rate and strain specific immunity (SSI), while removing the need for traditionally required steps such as cloning, individual progeny phenotyping and marker generation. The detection of novel variants, verified by experimental phenotyping methods, demonstrates the remarkable potential of this approach for the identification of genes controlling selectable phenotypes in malaria and other apicomplexan parasites for which experimental genetic crosses are amenable.

Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat

NARCIS (Netherlands)

Atanur, Santosh S.; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R.; Kaisaki, Pamela J.; Otto, Georg W.; Ma, Man Chun John; Keane, Thomas M.; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R.; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J.; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J.

2013-01-01

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and

An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations.

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Arunabha Majumdar

2018-02-01

Full Text Available Simultaneous analysis of genetic associations with multiple phenotypes may reveal shared genetic susceptibility across traits (pleiotropy. For a locus exhibiting overall pleiotropy, it is important to identify which specific traits underlie this association. We propose a Bayesian meta-analysis approach (termed CPBayes that uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. This method uses a unified Bayesian statistical framework based on a spike and slab prior. CPBayes performs a fully Bayesian analysis by employing the Markov Chain Monte Carlo (MCMC technique Gibbs sampling. It takes into account heterogeneity in the size and direction of the genetic effects across traits. It can be applied to both cohort data and separate studies of multiple traits having overlapping or non-overlapping subjects. Simulations show that CPBayes can produce higher accuracy in the selection of associated traits underlying a pleiotropic signal than the subset-based meta-analysis ASSET. We used CPBayes to undertake a genome-wide pleiotropic association study of 22 traits in the large Kaiser GERA cohort and detected six independent pleiotropic loci associated with at least two phenotypes. This includes a locus at chromosomal region 1q24.2 which exhibits an association simultaneously with the risk of five different diseases: Dermatophytosis, Hemorrhoids, Iron Deficiency, Osteoporosis and Peripheral Vascular Disease. We provide an R-package 'CPBayes' implementing the proposed method.

Evolution of the additive genetic variance–covariance matrix under continuous directional selection on a complex behavioural phenotype

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Careau, Vincent; Wolak, Matthew E.; Carter, Patrick A.; Garland, Theodore

2015-01-01

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance–covariance matrix (G). Yet knowledge of G in a population experiencing new or altered selection is not sufficient to predict selection response because G itself evolves in ways that are poorly understood. We experimentally evaluated changes in G when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. PMID:26582016

Evolution of the additive genetic variance-covariance matrix under continuous directional selection on a complex behavioural phenotype.

Science.gov (United States)

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2015-11-22

Given the pace at which human-induced environmental changes occur, a pressing challenge is to determine the speed with which selection can drive evolutionary change. A key determinant of adaptive response to multivariate phenotypic selection is the additive genetic variance-covariance matrix ( G: ). Yet knowledge of G: in a population experiencing new or altered selection is not sufficient to predict selection response because G: itself evolves in ways that are poorly understood. We experimentally evaluated changes in G: when closely related behavioural traits experience continuous directional selection. We applied the genetic covariance tensor approach to a large dataset (n = 17 328 individuals) from a replicated, 31-generation artificial selection experiment that bred mice for voluntary wheel running on days 5 and 6 of a 6-day test. Selection on this subset of G: induced proportional changes across the matrix for all 6 days of running behaviour within the first four generations. The changes in G: induced by selection resulted in a fourfold slower-than-predicted rate of response to selection. Thus, selection exacerbated constraints within G: and limited future adaptive response, a phenomenon that could have profound consequences for populations facing rapid environmental change. © 2015 The Author(s).

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

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Amaury Vaysse

2011-10-01

Full Text Available The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

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

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

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping

DEFF Research Database (Denmark)

Vaysse, Amaury; Ratnakumar, Abhirami; Derrien, Thomas

2011-01-01

The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse br...

Phenotypic selection and regulation of reproduction in different environments in wild barley

NARCIS (Netherlands)

Volis, S.; Verhoeven, K.J.F.; Mendlinger, S.; Ward, D.

2004-01-01

Plasticity of the phenotypic architecture of wild barley, Hordeum spontaneum, was studied in response to water and nutrient stress. Direct and indirect selection on several vegetative and reproductive traits was estimated and path analysis used to reveal how regulating pathways via maternal

Sexual selection on multivariate phenotypes in Anastrepha Fraterculus (Diptera: Tephritidae) from Argentina

International Nuclear Information System (INIS)

Sciurano, R.; Rodriguero, M.; Gomez Cendra, P.; Vilardi, J.; Segura, D.; Cladera, J.L.; Allinghi, Armando

2007-01-01

Despite the interest in applying environmentally friendly control methods such as sterile insect technique (SIT) against Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae), information about its biology, taxonomy, and behavior is still insufficient. To increase this information, the present study aims to evaluate the performance of wild flies under field cage conditions through the study of sexual competitiveness among males (sexual selection). A wild population from Horco Molle, Tucuman, Argentina was sampled. Mature virgin males and females were released into outdoor field cages to compete for mating. Morphometric analyses were applied to determine the relationship between the multivariate phenotype and copulatory success. Successful and unsuccessful males were measured for 8 traits: head width (HW), face width (FW), eye length (EL), thorax length (THL), wing length (WL), wing width (WW), femur length (FL), and tibia length (TIL). Combinations of different multivariate statistical methods and graphical analyses were used to evaluate sexual selection on male phenotype. The results indicated that wing width and thorax length would be the most probable targets of sexual selection. They describe a non-linear association between expected fitness and each of these 2 traits. This non-linear relation suggests that observed selection could maintain the diversity related to body size. (author) [es

Phenotypes selected during chronic lung infection in cystic fibrosis patients

DEFF Research Database (Denmark)

Ciofu, Oana; Mandsberg, Lotte F; Wang, Hengzhuang

2012-01-01

During chronic lung infection of patients with cystic fibrosis, Pseudomonas aeruginosa can survive for long periods of time under the challenging selective pressure imposed by the immune system and antibiotic treatment as a result of its biofilm mode of growth and adaptive evolution mediated by g...... the importance of biofilm prevention strategies by early aggressive antibiotic prophylaxis or therapy before phenotypic diversification during chronic lung infection of patients with cystic fibrosis....

Altered fibre types in gastrocnemius muscle of high wheel-running selected mice with mini-muscle phenotypes.

Science.gov (United States)

Guderley, Helga; Joanisse, Denis R; Mokas, Sophie; Bilodeau, Geneviève M; Garland, Theodore

2008-03-01

Selective breeding of mice for high voluntary wheel running has favoured characteristics that facilitate sustained, aerobically supported activity, including a "mini-muscle" phenotype with markedly reduced hind limb muscle mass, increased mass-specific activities of oxidative enzymes, decreased % myosin heavy chain IIb, and, in the medial gastrocnemius, reduced twitch speed, reduced mass-specific isotonic power, and increased fatigue resistance. To evaluate whether selection has altered fibre type expression in mice with either "mini" or normal muscle phenotypes, we examined fibre types of red and white gastrocnemius. In both the medial and lateral gastrocnemius, the mini-phenotype increased activities of oxidative enzymes and decreased activities of glycolytic enzymes. In red muscle samples, the mini-phenotype markedly changed fibre types, with the % type I and type IIA fibres and the surface area of type IIA fibres increasing; in addition, mice from selected lines in general had an increased % type IIA fibres and larger type I fibres as compared with mice from control lines. White muscle samples from mini-mice showed dramatic structural alterations, with an atypical distribution of extremely small, unidentifiable fibres surrounded by larger, more oxidative fibres than normally present in white muscle. The increased proportion of oxidative fibres and these atypical small fibres together may explain the reduced mass and increased mitochondrial enzyme activities in mini-muscles. These and previous results demonstrate that extension of selective breeding beyond the time when the response of the selected trait (i.e. distance run) has levelled off can still modify the mechanistic underpinnings of this behaviour.

Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

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Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko

2017-07-01

Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

Parallel selective pressures drive convergent diversification of phenotypes in pythons and boas.

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Esquerré, Damien; Scott Keogh, J

2016-07-01

Pythons and boas are globally distributed and distantly related radiations with remarkable phenotypic and ecological diversity. We tested whether pythons, boas and their relatives have evolved convergent phenotypes when they display similar ecology. We collected geometric morphometric data on head shape for 1073 specimens representing over 80% of species. We show that these two groups display strong and widespread convergence when they occupy equivalent ecological niches and that the history of phenotypic evolution strongly matches the history of ecological diversification, suggesting that both processes are strongly coupled. These results are consistent with replicated adaptive radiation in both groups. We argue that strong selective pressures related to habitat-use have driven this convergence. Pythons and boas provide a new model system for the study of macro-evolutionary patterns of morphological and ecological evolution and they do so at a deeper level of divergence and global scale than any well-established adaptive radiation model systems. © 2016 John Wiley & Sons Ltd/CNRS.

The effects of stabilizing and directional selection on phenotypic and genotypic variation in a population of RNA enzymes.

Science.gov (United States)

Hayden, Eric J; Bratulic, Sinisa; Koenig, Iwo; Ferrada, Evandro; Wagner, Andreas

2014-02-01

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population's response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

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Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Collagen can selectively trigger a platelet secretory phenotype via glycoprotein VI.

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Véronique Ollivier

Full Text Available Platelets are not only central actors of hemostasis and thrombosis but also of other processes including inflammation, angiogenesis, and tissue regeneration. Accumulating evidence indicates that these "non classical" functions of platelets do not necessarily rely on their well-known ability to form thrombi upon activation. This suggests the existence of non-thrombotic alternative states of platelets activation. We investigated this possibility through dose-response analysis of thrombin- and collagen-induced changes in platelet phenotype, with regards to morphological and functional markers of platelet activation including shape change, aggregation, P-selectin and phosphatidylserine surface expression, integrin activation, and release of soluble factors. We show that collagen at low dose (0.25 µg/mL selectively triggers a platelet secretory phenotype characterized by the release of dense- and alpha granule-derived soluble factors without causing any of the other major platelet changes that usually accompany thrombus formation. Using a blocking antibody to glycoprotein VI (GPVI, we further show that this response is mediated by GPVI. Taken together, our results show that platelet activation goes beyond the mechanisms leading to platelet aggregation and also includes alternative platelet phenotypes that might contribute to their thrombus-independent functions.

Exploring venlafaxine pharmacokinetic variability with a phenotyping approach, a multicentric french-swiss study (MARVEL study).

Science.gov (United States)

Lloret-Linares, Célia; Daali, Youssef; Chevret, Sylvie; Nieto, Isabelle; Molière, Fanny; Courtet, Philippe; Galtier, Florence; Richieri, Raphaëlle-Marie; Morange, Sophie; Llorca, Pierre-Michel; El-Hage, Wissam; Desmidt, Thomas; Haesebaert, Frédéric; Vignaud, Philippe; Holtzmann, Jerôme; Cracowski, Jean-Luc; Leboyer, Marion; Yrondi, Antoine; Calvas, Fabienne; Yon, Liova; Le Corvoisier, Philippe; Doumy, Olivier; Heron, Kyle; Montange, Damien; Davani, Siamak; Déglon, Julien; Besson, Marie; Desmeules, Jules; Haffen, Emmanuel; Bellivier, Frank

2017-11-07

completed within approximately 2 years with 205 patients. Metabolic ratios are determined in Geneva, Switzerland. By showing an association between drug metabolism and VLX concentrations, efficacy and tolerance, there is a hope that testing drug metabolism pathways with a phenotypical approach would help physicians in selecting and dosing antidepressants. The MARVEL study will provide an important contribution to increasing the knowledge of VLX variability and in optimizing the use of methods of personalized therapy in psychiatric settings. ClinicalTrials.gov NCT02590185 (10/27/2015). This study is currently recruiting participants.

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Science.gov (United States)

Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan

2015-07-01

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

Phenotypic selection varies with pollination intensity across populations of Sabatia angularis.

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Emel, Sarah L; Franks, Steven J; Spigler, Rachel B

2017-07-01

Pollinators are considered primary selective agents acting on plant traits, and thus variation in the strength of the plant-pollinator interaction might drive variation in the opportunity for selection and selection intensity across plant populations. Here, we examine whether these critical evolutionary parameters covary with pollination intensity across wild populations of the biennial Sabatia angularis. We quantified pollination intensity in each of nine S. angularis populations as mean stigmatic pollen load per population. For female fitness and three components, fruit number, fruit set (proportion of flowers setting fruit) and number of seeds per fruit, we evaluated whether the opportunity for selection varied with pollination intensity. We used phenotypic selection analyses to test for interactions between pollination intensity and selection gradients for five floral traits, including flowering phenology. The opportunity for selection via fruit set and seeds per fruit declined significantly with increasing pollen receipt, as expected. We demonstrated significant directional selection on multiple traits across populations. We also found that selection intensity for all traits depended on pollination intensity. Consistent with general theory about the relationship between biotic interaction strength and the intensity of selection, our study suggests that variation in pollination intensity drives variation in selection across S. angularis populations. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders

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J. Patrick Malone

2013-05-01

Full Text Available The contribution of evolutionary psychology to the study of development and psychopathology depends on adherence to the principles of evolutionary biology. The human brain evolved because selection favored neither size nor complexity but instead the phenotypic plasticity supporting cognitive flexibility. Cell proliferation, migration, elongation, synaptogenesis, synaptic pruning, apoptosis, and myelination occur at varying rates during asynchronous phases of development throughout the brain. Developmentally sensitive periods result from phenotypic plasticity and are vital for adaptation to the environment. The biological systems surrounding the CYP19A1 gene provide mechanisms for neuroprotection and targeted neuronal debridement in response to environmental stress, uniting selection with developmental biology. Updates to Dunbar’s original hypothesis with current primatological data, inclusion of total brain mass, and the introduction of CYP19A1 orthology from nine primate species yields a linear regression, R 2 = .994, adjusted R 2 = .989, F(3, 5 = 143.758, p < .001.

Phenotypic selection on flowering phenology and pollination efficiency traits between Primula populations with different pollinator assemblages

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Wu, Yun; Li, Qing‐Jun

2017-01-01

Abstract Floral traits have largely been attributed to phenotypic selection in plant–pollinator interactions. However, the strength of this link has rarely been ascertained with real pollinators. We conducted pollinator observations and estimated selection through female fitness on flowering phenology and floral traits between two Primula secundiflora populations. We quantified pollinator‐mediated selection by subtracting estimates of selection gradients of plants receiving supplemental hand ...

An analysis of phenotypic selection in natural stands of northern red oak (Quercus rubra L.)

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Jeffery W. Stringer; David B. Wagner; Scott E. Schlarbaum; Daniel B. Houston

1995-01-01

Comparison of growth and stem quality parameters of 19-year-old progeny from superior and comparison trees indicates that rigorous phenotypic selection of trees in natural stands may not be an efficient method of parent tree selection for Quercus rubra L. Total tree height, dbh, number of branches in the butt log, fork height, and number of mainstem...

Utilization of genomic signatures to identify phenotype-specific drugs.

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Seiichi Mori

2009-08-01

Full Text Available Genetic and genomic studies highlight the substantial complexity and heterogeneity of human cancers and emphasize the general lack of therapeutics that can match this complexity. With the goal of expanding opportunities for drug discovery, we describe an approach that makes use of a phenotype-based screen combined with the use of multiple cancer cell lines. In particular, we have used the NCI-60 cancer cell line panel that includes drug sensitivity measures for over 40,000 compounds assayed on 59 independent cells lines. Targets are cancer-relevant phenotypes represented as gene expression signatures that are used to identify cells within the NCI-60 panel reflecting the signature phenotype and then connect to compounds that are selectively active against those cells. As a proof-of-concept, we show that this strategy effectively identifies compounds with selectivity to the RAS or PI3K pathways. We have then extended this strategy to identify compounds that have activity towards cells exhibiting the basal phenotype of breast cancer, a clinically-important breast cancer characterized as ER-, PR-, and Her2- that lacks viable therapeutic options. One of these compounds, Simvastatin, has previously been shown to inhibit breast cancer cell growth in vitro and importantly, has been associated with a reduction in ER-, PR- breast cancer in a clinical study. We suggest that this approach provides a novel strategy towards identification of therapeutic agents based on clinically relevant phenotypes that can augment the conventional strategies of target-based screens.

Practical Approaches for Detecting Selection in Microbial Genomes

OpenAIRE

Hedge, Jessica; Wilson, Daniel J.

2016-01-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers th...

A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks

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Xuezhong Zhou

2018-05-01

Full Text Available The International Classification of Diseases (ICD relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy. Keywords: Disease taxonomy, Network medicine, Disease phenotypes, Molecular profiles, Precision medicine

A test of phenotypic selection on petal form in the wild carnation, Dianthus inoxianus.

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Herrera, J; Balao, F

2015-11-01

Floral phenotypes are considered a product of pollinator-mediated selection, which also has the side effect of decreasing floral variation within species. Correlates of flower visibility and function were studied in a carnation species (Dianthus inoxianus), which has crepuscular anthesis and scent-based pollination by the hawkmoth Hyles livornica. We also assessed constancy of flower form in nature and in cultivation and, using fruit set as an estimate of plant relative fitness, tested whether the main pollinator exerted phenotypic selection on floral traits. Petal claw, which is roughly equivalent to the average depth at which an insect's proboscis must be inserted to reach nectar, was remarkably constant among wild plants (coefficient of variation 8%). In contrast, the area of the visible part of the petal, and the intensity of a coloured dot pattern on the petal was very variable (respectively CV = 34% and 102%). Cultivation in a common environment revealed significant variation among genotypes as regards petal area, degree of laciniation and extension of the dot pattern, but not petal claw length, which remained steady. Petal area, shape and colour did not affect relative fitness during the year of study, but plants with intermediate petal claws (i.e. floral tubes) set significantly more fruit. Results are compatible with low response of the main pollinator to variation in visual traits (petal area, laciniation, colour) and high responsiveness to variation in other aspects (tube length). Inconsistent phenotypic selection by pollinators may add to other causes of floral variation in the genus Dianthus, the causes of which are discussed. © 2015 German Botanical Society and The Royal Botanical Society of the Netherlands.

Selection of candidate plus phenotypes of Jatropha curcas L. using method of paired comparisons

Energy Technology Data Exchange (ETDEWEB)

Mishra, D.K. [Silviculture Division, Arid Forest Research Institute, P.O. Krishi Mandi, New Pali Road, Jodhpur 342005, Rajasthan (India)

2009-03-15

Jatropha curcas L. (Euphorbiaceae) is an oil bearing species with multiple uses and considerable potential as a biodiesel crop. The present communication deals with the method of selecting plus phenotypes of J. curcas for exploiting genetic variability for further improvement. Candidate plus tree selection is the first and most important stage in any tree improvement programme. The selection of candidate plus plants (CPPs) is based upon various important attributes associated with the species and their relative ranking. Relative preference between various traits and scoring for each trait has been worked out by using the method of paired comparisons for the selection of CPP in J. curcas L. The most important ones are seed and oil yields. (author)

Genetic and Computational Approaches for Studying Plant Development and Abiotic Stress Responses Using Image-Based Phenotyping

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Campbell, M. T.; Walia, H.; Grondin, A.; Knecht, A.

2017-12-01

The development of abiotic stress tolerant crops (i.e. drought, salinity, or heat stress) requires the discovery of DNA sequence variants associated with stress tolerance-related traits. However, many traits underlying adaptation to abiotic stress involve a suite of physiological pathways that may be induced at different times throughout the duration of stress. Conventional single-point phenotyping approaches fail to fully capture these temporal responses, and thus downstream genetic analysis may only identify a subset of the genetic variants that are important for adaptation to sub-optimal environments. Although genomic resources for crops have advanced tremendously, the collection of phenotypic data for morphological and physiological traits is laborious and remains a significant bottleneck in bridging the phenotype-genotype gap. In recent years, the availability of automated, image-based phenotyping platforms has provided researchers with an opportunity to collect morphological and physiological traits non-destructively in a highly controlled environment. Moreover, these platforms allow abiotic stress responses to be recorded throughout the duration of the experiment, and have facilitated the use of function-valued traits for genetic analyses in major crops. We will present our approaches for addressing abiotic stress tolerance in cereals. This talk will focus on novel open-source software to process and extract biological meaningful data from images generated from these phenomics platforms. In addition, we will discuss the statistical approaches to model longitudinal phenotypes and dissect the genetic basis of dynamic responses to these abiotic stresses throughout development.

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

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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

Body Temperature Measurements for Metabolic Phenotyping in Mice

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Meyer, Carola W.; Ootsuka, Youichirou; Romanovsky, Andrej A.

2017-01-01

Endothermic organisms rely on tightly balanced energy budgets to maintain a regulated body temperature and body mass. Metabolic phenotyping of mice, therefore, often includes the recording of body temperature. Thermometry in mice is conducted at various sites, using various devices and measurement practices, ranging from single-time probing to continuous temperature imaging. Whilst there is broad agreement that body temperature data is of value, procedural considerations of body temperature measurements in the context of metabolic phenotyping are missing. Here, we provide an overview of the various methods currently available for gathering body temperature data from mice. We explore the scope and limitations of thermometry in mice, with the hope of assisting researchers in the selection of appropriate approaches, and conditions, for comprehensive mouse phenotypic analyses. PMID:28824441

Practical Approaches for Detecting Selection in Microbial Genomes.

Science.gov (United States)

Hedge, Jessica; Wilson, Daniel J

2016-02-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

An invasive plant alters phenotypic selection on the vegetative growth of a native congener.

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Beans, Carolyn M; Roach, Deborah A

2015-02-01

The ecological consequences of plant competition have frequently been tested, but the evolutionary outcomes of these interactions have gone largely unexplored. The study of species invasions can make an important contribution to this field of research by allowing us to watch ecological and evolutionary processes unfold as a novel species is integrated into a plant community. We explored the ecological and evolutionary impact of an invasive jewelweed, Impatiens glandulifera, on a closely related native congener, I. capensis and asked: (1) Does the presence of the invasive jewelweed alter the fitness of native jewelweed populations? (2) Does the invasive jewelweed affect the vegetative growth of the native congener? and (3) Does the invasive jewelweed alter phenotypic selection on the vegetative traits of the native congener? We used a greenhouse competition experiment, an invasive species removal field experiment, and a survey of natural populations. We show that when the invasive jewelweed is present, phenotypic selection favors native jewelweed individuals investing less in rapid upward growth and more in branching and fruiting potential through the production of nodes. This research demonstrates that invasive plants have the potential to greatly alter natural selection on native competitors. Studies investigating altered selection in invaded communities can reveal the potential evolutionary impact of invasive competitors, while deepening our understanding of the more general role of competition in driving plant evolution and permitting species coexistence. © 2015 Botanical Society of America, Inc.

Accelerating the Switchgrass (Panicum virgatum L.) Breeding Cycle Using Genomic Selection Approaches

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Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.

2014-01-01

Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield. PMID:25390940

Species identification of Aspergillus section Flavi isolates from Portuguese almonds using phenotypic, including MALDI-TOF ICMS, and molecular approaches

OpenAIRE

Rodrigues, Paula; Venâncio, Armando; Lima, Nelson

2011-01-01

Section Flavi is one of the most significant Sections in the genus Aspergillus. Taxonomy of this section currently depends on multivariate approaches, entailing phenotypic and molecular traits. This work aimed to identify isolates from section Flavi by combining various classic phenotypic and genotypic methods as well as the novel approach based on spectral analysis by MALDI-TOF ICMS, and to evaluate the discriminatory power of the various approaches in species identification. Methods and ...

Practical Approaches for Detecting Selection in Microbial Genomes.

Directory of Open Access Journals (Sweden)

Jessica Hedge

2016-02-01

Full Text Available Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

Phenotypic Screening Approaches to Develop Aurora Kinase Inhibitors: Drug Discovery Perspectives.

Science.gov (United States)

Marugán, Carlos; Torres, Raquel; Lallena, María José

2015-01-01

Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins, such as Aurora-A and -B. Current drugs, which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules), have several side effects (neutropenia, alopecia, and emesis). Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype. We will briefly describe two multiplexing technologies [high-content imaging (HCI) and flow cytometry] and two key processes for drug discovery research (assay development and validation) following our own published industry quality standards. We will further focus on HCI as a useful tool for phenotypic screening and will provide a concrete example of HCI assay to detect Aurora-A or -B selective inhibitors discriminating the off-target effects related to the inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors.

The evolution of phenotypic integration: How directional selection reshapes covariation in mice.

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Penna, Anna; Melo, Diogo; Bernardi, Sandra; Oyarzabal, Maria Inés; Marroig, Gabriel

2017-10-01

Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection. © 2017 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Selection against aerial dispersal in ants: two non-flying queen phenotypes in Pogonomyrmex laticeps.

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Christian Peeters

Full Text Available The South American seed-harvester ant Pogonomyrmex laticeps has dimorphic queens: ergatoid (permanently wingless and brachypterous (short, non-functional wings. Surveys in western Argentina indicated that colonies near Chilecito, La Rioja Province, produced only ergatoid queens, while those near Punta Balasto, Catamarca Province (263 km away, produced only brachypterous queens. Brachypterous queens were significantly larger than ergatoid queens for 10 of 11 external characters, but both phenotypes had comparable reproductive potential, i.e., a spermatheca and a similar number of ovarioles. Using normal winged queens of the closely related P. uruguayensis for comparison, we determined that both queen phenotypes in P. laticeps had a full set of dorsal thoracic sclerites, albeit each sclerite was much reduced, whereas workers had a thorax without distinct dorsal sclerites. Sclerites were fused and immobile in ergatoid queens, while they were separable and fully articulated in brachypterous queens. Both phenotypes lacked the big indirect flight muscles, but brachypterous queens retained the tiny direct flight muscles. Overall, this dimorphism across populations indicates that there are alternative solutions to selective pressures against flying queens. We lack field data about colony founding strategy (independent or dependent for either queen phenotype, but colonies at both sites produced numerous gynes, and we infer that all foundresses initiate colonies independently and are obligate foragers.

Sexual and natural selection in the evolution of extended phenotypes: the use of green nesting material in starlings.

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Rubalcaba, J G; Polo, V; Maia, R; Rubenstein, D R; Veiga, J P

2016-08-01

Although sexual selection is typically considered the predominant force driving the evolution of ritualized sexual behaviours, natural selection may also play an important and often underappreciated role. The use of green aromatic plants among nesting birds has been interpreted as a component of extended phenotype that evolved either via natural selection due to potential sanitary functions or via sexual selection as a signal of male attractiveness. Here, we compared both hypotheses using comparative methods in starlings, a group where this behaviour is widespread. We found that the use of green plants was positively related to male-biased size dimorphism and that it was most likely to occur among cavity-nesting species. These results suggest that this behaviour is likely favoured by sexual selection, but also related to its sanitary use in response to higher parasite loads in cavities. We speculate that the use of green plants in starlings may be facilitated by cavity nesting and was subsequently co-opted as a sexual signal by males. Our results represent an example of how an extended phenotypic component of males becomes sexually selected by females. Thus, both natural selection and sexual selection are necessary to fully understand the evolution of ritualized behaviours involved in courtship. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Genomic Selection Using Extreme Phenotypes and Pre-Selection of SNPs in Large Yellow Croaker (Larimichthys crocea).

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Dong, Linsong; Xiao, Shijun; Chen, Junwei; Wan, Liang; Wang, Zhiyong

2016-10-01

Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.

Consistent selection towards low activity phenotypes when catchability depends on encounters among human predators and fish.

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Josep Alós

Full Text Available Together with life-history and underlying physiology, the behavioural variability among fish is one of the three main trait axes that determines the vulnerability to fishing. However, there are only a few studies that have systematically investigated the strength and direction of selection acting on behavioural traits. Using in situ fish behaviour revealed by telemetry techniques as input, we developed an individual-based model (IBM that simulated the Lagrangian trajectory of prey (fish moving within a confined home range (HR. Fishers exhibiting various prototypical fishing styles targeted these fish in the model. We initially hypothesised that more active and more explorative individuals would be systematically removed under all fished conditions, in turn creating negative selection differentials on low activity phenotypes and maybe on small HR. Our results partly supported these general predictions. Standardised selection differentials were, on average, more negative on HR than on activity. However, in many simulation runs, positive selection pressures on HR were also identified, which resulted from the stochastic properties of the fishes' movement and its interaction with the human predator. In contrast, there was a consistent negative selection on activity under all types of fishing styles. Therefore, in situations where catchability depends on spatial encounters between human predators and fish, we would predict a consistent selection towards low activity phenotypes and have less faith in the direction of the selection on HR size. Our study is the first theoretical investigation on the direction of fishery-induced selection of behaviour using passive fishing gears. The few empirical studies where catchability of fish was measured in relation to passive fishing techniques, such as gill-nets, traps or recreational fishing, support our predictions that fish in highly exploited situations are, on average, characterised by low swimming activity

Natural variation of model mutant phenotypes in Ciona intestinalis.

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Paolo Sordino

Full Text Available 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.

Natural Variation of Model Mutant Phenotypes in Ciona intestinalis

Science.gov (United States)

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

Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation

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Martinez Fernando J

2010-03-01

Full Text Available Abstract Background Numerous studies have demonstrated associations between genetic markers and COPD, but results have been inconsistent. One reason may be heterogeneity in disease definition. Unsupervised learning approaches may assist in understanding disease heterogeneity. Methods We selected 31 phenotypic variables and 12 SNPs from five candidate genes in 308 subjects in the National Emphysema Treatment Trial (NETT Genetics Ancillary Study cohort. We used factor analysis to select a subset of phenotypic variables, and then used cluster analysis to identify subtypes of severe emphysema. We examined the phenotypic and genotypic characteristics of each cluster. Results We identified six factors accounting for 75% of the shared variability among our initial phenotypic variables. We selected four phenotypic variables from these factors for cluster analysis: 1 post-bronchodilator FEV1 percent predicted, 2 percent bronchodilator responsiveness, and quantitative CT measurements of 3 apical emphysema and 4 airway wall thickness. K-means cluster analysis revealed four clusters, though separation between clusters was modest: 1 emphysema predominant, 2 bronchodilator responsive, with higher FEV1; 3 discordant, with a lower FEV1 despite less severe emphysema and lower airway wall thickness, and 4 airway predominant. Of the genotypes examined, membership in cluster 1 (emphysema-predominant was associated with TGFB1 SNP rs1800470. Conclusions Cluster analysis may identify meaningful disease subtypes and/or groups of related phenotypic variables even in a highly selected group of severe emphysema subjects, and may be useful for genetic association studies.

Data compression can discriminate broilers by selection line, detect haplotypes, and estimate genetic potential for complex phenotypes.

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Hudson, N J; Hawken, R J; Okimoto, R; Sapp, R L; Reverter, A

2017-09-01

Accurately establishing the relationships among individuals lays the foundation for genetic analyses such as genome-wide association studies and identification of selection signatures. Of particular interest to the poultry industry are estimates of genetic merit based on molecular data. These estimates can be commercially exploited in marker-assisted breeding programs to accelerate genetic improvement. Here, we test the utility of a new method we have recently developed to estimate animal relatedness and applied it to genetic parameter estimation in commercial broilers. Our approach is based on the concept of data compression from information theory. Using the real-world compressor gzip to estimate normalized compression distance (NCD) we have built compression-based relationship matrices (CRM) for 988 chickens from 4 commercial broiler lines-2 male and 2 female lines. For all pairs of individuals, we found a strong negative relationship between the commonly used genomic relationship matrix (GRM) and NCD. This reflects the fact that "similarity" is the inverse of "distance." The CRM explained more genetic variation than the corresponding GRM in 2 of 3 phenotypes, with corresponding improvements in accuracy of genomic-enabled predictions of breeding value. A sliding-window version of the analysis highlighted haplotype regions of the genome apparently under selection in a line-specific manner. In the male lines, we retrieved high population-specific scores for IGF-1 and a cognate receptor, INSR. For the female lines, we detected an extreme score for a region containing a reproductive hormone receptor (GNRHR). We conclude that our compression-based method is a valid approach to established relationships and identify regions under selective pressure in commercial lines of broiler chickens. © 2017 Poultry Science Association Inc.

Phenotypic screening approaches to develop Aurora kinase inhibitors: Drug Discovery perspectives

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Carlos eMarugán

2016-01-01

Full Text Available Targeting mitotic regulators as a strategy to fight cancer implies the development of drugs against key proteins such as Aurora A and B. Current drugs which target mitosis through a general mechanism of action (stabilization/destabilization of microtubules, have several side effects (neutropenia, alopecia, emesis. Pharmaceutical companies aim at avoiding these unwanted effects by generating improved and selective drugs that increase the quality of life of the patients. However, the development of these drugs is an ambitious task that involves testing thousands of compounds through biochemical and cell-based assays. In addition, molecules usually target complex biological processes, involving several proteins and different molecular pathways, further emphasizing the need for high-throughput screening techniques and multiplexing technologies in order to identify drugs with the desired phenotype.We will briefly describe two multiplexing technologies (high-content imaging, microarrays and flow cytometry and two key processes for drug discovery research (assay development and validation following our own published industry quality standards. We will further focus on high-content imaging as a useful tool for phenotypic screening and will provide a concrete example of high-content imaging assay to detect Aurora A or B selective inhibitors discriminating the off-target effects related to inhibition of other cell cycle or non-cell cycle key regulators. Finally, we will describe other assays that can help to characterize the in vitro pharmacology of the inhibitors.

Population structure and strong divergent selection shape phenotypic diversification in maize landraces.

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Pressoir, G; Berthaud, J

2004-02-01

To conserve the long-term selection potential of maize, it is necessary to investigate past and present evolutionary processes that have shaped quantitative trait variation. Understanding the dynamics of quantitative trait evolution is crucial to future crop breeding. We characterized population differentiation of maize landraces from the State of Oaxaca, Mexico for quantitative traits and molecular markers. Qst values were much higher than Fst values obtained for molecular markers. While low values of Fst (0.011 within-village and 0.003 among-villages) suggest that considerable gene flow occurred among the studied populations, high levels of population differentiation for quantitative traits were observed (ie an among-village Qst value of 0.535 for kernel weight). Our results suggest that although quantitative traits appear to be under strong divergent selection, a considerable amount of gene flow occurs among populations. Furthermore, we characterized nonproportional changes in the G matrix structure both within and among villages that are consequences of farmer selection. As a consequence of these differences in the G matrix structure, the response to multivariate selection will be different from one population to another. Large changes in the G matrix structure could indicate that farmers select for genes of major and pleiotropic effect. Farmers' decision and selection strategies have a great impact on phenotypic diversification in maize landraces.

Mining for genotype-phenotype relations in Saccharomyces using partial least squares

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Sæbø Solve

2011-08-01

Full Text Available Abstract Background Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS for mapping genotype-phenotype relations. Results Applying this methodology to an extensive data set for the model yeast Saccharomyces cerevisiae, we found that the relationship between genotype-phenotype involves surprisingly few genes in the sense that an overwhelmingly large fraction of the phenotypic variation can be explained by variation in less than 1% of the full gene reference set containing 5791 genes. These phenotype influencing genes were evolving 20% faster than non-influential genes and were unevenly distributed over cellular functions, with strong enrichments in functions such as cellular respiration and transposition. These genes were also enriched with known paralogs, stop codon variations and copy number variations, suggesting that such molecular adjustments have had a disproportionate influence on Saccharomyces yeasts recent adaptation to environmental changes in its ecological niche. Conclusions BLAST and PLS based multivariate approach derived results that adhere to the known yeast phylogeny and gene ontology and thus verify that the methodology extracts a set of fast evolving genes that capture the phylogeny of the yeast strains. The approach is worth pursuing, and future investigations should be made to improve the computations of genotype signals as well as variable selection procedure within the PLS framework.

Phenotypic and genetic diversification of Pseudanabaena spp. (cyanobacteria).

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Acinas, Silvia G; Haverkamp, Thomas H A; Huisman, Jef; Stal, Lucas J

2009-01-01

Pseudanabaena species are poorly known filamentous bloom-forming cyanobacteria closely related to Limnothrix. We isolated 28 Pseudanabaena strains from the Baltic Sea (BS) and the Albufera de Valencia (AV; Spain). By combining phenotypic and genotypic approaches, the phylogeny, diversity and evolutionary diversification of these isolates were explored. Analysis of the in vivo absorption spectra of the Pseudanabaena strains revealed two coexisting pigmentation phenotypes: (i) phycocyanin-rich (PC-rich) strains and (ii) strains containing both PC and phycoerythrin (PE). Strains of the latter phenotype were all capable of complementary chromatic adaptation (CCA). About 65 kb of the Pseudanabaena genomes were sequenced through a multilocus sequencing approach including the sequencing of the16 and 23S rRNA genes, the ribosomal intergenic spacer (IGS), internal transcribed spacer 1 (ITS-1), the cpcBA operon encoding PC and the IGS between cpcA and cpcB. In addition, the presence of nifH, one of the structural genes of nitrogenase, was investigated. Sequence analysis of ITS and cpcBA-IGS allowed the differentiation between Pseudanabaena isolates exhibiting high levels of microdiversity. This multilocus sequencing approach revealed specific clusters for the BS, the AV and a mixed cluster with strains from both ecosystems. The latter comprised exclusively CCA phenotypes. The phylogenies of the 16 and 23S rRNA genes are consistent, but analysis of other loci indicated the loss of substructure, suggesting that the recombination between these loci has occurred. Our preliminary results on population genetic analyses of the PC genes suggest an evolutionary diversification of Pseudanabaena through purifying selection.

Gut Microbiota and a Selectively Bred Taste Phenotype: A Novel Model of Microbiome-Behavior Relationships.

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Lyte, Mark; Fodor, Anthony A; Chapman, Clinton D; Martin, Gary G; Perez-Chanona, Ernesto; Jobin, Christian; Dess, Nancy K

2016-06-01

The microbiota-gut-brain axis is increasingly implicated in obesity, anxiety, stress, and other health-related processes. Researchers have proposed that gut microbiota may influence dietary habits, and pathways through the microbiota-gut-brain axis make such a relationship feasible; however, few data bear on the hypothesis. As a first step in the development of a model system, the gut microbiome was examined in rat lines selectively outbred on a taste phenotype with biobehavioral profiles that have diverged with respect to energy regulation, anxiety, and stress. Occidental low and high-saccharin-consuming rats were assessed for body mass and chow, water, and saccharin intake; littermate controls had shared cages with rats in the experimental group but were not assessed. Cecum and colon microbial communities were profiled using Illumina 16S rRNA sequencing and multivariate analysis of microbial diversity and composition. The saccharin phenotype was confirmed (low-saccharin-consuming rats, 0.7Δ% [0.9Δ%]; high-saccharin-consuming rats, 28.1Δ% [3.6Δ%]). Regardless of saccharin exposure, gut microbiota differed between lines in terms of overall community similarity and taxa at lower phylogenetic levels. Specifically, 16 genera in three phyla distinguished the lines at a 10% false discovery rate. The study demonstrates for the first time that rodent lines created through selective pressure on taste and differing on functionally related correlates host different microbial communities. Whether the microbiota are causally related to the taste phenotype or its correlates remains to be determined. These findings encourage further inquiry on the relationship of the microbiome to taste, dietary habits, emotion, and health.

Root Traits and Phenotyping Strategies for Plant Improvement.

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

2015-06-15

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

Root Traits and Phenotyping Strategies for Plant Improvement

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Ana Paez-Garcia

2015-06-01

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

Mutation Breeding and Selection for Phenotypic Mutants in Standard Rice Varieties by Ion Beam

International Nuclear Information System (INIS)

Puddhanon, Prawit; Pintanon, Prateep; Chaithep, Waree; Songjuntuke, Ksan

2009-07-01

Full text: Effects of 80 keV ion beam (10 16 ion/cm 2 on mutations of RD6 and Sanpatong 1 rice varieties were studied in 2006. In order to obtain the phenotypic mutants, each variety was sown in the laboratory and under field conditions at Maejo University in 2007 dry season. Seed germination noticeably declined. For RD6, only 45.1% germinated in the laboratory, and 18.1% were established under the field condition. Similarly, 62.3% of Sanpatong 1 germinated in the laboratory and 31.4% established in the field. No phenotypic mutants were observed in the first generation (M 1 ). The M2 seeds were harvested separately from 3 panicles of each M plant in RD6 and Sanpatong1, totaling 810 and 1,878 lines, respectively. In 2007 rainy season, they were planted on a panicle to row basis. It was found that more phenotypic mutants were observed in the M 2 for Sanpatong 1 than for RD6. The mutant characters included dwarf plants, early maturity, male sterility and larger panicle sizes. As a result, about 420 within line selections were collected and the M 3 seeds were harvested for further field condition and gene markers evaluations

A three-tier phenotyping approach for hunting QTLs related to heat tolerance in bread wheat

DEFF Research Database (Denmark)

Sharma, Dew Kumari; Rosenqvist, Eva; Ottosen, Carl-Otto

2014-01-01

In the global climate change scenario, heatstress together with other abiotic stresses will remain an importantdeterminant of future food security. Wheat (Triticum aestivum L.) is the third most important crop, feeding about one third of the world population. Being a crop of temperate climate......, wheat is sensitive to heat stress, particularly at the reproductive phase. Heat tolerance is a complex trait. In the present study, a combined approach of physiological phenotyping and quantitative genetics was used to dissect the complex nature of heat tolerance into photosynthesis related traits......- with a top-to-bottom (forward) approach: Tier 1: Phenotyping: As a starting point,the quantification of heat tolerance was done by the chlorophyll fluorescence parameter, Fv/Fm, as a measure of maximum quantum efficiency of PSII photochemistry after heat stress treatment (40°C for 72h). This way...

Robust and sensitive analysis of mouse knockout phenotypes.

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Natasha A Karp

Full Text Available 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.

Spice: discovery of phenotype-determining component interplays

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Chen Zhengzhang

2012-05-01

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

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

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Lande, Russell

2009-07-01

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

Assortment and the analysis of natural selection on social traits.

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McDonald, Grant C; Farine, Damien R; Foster, Kevin R; Biernaskie, Jay M

2017-11-01

A central problem in evolutionary biology is to determine whether and how social interactions contribute to natural selection. A key method for phenotypic data is social selection analysis, in which fitness effects from social partners contribute to selection only when there is a correlation between the traits of individuals and their social partners (nonrandom phenotypic assortment). However, there are inconsistencies in the use of social selection that center around the measurement of phenotypic assortment. Here, we use data analysis and simulations to resolve these inconsistencies, showing that: (i) not all measures of assortment are suitable for social selection analysis; and (ii) the interpretation of assortment, and how to detect nonrandom assortment, will depend on the scale at which it is measured. We discuss links to kin selection theory and provide a practical guide for the social selection approach. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

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Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C

2012-08-01

Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

From Genome to Phenotype: An Integrative Approach to Evaluate the Biodiversity of Lactococcus lactis

Science.gov (United States)

Laroute, Valérie; Tormo, Hélène; Couderc, Christel; Mercier-Bonin, Muriel; Le Bourgeois, Pascal; Cocaign-Bousquet, Muriel; Daveran-Mingot, Marie-Line

2017-01-01

Lactococcus lactis is one of the most extensively used lactic acid bacteria for the manufacture of dairy products. Exploring the biodiversity of L. lactis is extremely promising both to acquire new knowledge and for food and health-driven applications. L. lactis is divided into four subspecies: lactis, cremoris, hordniae and tructae, but only subsp. lactis and subsp. cremoris are of industrial interest. Due to its various biotopes, Lactococcus subsp. lactis is considered the most diverse. The diversity of L. lactis subsp. lactis has been assessed at genetic, genomic and phenotypic levels. Multi-Locus Sequence Type (MLST) analysis of strains from different origins revealed that the subsp. lactis can be classified in two groups: “domesticated” strains with low genetic diversity, and “environmental” strains that are the main contributors of the genetic diversity of the subsp. lactis. As expected, the phenotype investigation of L. lactis strains reported here revealed highly diverse carbohydrate metabolism, especially in plant- and gut-derived carbohydrates, diacetyl production and stress survival. The integration of genotypic and phenotypic studies could improve the relevance of screening culture collections for the selection of strains dedicated to specific functions and applications. PMID:28534821

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

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Lee Hyunju

2009-12-01

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

OligoPVP: Phenotype-driven analysis of individual genomic information to prioritize oligogenic disease variants

KAUST Repository

Boudellioua, Imene

2018-05-02

Purpose: An increasing number of Mendelian disorders have been identified for which two or more variants in one or more genes are required to cause the disease, or significantly modify its severity or phenotype. It is difficult to discover such interactions using existing approaches. The purpose of our work is to develop and evaluate a system that can identify combinations of variants underlying oligogenic diseases in individual whole exome or whole genome sequences. Methods: Information that links patient phenotypes to databases of gene-phenotype associations observed in clinical research can provide useful information and improve variant prioritization for Mendelian diseases. Additionally, background knowledge about interactions between genes can be utilized to guide and restrict the selection of candidate disease modules. Results: We developed OligoPVP, an algorithm that can be used to identify variants in oligogenic diseases and their interactions, using whole exome or whole genome sequences together with patient phenotypes as input. We demonstrate that OligoPVP has significantly improved performance when compared to state of the art pathogenicity detection methods. Conclusions: Our results show that OligoPVP can efficiently detect oligogenic interactions using a phenotype-driven approach and identify etiologically important variants in whole genomes.

High-Resolution Phenotypic Landscape of the RNA Polymerase II Trigger Loop.

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Chenxi Qiu

2016-11-01

Full Text Available The active sites of multisubunit RNA polymerases have a "trigger loop" (TL that multitasks in substrate selection, catalysis, and translocation. To dissect the Saccharomyces cerevisiae RNA polymerase II TL at individual-residue resolution, we quantitatively phenotyped nearly all TL single variants en masse. Three mutant classes, revealed by phenotypes linked to transcription defects or various stresses, have distinct distributions among TL residues. We find that mutations disrupting an intra-TL hydrophobic pocket, proposed to provide a mechanism for substrate-triggered TL folding through destabilization of a catalytically inactive TL state, confer phenotypes consistent with pocket disruption and increased catalysis. Furthermore, allele-specific genetic interactions among TL and TL-proximal domain residues support the contribution of the funnel and bridge helices (BH to TL dynamics. Our structural genetics approach incorporates structural and phenotypic data for high-resolution dissection of transcription mechanisms and their evolution, and is readily applicable to other essential yeast proteins.

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

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

2016-04-01

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

Cognition and gait show a selective pattern of association dominated by phenotype in incident Parkinson’s disease

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Sue eLord

2014-10-01

Full Text Available Reports outlining the association between gait and cognition in Parkinson’s disease (PD are limited because of methodological issues and a bias towards studying advanced disease. This study examines the association between gait and cognition in 121 early PD who were characterized according to motor phenotype, and 184 healthy older adults. Quantitative gait was captured using a 7m GAITrite walkway whilst walking for two minutes under single task conditions and described by five domains (pace, rhythm, variability, asymmetry and postural control. Cognitive outcomes were summarized by six domains (attention, working memory, visual memory, executive function, visuospatial function and global cognition. Partial correlations and multivariate linear regression were used to determine independent associations for all participants and for PD tremor-dominant (TD and postural instability and gait disorder (PIGD phenotypes, controlling for age, sex, and premorbid intelligence using the National Adult Reading Test (NART. Cognitive and gait outcomes were significantly worse for PD. Gait, but not cognitive outcomes, were selectively worse for the PIGD phenotype. Significant associations emerged for two gait domains for controls (pace and postural control and four gait domains for PD (pace, rhythm, variability, and postural control.The strongest correlation was for pace and attention for PD and controls. Associations were not significant for participants with the TD phenotype. In early PD the cognitive correlates of gait are predominantly with fronto-executive functions, and are determined by the PIGD PD phenotype. These associations provide a basis for understanding the complex role of cognition in Parkinsonian gait.

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

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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

Fluoroorotic acid-selected Nicotiana plumbaginifolia cell lines with a stable thymine starvation phenotype have lost the thymine-regulated transcriptional program.

Science.gov (United States)

Santoso, D; Thornburg, R

2000-08-01

We have selected 143 independent Nicotiana plumbaginifolia cell lines that survive in the presence of 5-fluoroorotic acid. These lines show several diverse phenotypes. The majority of these cell lines showed reduced levels of UMP synthase. However, one particular phenotype, which represents 14% of the total independent lines (20 cell lines), showed an unexpected, high level of UMP synthase and was therefore analyzed in detail. The selected cell lines showed no differences with wild-type cells with respect to uptake of orotic acid, affinity of UMP synthase for its substrates, or UMP synthase gene-copy number. Alternative detoxification mechanisms were also excluded. The elevated enzyme activity was correlated with elevated UMP synthase protein levels as well as elevated UMP synthase mRNA levels. In contrast to wild-type cell lines, the fluoroorotic acid-selected cell lines did not respond to thymine or to other biochemicals that affect thymine levels. In addition, there was also a concomitant up-regulation of aspartate transcarbamoylase, however, dihydroorotase and dihydroorotate dehydrogenase are not up-regulated in these cell lines.

CASSAVA BREEDING II: PHENOTYPIC CORRELATIONS THROUGH THE DIFFERENT STAGES OF SELECTION

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Orlando Joaqui Barandica

2016-12-01

Full Text Available Breeding cassava relies on a phenotypic recurrent selection that takes advantage of the vegetative propagation of this crop. Successive stages of selection (single row trial- SRT; preliminary yield trial – PYT; advanced yield trial – AYT; and uniform yield trials UYT, gradually reduce the number of genotypes as the plot size, number of replications and locations increase. An important feature of this scheme is that, because of the clonal, reproduction of cassava, the same identical genotypes are evaluated throughout these four successive stages of selection. For this study data, from 14 years (more than 30,000 data points of evaluation in a sub-humid tropical environment was consolidated for a meta-analysis. Correlation coefficients for fresh root yield (FRY, dry matter content (DMC, harvest index (HIN and plant type score (PTS along the different stages of selection were estimated. DMC and PTS measured in different trials showed the highest correlation coefficients, indicating a relatively good repeatability. HIN had an intermediate repeatability, whereas FRY had the lowest value. The association between HIN and FRY was lower than expected, suggesting that HIN in early stages was not reliable as indirect selection for FRY in later stages. There was a consistent decrease in the average performance of clones grown in PYTs compared with the earlier evaluation of the same genotypes at SRTs. A feasible explanation for this trend is the impact of the environment on the physiological and nutritional status of the planting material and/or epigenetic effects. The usefulness of HIN is questioned. Measuring this variable takes considerable efforts at harvest time. DMC and FRY showed a weak positive association in SRT (r= 0.21 but a clearly negative one at UYT (r= -0.42. The change if the relationship between these variables is the result of selection. In later stages of selection, the plant is forced to maximize productivity on a dry weight basis

Tumor cell phenotype is sustained by selective MAPK oxidation in mitochondria.

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Soledad Galli

2008-06-01

Full Text Available Mitochondria are major cellular sources of hydrogen peroxide (H(2O(2, the production of which is modulated by oxygen availability and the mitochondrial energy state. An increase of steady-state cell H(2O(2 concentration is able to control the transition from proliferating to quiescent phenotypes and to signal the end of proliferation; in tumor cells thereby, low H(2O(2 due to defective mitochondrial metabolism can contribute to sustain proliferation. Mitogen-activated protein kinases (MAPKs orchestrate signal transduction and recent data indicate that are present in mitochondria and regulated by the redox state. On these bases, we investigated the mechanistic connection of tumor mitochondrial dysfunction, H(2O(2 yield, and activation of MAPKs in LP07 murine tumor cells with confocal microscopy, in vivo imaging and directed mutagenesis. Two redox conditions were examined: low 1 microM H(2O(2 increased cell proliferation in ERK1/2-dependent manner whereas high 50 microM H(2O(2 arrested cell cycle by p38 and JNK1/2 activation. Regarding the experimental conditions as a three-compartment model (mitochondria, cytosol, and nuclei, the different responses depended on MAPKs preferential traffic to mitochondria, where a selective activation of either ERK1/2 or p38-JNK1/2 by co-localized upstream kinases (MAPKKs facilitated their further passage to nuclei. As assessed by mass spectra, MAPKs activation and efficient binding to cognate MAPKKs resulted from oxidation of conserved ERK1/2 or p38-JNK1/2 cysteine domains to sulfinic and sulfonic acids at a definite H(2O(2 level. Like this, high H(2O(2 or directed mutation of redox-sensitive ERK2 Cys(214 impeded binding to MEK1/2, caused ERK2 retention in mitochondria and restricted shuttle to nuclei. It is surmised that selective cysteine oxidations adjust the electrostatic forces that participate in a particular MAPK-MAPKK interaction. Considering that tumor mitochondria are dysfunctional, their inability to

The phenotypic variance gradient - a novel concept.

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Pertoldi, Cino; Bundgaard, Jørgen; Loeschcke, Volker; Barker, James Stuart Flinton

2014-11-01

Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life-history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely "a plot of log (variance) on the y-axis versus log (mean) on the x-axis, with a reference line added". This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a "phenotypic variance gradient", are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.

Behaviourally mediated phenotypic selection in a disturbed coral reef environment.

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Mark I McCormick

2009-09-01

Full Text Available Natural and anthropogenic disturbances are leading to changes in the nature of many habitats globally, and the magnitude and frequency of these perturbations are predicted to increase under climate change. Globally coral reefs are one of the most vulnerable ecosystems to climate change. Fishes often show relatively rapid declines in abundance when corals become stressed and die, but the processes responsible are largely unknown. This study explored the mechanism by which coral bleaching may influence the levels and selective nature of mortality on a juvenile damselfish, Pomacentrus amboinensis, which associates with hard coral. Recently settled fish had a low propensity to migrate small distances (40 cm between habitat patches, even when densities were elevated to their natural maximum. Intraspecific interactions and space use differ among three habitats: live hard coral, bleached coral and dead algal-covered coral. Large fish pushed smaller fish further from the shelter of bleached and dead coral thereby exposing smaller fish to higher mortality than experienced on healthy coral. Small recruits suffered higher mortality than large recruits on bleached and dead coral. Mortality was not size selective on live coral. Survival was 3 times as high on live coral as on either bleached or dead coral. Subtle behavioural interactions between fish and their habitats influence the fundamental link between life history stages, the distribution of phenotypic traits in the local population and potentially the evolution of life history strategies.

Phenotypic profiles of Armenian grape cultivars

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Aroutiounian Rouben

2015-01-01

Full Text Available The conservation and sustainable use of grapevine biodiversity in Armenia is particularly important due to the large number of traditional local varieties. Being partially different from European grapevine gene pool, the material of Armenian local cultivars significantly contributes to the understanding of the genetic variation and is valuable source for target selection. During last years many Armenian grapevine cultivars have been already described and their genotypes determined, but some local varieties and wild accessions remain unidentified and their phenotypic characteristics overlooked. The comprehensive analysis of phenotypes is essential for research, including genetic association studies, cultivar evaluation and selection. The goal of our research was the phenotyping on the base of reproductive, carpological and analytical characteristics of 80 Armenian aboriginal and new grape cultivars. Description of phenotypic profiles is important step towards identification and conservation of genetic resources of Armenian grapes. In future, these data can be applied for breeding of improved grape varieties targeted to fresh consumption and wine production.

Phenotypic selection on flowering phenology and pollination efficiency traits between Primula populations with different pollinator assemblages.

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Wu, Yun; Li, Qing-Jun

2017-10-01

Floral traits have largely been attributed to phenotypic selection in plant-pollinator interactions. However, the strength of this link has rarely been ascertained with real pollinators. We conducted pollinator observations and estimated selection through female fitness on flowering phenology and floral traits between two Primula secundiflora populations. We quantified pollinator-mediated selection by subtracting estimates of selection gradients of plants receiving supplemental hand pollination from those of plants receiving open pollination. There was net directional selection for an earlier flowering start date at populations where the dominant pollinators were syrphid flies, and flowering phenology was also subjected to stabilized quadratic selection. However, a later flowering start date was significantly selected at populations where the dominant pollinators were legitimate (normal pollination through the corolla tube entrance) and illegitimate bumblebees (abnormal pollination through nectar robbing hole which located at the corolla tube), and flowering phenology was subjected to disruptive quadratic selection. Wider corolla tube entrance diameter was selected at both populations. Furthermore, the strength of net directional selection on flowering start date and corolla tube entrance diameter was stronger at the population where the dominant pollinators were syrphid flies. Pollinator-mediated selection explained most of the between-population variations in the net directional selection on flowering phenology and corolla tube entrance diameter. Our results suggested the important influence of pollinator-mediated selection on floral evolution. Variations in pollinator assemblages not only resulted in variation in the direction of selection but also the strength of selection on floral traits.

Informatics and machine learning to define the phenotype.

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Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

Evolving phenotypic networks in silico.

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François, Paul

2014-11-01

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

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

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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

Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

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Elliot L. Heffner

2011-03-01

Full Text Available Genomic selection (GS uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotypes of lines from each cross before conducting GS. This will prolong the selection cycle and may result in lower gains per year than approaches that estimate marker-effects with multiple families from previous selection cycles. In this study, phenotypic selection (PS, conventional marker-assisted selection (MAS, and GS prediction accuracy were compared for 13 agronomic traits in a population of 374 winter wheat ( L. advanced-cycle breeding lines. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection, training population size, and marker density in the presence of genotype × environment interactions (G×E. The average prediction accuracies using GS were 28% greater than with MAS and were 95% as accurate as PS. For net merit, the average accuracy across six selection indices for GS was 14% greater than for PS. These results provide empirical evidence that multifamily GS could increase genetic gain per unit time and cost in plant breeding.

Identifying niche-mediated regulatory factors of stem cell phenotypic state: a systems biology approach.

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Ravichandran, Srikanth; Del Sol, Antonio

2017-02-01

Understanding how the cellular niche controls the stem cell phenotype is often hampered due to the complexity of variegated niche composition, its dynamics, and nonlinear stem cell-niche interactions. Here, we propose a systems biology view that considers stem cell-niche interactions as a many-body problem amenable to simplification by the concept of mean field approximation. This enables approximation of the niche effect on stem cells as a constant field that induces sustained activation/inhibition of specific stem cell signaling pathways in all stem cells within heterogeneous populations exhibiting the same phenotype (niche determinants). This view offers a new basis for the development of single cell-based computational approaches for identifying niche determinants, which has potential applications in regenerative medicine and tissue engineering. © 2017 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Fluoroorotic Acid-Selected Nicotiana plumbaginifolia Cell Lines with a Stable Thymine Starvation Phenotype Have Lost the Thymine-Regulated Transcriptional Program1

Science.gov (United States)

Santoso, Djoko; Thornburg, Robert

2000-01-01

We have selected 143 independent Nicotiana plumbaginifolia cell lines that survive in the presence of 5-fluoroorotic acid. These lines show several diverse phenotypes. The majority of these cell lines showed reduced levels of UMP synthase. However, one particular phenotype, which represents 14% of the total independent lines (20 cell lines), showed an unexpected, high level of UMP synthase and was therefore analyzed in detail. The selected cell lines showed no differences with wild-type cells with respect to uptake of orotic acid, affinity of UMP synthase for its substrates, or UMP synthase gene-copy number. Alternative detoxification mechanisms were also excluded. The elevated enzyme activity was correlated with elevated UMP synthase protein levels as well as elevated UMP synthase mRNA levels. In contrast to wild-type cell lines, the fluoroorotic acid-selected cell lines did not respond to thymine or to other biochemicals that affect thymine levels. In addition, there was also a concomitant up-regulation of aspartate transcarbamoylase, however, dihydroorotase and dihydroorotate dehydrogenase are not up-regulated in these cell lines. PMID:10938367

Phenotypic plasticity and effects of selection on cell division symmetry in Escherichia coli.

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Uttara N Lele

Full Text Available Aging has been demonstrated in unicellular organisms and is presumably due to asymmetric distribution of damaged proteins and other components during cell division. Whether the asymmetry-induced aging is inevitable or an adaptive and adaptable response is debated. Although asymmetric division leads to aging and death of some cells, it increases the effective growth rate of the population as shown by theoretical and empirical studies. Mathematical models predict on the other hand, that if the cells divide symmetrically, cellular aging may be delayed or absent, growth rate will be reduced but growth yield will increase at optimum repair rates. Therefore in nutritionally dilute (oligotrophic environments, where growth yield may be more critical for survival, symmetric division may get selected. These predictions have not been empirically tested so far. We report here that Escherichia coli grown in oligotrophic environments had greater morphological and functional symmetry in cell division. Both phenotypic plasticity and genetic selection appeared to shape cell division time asymmetry but plasticity was lost on prolonged selection. Lineages selected on high nutrient concentration showed greater frequency of presumably old or dead cells. Further, there was a negative correlation between cell division time asymmetry and growth yield but there was no significant correlation between asymmetry and growth rate. The results suggest that cellular aging driven by asymmetric division may not be hardwired but shows substantial plasticity as well as evolvability in response to the nutritional environment.

A systematic review of COTS evaluation and selection approaches

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Rakesh Garg

2017-11-01

Full Text Available In the past decades, a number of researchers have made their significant contributions to develop different approaches for solving a very challenging problem of commercial off-the shelf (COTS selection. The development of software with high quality and minimum development time has always been a difficult job for the software developers. Therefore, in today’s scenario, software developers move towards the implementation of component based software engineering that relies on the integration of small pieces of code namely (COTS. In this study, we present a comprehensive descriptive explanation of the various COTS evaluation and selection approaches developed by various researchers in the past to understand the concept of COTS selection. The advantages and disadvantages of each COTS selection approach are also provided, which will give a better prospect to the readers to understand the various existing COTS evaluation and selection approaches.

Model-assisted phenotyping by digital images in papaya breeding program

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Diego Fernando Marmolejo Cortes

Full Text Available ABSTRACT Manual phenotyping for papaya Carica papaya (L breeding purposes limits the evaluation of a great number of plants and hampers selection of superior genotypes. This study aimed to validate two methodologies for the phenotyping of morpho-agronomic plant traits using image analysis and fruit traits through image processing. In plants of the ‘THB’ variety and ‘UENF/Caliman-01’ hybrid two images (A and B were analyzed to estimate commercial and irregularly shaped fruits. Image A was also used in the estimation of plant height, stem diameter and the first fruit insertion height. In ‘THB’ fruits, largest and smallest diameters, length, and volume were estimated by using a caliper and image processing (IP. Volume was obtained by water column displacement (WCD and by the expression of ellipsoid approximation (EA. Correlations above 0.85 between manual and image measurements were obtained for all traits. The averages of the morpho-agronomic traits, estimated by using images, were similar when compared to the averages measured manually. In addition, the errors of the proposed methodologies were low compared to manual phenotyping. Bland-Altman's approach indicated agreement between the volume estimated by WCD and EA using caliper and IP. The strong association obtained between volume and fruit weight suggests the use of regression to estimate this trait. Thus, the expectation is that image-based phenotyping can be used to expand the experiments, thereby maintaining accuracy and providing greater genetic gains in the selection of superior genotypes.

Global change and the evolution of phenotypic plasticity in plants.

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Matesanz, Silvia; Gianoli, Ernesto; Valladares, Fernando

2010-09-01

Global change drivers create new environmental scenarios and selective pressures, affecting plant species in various interacting ways. Plants respond with changes in phenology, physiology, and reproduction, with consequences for biotic interactions and community composition. We review information on phenotypic plasticity, a primary means by which plants cope with global change scenarios, recommending promising approaches for investigating the evolution of plasticity and describing constraints to its evolution. We discuss the important but largely ignored role of phenotypic plasticity in range shifts and review the extensive literature on invasive species as models of evolutionary change in novel environments. Plasticity can play a role both in the short-term response of plant populations to global change as well as in their long-term fate through the maintenance of genetic variation. In new environmental conditions, plasticity of certain functional traits may be beneficial (i.e., the plastic response is accompanied by a fitness advantage) and thus selected for. Plasticity can also be relevant in the establishment and persistence of plants in novel environments that are crucial for populations at the colonizing edge in range shifts induced by climate change. Experimental studies show taxonomically widespread plastic responses to global change drivers in many functional traits, though there is a lack of empirical support for many theoretical models on the evolution of phenotypic plasticity. Future studies should assess the adaptive value and evolutionary potential of plasticity under complex, realistic global change scenarios. Promising tools include resurrection protocols and artificial selection experiments. © 2010 New York Academy of Sciences.

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

Science.gov (United States)

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

2011-07-01

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

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

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Md. Matiur eRahaman

2015-08-01

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

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

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Tallulah Andrews

2015-03-01

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

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

Science.gov (United States)

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

2015-03-01

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

Testing evolutionary hypotheses for phenotypic divergence using landscape genetics.

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Funk, W Chris; Murphy, Melanie A

2010-02-01

Understanding the evolutionary causes of phenotypic variation among populations has long been a central theme in evolutionary biology. Several factors can influence phenotypic divergence, including geographic isolation, genetic drift, divergent natural or sexual selection, and phenotypic plasticity. But the relative importance of these factors in generating phenotypic divergence in nature is still a tantalizing and unresolved problem in evolutionary biology. The origin and maintenance of phenotypic divergence is also at the root of many ongoing debates in evolutionary biology, such as the extent to which gene flow constrains adaptive divergence (Garant et al. 2007) and the relative importance of genetic drift, natural selection, and sexual selection in initiating reproductive isolation and speciation (Coyne & Orr 2004). In this issue, Wang & Summers (2010) test the causes of one of the most fantastic examples of phenotypic divergence in nature: colour pattern divergence among populations of the strawberry poison frog (Dendrobates pumilio) in Panama and Costa Rica (Fig. 1). This study provides a beautiful example of the use of the emerging field of landscape genetics to differentiate among hypotheses for phenotypic divergence. Using landscape genetic analyses, Wang & Summers were able to reject the hypotheses that colour pattern divergence is due to isolation-by-distance (IBD) or landscape resistance. Instead, the hypothesis left standing is that colour divergence is due to divergent selection, in turn driving reproductive isolation among populations with different colour morphs. More generally, this study provides a wonderful example of how the emerging field of landscape genetics, which has primarily been applied to questions in conservation and ecology, now plays an essential role in evolutionary research.

Phenotype ontologies and cross-species analysis for translational research.

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Peter N Robinson

2014-04-01

Full Text Available The use of model organisms as tools for the investigation of human genetic variation has significantly and rapidly advanced our understanding of the aetiologies underlying hereditary traits. However, while equivalences in the DNA sequence of two species may be readily inferred through evolutionary models, the identification of equivalence in the phenotypic consequences resulting from comparable genetic variation is far from straightforward, limiting the value of the modelling paradigm. In this review, we provide an overview of the emerging statistical and computational approaches to objectively identify phenotypic equivalence between human and model organisms with examples from the vertebrate models, mouse and zebrafish. Firstly, we discuss enrichment approaches, which deem the most frequent phenotype among the orthologues of a set of genes associated with a common human phenotype as the orthologous phenotype, or phenolog, in the model species. Secondly, we introduce and discuss computational reasoning approaches to identify phenotypic equivalences made possible through the development of intra- and interspecies ontologies. Finally, we consider the particular challenges involved in modelling neuropsychiatric disorders, which illustrate many of the remaining difficulties in developing comprehensive and unequivocal interspecies phenotype mappings.

Survey for service selection approaches in dynamic environments

CSIR Research Space (South Africa)

Manqele, Lindelweyizizwe S

2017-09-01

Full Text Available The usage of the service selection approaches across different dynamic service provisioning environments has increased the challenges associated with an effective method that can be used to select a relevant service. The use of service selection...

PhenoTips: Patient Phenotyping Software for Clinical and Research Use.

OpenAIRE

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

2014-01-01

We have developed PhenoTips, a deep phenotyping tool and database, specifically designed for phenotyping patients with genetic disorders. Our tool closely mirrors clinician workflows so as to facilitate the recording of observations made during the patient encounter. 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, predic...

Selection based on the size of the black tie of the great tit may be reversed in urban habitats

OpenAIRE

Senar, Juan Carlos; Conroy, Michael J; Quesada, Javier; Mateos-Gonzalez, Fernando

2014-01-01

A standard approach to model how selection shapes phenotypic traits is the analysis of capture-recapture data relating trait variation to survival. Divergent selection, however, has never been analyzed by the capture-recapture approach. Most reported examples of differences between urban and nonurban animals reflect behavioral plasticity rather than divergent selection. The aim of this paper was to use a capture-recapture approach to test the hypothesis that divergent selection can also drive...

The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

Science.gov (United States)

Lievens, Filip; Sackett, Paul R

2017-01-01

Past reviews and meta-analyses typically conceptualized and examined selection procedures as holistic entities. We draw on the product design literature to propose a modular approach as a complementary perspective to conceptualizing selection procedures. A modular approach means that a product is broken down into its key underlying components. Therefore, we start by presenting a modular framework that identifies the important measurement components of selection procedures. Next, we adopt this modular lens for reviewing the available evidence regarding each of these components in terms of affecting validity, subgroup differences, and applicant perceptions, as well as for identifying new research directions. As a complement to the historical focus on holistic selection procedures, we posit that the theoretical contributions of a modular approach include improved insight into the isolated workings of the different components underlying selection procedures and greater theoretical connectivity among different selection procedures and their literatures. We also outline how organizations can put a modular approach into operation to increase the variety in selection procedures and to enhance the flexibility in designing them. Overall, we believe that a modular perspective on selection procedures will provide the impetus for programmatic and theory-driven research on the different measurement components of selection procedures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Constraints on the evolution of phenotypic plasticity

DEFF Research Database (Denmark)

Murren, Courtney J; Auld, Josh R.; Callahan, Hilary S

2015-01-01

Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce...... an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits...... to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently...

Categorization and selection of regulatory approaches for nuclear power plants

International Nuclear Information System (INIS)

Sugaya, Junko; Harayama, Yuko

2009-01-01

Several new regulatory approaches have been introduced to Japanese nuclear safety regulations, in which a prescriptive and deterministic approach had traditionally predominated. However, the options of regulatory approaches that can possibly be applied to nuclear safety regulations as well as the methodology for selecting the options are not systematically defined. In this study, various regulatory approaches for nuclear power plants are categorized as prescriptive or nonprescriptive, outcome-based or process-based, and deterministic or risk-informed. 18 options of regulatory approaches are conceptually developed and the conditions for selecting the appropriate regulatory approaches are identified. Current issues on nuclear regulations regarding responsibilities, transparency, consensus standards and regulatory inspections are examined from the viewpoints of regulatory approaches to verify usefulness of the categorization and selection concept of regulatory approaches. Finally, some of the challenges at the transitional phase of regulatory approaches are discussed. (author)

Genomic selection accuracy using multi-family prediction models in a wheat breeding program

Science.gov (United States)

Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

Power and type I error results for a bias-correction approach recently shown to provide accurate odds ratios of genetic variants for the secondary phenotypes associated with primary diseases.

Science.gov (United States)

Wang, Jian; Shete, Sanjay

2011-11-01

We recently proposed a bias correction approach to evaluate accurate estimation of the odds ratio (OR) of genetic variants associated with a secondary phenotype, in which the secondary phenotype is associated with the primary disease, based on the original case-control data collected for the purpose of studying the primary disease. As reported in this communication, we further investigated the type I error probabilities and powers of the proposed approach, and compared the results to those obtained from logistic regression analysis (with or without adjustment for the primary disease status). We performed a simulation study based on a frequency-matching case-control study with respect to the secondary phenotype of interest. We examined the empirical distribution of the natural logarithm of the corrected OR obtained from the bias correction approach and found it to be normally distributed under the null hypothesis. On the basis of the simulation study results, we found that the logistic regression approaches that adjust or do not adjust for the primary disease status had low power for detecting secondary phenotype associated variants and highly inflated type I error probabilities, whereas our approach was more powerful for identifying the SNP-secondary phenotype associations and had better-controlled type I error probabilities. © 2011 Wiley Periodicals, Inc.

Molecular Ecological Basis of Grasshopper (Oedaleus asiaticus) Phenotypic Plasticity under Environmental Selection

Science.gov (United States)

Qin, Xinghu; Hao, Kun; Ma, Jingchuan; Huang, Xunbing; Tu, Xiongbing; Ali, Md. Panna; Pittendrigh, Barry R.; Cao, Guangchun; Wang, Guangjun; Nong, Xiangqun; Whitman, Douglas W.; Zhang, Zehua

2017-01-01

While ecological adaptation in insects can be reflected by plasticity of phenotype, determining the causes and molecular mechanisms for phenotypic plasticity (PP) remains a crucial and still difficult question in ecology, especially where control of insect pests is involved. Oedaleus asiaticus is one of the most dominant pests in the Inner Mongolia steppe and represents an excellent system to study phenotypic plasticity. To better understand ecological factors affecting grasshopper phenotypic plasticity and its molecular control, we conducted a full transcriptional screening of O. asiaticus grasshoppers reared in four different grassland patches in Inner Mongolia. Grasshoppers showed different degrees of PP associated with unique gene expressions and different habitat plant community compositions. Grasshopper performance variables were susceptible to habitat environment conditions and closely associated with plant architectures. Intriguingly, eco-transcriptome analysis revealed five potential candidate genes playing important roles in grasshopper performance, with gene expression closely relating to PP and plant community factors. By linking the grasshopper performances to gene profiles and ecological factors using canonical regression, we first demonstrated the eco-transcriptomic architecture (ETA) of grasshopper phenotypic traits (ETAGPTs). ETAGPTs revealed plant food type, plant density, coverage, and height were the main ecological factors influencing PP, while insect cuticle protein (ICP), negative elongation factor A (NELFA), and lactase-phlorizin hydrolase (LCT) were the key genes associated with PP. Our study gives a clear picture of gene-environment interaction in the formation and maintenance of PP and enriches our understanding of the transcriptional events underlying molecular control of rapid phenotypic plasticity associated with environmental variability. The findings of this study may also provide new targets for pest control and highlight the

Molecular Ecological Basis of Grasshopper (Oedaleus asiaticus Phenotypic Plasticity under Environmental Selection

Directory of Open Access Journals (Sweden)

Xinghu Qin

2017-10-01

Full Text Available While ecological adaptation in insects can be reflected by plasticity of phenotype, determining the causes and molecular mechanisms for phenotypic plasticity (PP remains a crucial and still difficult question in ecology, especially where control of insect pests is involved. Oedaleus asiaticus is one of the most dominant pests in the Inner Mongolia steppe and represents an excellent system to study phenotypic plasticity. To better understand ecological factors affecting grasshopper phenotypic plasticity and its molecular control, we conducted a full transcriptional screening of O. asiaticus grasshoppers reared in four different grassland patches in Inner Mongolia. Grasshoppers showed different degrees of PP associated with unique gene expressions and different habitat plant community compositions. Grasshopper performance variables were susceptible to habitat environment conditions and closely associated with plant architectures. Intriguingly, eco-transcriptome analysis revealed five potential candidate genes playing important roles in grasshopper performance, with gene expression closely relating to PP and plant community factors. By linking the grasshopper performances to gene profiles and ecological factors using canonical regression, we first demonstrated the eco-transcriptomic architecture (ETA of grasshopper phenotypic traits (ETAGPTs. ETAGPTs revealed plant food type, plant density, coverage, and height were the main ecological factors influencing PP, while insect cuticle protein (ICP, negative elongation factor A (NELFA, and lactase-phlorizin hydrolase (LCT were the key genes associated with PP. Our study gives a clear picture of gene-environment interaction in the formation and maintenance of PP and enriches our understanding of the transcriptional events underlying molecular control of rapid phenotypic plasticity associated with environmental variability. The findings of this study may also provide new targets for pest control and

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

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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.

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

Science.gov (United States)

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

2013-06-01

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

Statistical approach for selection of biologically informative genes.

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Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes

Phenotyping of Brassica napus for high oil content

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Multi-trait and multi-growth stage phenotyping may improve our ability to assess the dynamic changes in the B. napus phenome under spatiotemporal field conditions. A minimum set of phenotypic traits that can integrate ontogeny and architecture of Brassica napus L. is required for breeding and select...

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

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Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

African Journals Online (AJOL)

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

Adaptive evolution in locomotor performance: How selective pressures and functional relationships produce diversity.

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Scales, Jeffrey A; Butler, Marguerite A

2016-01-01

Despite the complexity of nature, most comparative studies of phenotypic evolution consider selective pressures in isolation. When competing pressures operate on the same system, it is commonly expected that trade-offs will occur that will limit the evolution of phenotypic diversity, however, it is possible that interactions among selective pressures may promote diversity instead. We explored the evolution of locomotor performance in lizards in relation to possible selective pressures using the Ornstein-Uhlenbeck process. Here, we show that a combination of selection based on foraging mode and predator escape is required to explain variation in performance phenotypes. Surprisingly, habitat use contributed little explanatory power. We find that it is possible to evolve very different abilities in performance which were previously thought to be tightly correlated, supporting a growing literature that explores the many-to-one mapping of morphological design. Although we generally find the expected trade-off between maximal exertion and speed, this relationship surprisingly disappears when species experience selection for both performance types. We conclude that functional integration need not limit adaptive potential, and that an integrative approach considering multiple major influences on a phenotype allows a more complete understanding of adaptation and the evolution of diversity. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Decomposing phenotype descriptions for the human skeletal phenome.

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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.

Chemical rationale for selection of isolates for genome sequencing

DEFF Research Database (Denmark)

Rank, Christian; Larsen, Thomas Ostenfeld; Frisvad, Jens Christian

The advances in gene sequencing will in the near future enable researchers to affordably acquire the full genomes of handpicked isolates. We here present a method to evaluate the chemical potential of an entire species and select representatives for genome sequencing. The selection criteria for new...... strains to be sequenced can be manifold, but for studying the functional phenotype, using a metabolome based approach offers a cheap and rapid assessment of critical strains to cover the chemical diversity. We have applied this methodology on the complex A. flavus/A. oryzae group. Though these two species...... are in principal identical, they represent two different phenotypes. This is clearly presented through a correspondence analysis of selected extrolites, in which the subtle chemical differences are visually dispersed. The results points to a handful of strains, which, if sequenced, will likely enhance our...

Species identification of Aspergillus section Flavi isolates from Portuguese almonds using phenotypic, including MALDI-TOF ICMS, and molecular approaches.

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Rodrigues, P; Santos, C; Venâncio, A; Lima, N

2011-10-01

Section Flavi is one of the most significant sections in the genus Aspergillus. Taxonomy of this section currently depends on multivariate approaches, entailing phenotypic and molecular traits. This work aimed to identify isolates from section Flavi by combining various classic phenotypic and genotypic methods as well as the novel approach based on spectral analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF ICMS) and to evaluate the discriminatory power of the various approaches in species identification.   Aspergillus section Flavi isolates obtained from Portuguese almonds were characterized in terms of macro- and micromorphology, mycotoxin pattern, calmodulin gene sequence and MALDI-TOF protein fingerprint spectra. For each approach, dendrograms were created and results were compared. All data sets divided the isolates into three groups, corresponding to taxa closely related to Aspergillus flavus, Aspergillus parasiticus and Aspergillus tamarii. In the A. flavus clade, molecular and spectral analyses were not able to resolve between aflatoxigenic and nonaflatoxigenic isolates. In the A. parasiticus cluster, two well-resolved clades corresponded to unidentified taxa, corresponding to those isolates with mycotoxin profile different from that expected for A. parasiticus. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Environmental carbonate chemistry selects for phenotype of recently isolated strains of Emiliania huxleyi

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Rickaby, Rosalind E. M.; Hermoso, Michaël; Lee, Renee B. Y.; Rae, Benjamin D.; Heureux, Ana M. C.; Balestreri, Cecilia; Chakravarti, Leela; Schroeder, Declan C.; Brownlee, Colin

2016-05-01

Coccolithophorid algae, particularly Emiliania huxleyi, are prolific biomineralisers that, under many conditions, dominate communities of marine eukaryotic plankton. Their ability to photosynthesise and form calcified scales (coccoliths) has placed them in a unique position in the global carbon cycle. Contrasting reports have been made with regards to the response of E. huxleyi to ocean acidification. Therefore, there is a pressing need to further determine the fate of this key organism in a rising CO2 world. In this paper, we investigate the phenotype of newly isolated, genetically diverse, strains of E. huxleyi from UK Ocean Acidification Research Programme (UKOA) cruises around the British Isles, the Arctic, and the Southern Ocean. We find a continuum of diversity amongst the physiological and photosynthetic parameters of different strains of E. huxleyi morphotype A under uniform, ambient conditions imposed in the laboratory. This physiology is best explained by adaptation to carbonate chemistry in the former habitat rather than being prescribed by genetic fingerprints such as the coccolithophore morphology motif (CMM). To a first order, the photosynthetic capacity of each strain is a function of both aqueous CO2 availability, and calcification rate, suggestive of a link between carbon concentrating ability and calcification. The calcification rate of each strain is related linearly to the natural environmental [CO32-] at the site of isolation, but a few exceptional strains display low calcification rates at the highest [CO32-] when calcification is limited by low CO2 availability and/or a lack of a carbon concentrating mechanism. We present O2-electrode measurements alongside coccolith oxygen isotopic composition and the uronic acid content (UAC) of the coccolith associated polysaccharide (CAP), that act as indirect tools to show the differing carbon concentrating ability of the strains. The environmental selection revealed amongst our recently isolated strain

Mining skeletal phenotype descriptions from scientific literature.

Directory of Open Access Journals (Sweden)

Tudor Groza

Full Text Available Phenotype descriptions are important for our understanding of genetics, as they enable the computation and analysis of a varied range of issues related to the genetic and developmental bases of correlated characters. The literature contains a wealth of such phenotype descriptions, usually reported as free-text entries, similar to typical clinical summaries. In this paper, we focus on creating and making available an annotated corpus of skeletal phenotype descriptions. In addition, we present and evaluate a hybrid Machine Learning approach for mining phenotype descriptions from free text. Our hybrid approach uses an ensemble of four classifiers and experiments with several aggregation techniques. The best scoring technique achieves an F-1 score of 71.52%, which is close to the state-of-the-art in other domains, where training data exists in abundance. Finally, we discuss the influence of the features chosen for the model on the overall performance of the method.

Phenotyping animal models of diabetic neuropathy

DEFF Research Database (Denmark)

Biessels, G J; Bril, V; Calcutt, N A

2014-01-01

NIDDK, JDRF, and the Diabetic Neuropathy Study Group of EASD sponsored a meeting to explore the current status of animal models of diabetic peripheral neuropathy. The goal of the workshop was to develop a set of consensus criteria for the phenotyping of rodent models of diabetic neuropathy...... with a discussion on the merits and limitations of a unified approach to phenotyping rodent models of diabetic neuropathy and a consensus formed on the definition of the minimum criteria required for establishing the presence of the disease. A neuropathy phenotype in rodents was defined as the presence...

Does genomic selection have a future in plant breeding?

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Jonas, Elisabeth; de Koning, Dirk-Jan

2013-09-01

Plant breeding largely depends on phenotypic selection in plots and only for some, often disease-resistance-related traits, uses genetic markers. The more recently developed concept of genomic selection, using a black box approach with no need of prior knowledge about the effect or function of individual markers, has also been proposed as a great opportunity for plant breeding. Several empirical and theoretical studies have focused on the possibility to implement this as a novel molecular method across various species. Although we do not question the potential of genomic selection in general, in this Opinion, we emphasize that genomic selection approaches from dairy cattle breeding cannot be easily applied to complex plant breeding. Copyright © 2013 Elsevier Ltd. All rights reserved.

Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

Directory of Open Access Journals (Sweden)

Guijun Yang

2017-06-01

Full Text Available Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI, chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

Selective amygdalohippocampectomy via trans-superior temporal gyrus keyhole approach.

Science.gov (United States)

Mathon, Bertrand; Clemenceau, Stéphane

2016-04-01

Hippocampal sclerosis is the most common cause of drug-resistant epilepsy amenable for surgical treatment and seizure control. The rationale of the selective amygdalohippocampectomy is to spare cerebral tissue not included in the seizure generator. Describe the selective amygdalohippocampectomy through the trans-superior temporal gyrus keyhole approach. Selective amygdalohippocampectomy for temporal lobe epilepsy is performed when the data (semiology, neuroimaging, electroencephalography) point to the mesial temporal structures. The trans-superior temporal gyrus keyhole approach is a minimally invasive and safe technique that allows disconnection of the temporal stem and resection of temporomesial structures.

Genome-wide association analyses of expression phenotypes.

Science.gov (United States)

Chen, Gary K; Zheng, Tian; Witte, John S; Goode, Ellen L; Gao, Lei; Hu, Pingzhao; Suh, Young Ju; Suktitipat, Bhoom; Szymczak, Silke; Woo, Jung Hoon; Zhang, Wei

2007-01-01

A number of issues arise when analyzing the large amount of data from high-throughput genotype and expression microarray experiments, including design and interpretation of genome-wide association studies of expression phenotypes. These issues were considered by contributions submitted to Group 1 of the Genetic Analysis Workshop 15 (GAW15), which focused on the association of quantitative expression data. These contributions evaluated diverse hypotheses, including those relevant to cancer and obesity research, and used various analytic techniques, many of which were derived from information theory. Several observations from these reports stand out. First, one needs to consider the genetic model of the trait of interest and carefully select which single nucleotide polymorphisms and individuals are included early in the design stage of a study. Second, by targeting specific pathways when analyzing genome-wide data, one can generate more interpretable results than agnostic approaches. Finally, for datasets with small sample sizes but a large number of features like the Genetic Analysis Workshop 15 dataset, machine learning approaches may be more practical than traditional parametric approaches. (c) 2007 Wiley-Liss, Inc.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

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

Science.gov (United States)

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

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

Comparative Analyses of Phenotypic Trait Covariation within and among Populations.

Science.gov (United States)

Peiman, Kathryn S; Robinson, Beren W

2017-10-01

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

PhenoLink - a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains

Directory of Open Access Journals (Sweden)

Bayjanov Jumamurat R

2012-05-01

Full Text Available Abstract Background Linking phenotypes to high-throughput molecular biology information generated by ~omics technologies allows revealing cellular mechanisms underlying an organism's phenotype. ~Omics datasets are often very large and noisy with many features (e.g., genes, metabolite abundances. Thus, associating phenotypes to ~omics data requires an approach that is robust to noise and can handle large and diverse data sets. Results We developed a web-tool PhenoLink (http://bamics2.cmbi.ru.nl/websoftware/phenolink/ that links phenotype to ~omics data sets using well-established as well new techniques. PhenoLink imputes missing values and preprocesses input data (i to decrease inherent noise in the data and (ii to counterbalance pitfalls of the Random Forest algorithm, on which feature (e.g., gene selection is based. Preprocessed data is used in feature (e.g., gene selection to identify relations to phenotypes. We applied PhenoLink to identify gene-phenotype relations based on the presence/absence of 2847 genes in 42 Lactobacillus plantarum strains and phenotypic measurements of these strains in several experimental conditions, including growth on sugars and nitrogen-dioxide production. Genes were ranked based on their importance (predictive value to correctly predict the phenotype of a given strain. In addition to known gene to phenotype relations we also found novel relations. Conclusions PhenoLink is an easily accessible web-tool to facilitate identifying relations from large and often noisy phenotype and ~omics datasets. Visualization of links to phenotypes offered in PhenoLink allows prioritizing links, finding relations between features, finding relations between phenotypes, and identifying outliers in phenotype data. PhenoLink can be used to uncover phenotype links to a multitude of ~omics data, e.g., gene presence/absence (determined by e.g.: CGH or next-generation sequencing, gene expression (determined by e.g.: microarrays or RNA

METHOD FOR SELECTION OF PROJECT MANAGEMENT APPROACH BASED ON FUZZY CONCEPTS

Directory of Open Access Journals (Sweden)

Igor V. KONONENKO

2017-03-01

Full Text Available Literature analysis of works that devoted to research of the selection a project management approach and development of effective methods for this problem solution is given. Mathematical model and method for selection of project management approach with fuzzy concepts of applicability of existing approaches are proposed. The selection is made of such approaches as the PMBOK Guide, the ISO21500 standard, the PRINCE2 methodology, the SWEBOK Guide, agile methodologies Scrum, XP, and Kanban. The number of project parameters which have a great impact on the result of the selection and measure of their impact is determined. Project parameters relate to information about the project, team, communication, critical project risks. They include the number of people involved in the project, the customer's experience with this project team, the project team's experience in this field, the project team's understanding of requirements, adapting ability, initiative, and others. The suggested method is considered on the example of its application for selection a project management approach to software development project.

How does male–male competition generate negative frequency-dependent selection and disruptive selection during speciation?

Science.gov (United States)

Border, Shana E

2018-01-01

Abstract Natural selection has been shown to drive population differentiation and speciation. The role of sexual selection in this process is controversial; however, most of the work has centered on mate choice while the role of male–male competition in speciation is relatively understudied. Here, we outline how male–male competition can be a source of diversifying selection on male competitive phenotypes, and how this can contribute to the evolution of reproductive isolation. We highlight how negative frequency-dependent selection (advantage of rare phenotype arising from stronger male–male competition between similar male phenotypes compared with dissimilar male phenotypes) and disruptive selection (advantage of extreme phenotypes) drives the evolution of diversity in competitive traits such as weapon size, nuptial coloration, or aggressiveness. We underscore that male–male competition interacts with other life-history functions and that variable male competitive phenotypes may represent alternative adaptive options. In addition to competition for mates, aggressive interference competition for ecological resources can exert selection on competitor signals. We call for a better integration of male–male competition with ecological interference competition since both can influence the process of speciation via comparable but distinct mechanisms. Altogether, we present a more comprehensive framework for studying the role of male–male competition in speciation, and emphasize the need for better integration of insights gained from other fields studying the evolutionary, behavioral, and physiological consequences of agonistic interactions. PMID:29492042

An Approximate Approach to Automatic Kernel Selection.

Science.gov (United States)

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Tests of selection in pooled case-control data: an empirical study.

Science.gov (United States)

Udpa, Nitin; Zhou, Dan; Haddad, Gabriel G; Bafna, Vineet

2011-01-01

For smaller organisms with faster breeding cycles, artificial selection can be used to create sub-populations with different phenotypic traits. Genetic tests can be employed to identify the causal markers for the phenotypes, as a precursor to engineering strains with a combination of traits. Traditional approaches involve analyzing crosses of inbred strains to test for co-segregation with genetic markers. Here we take advantage of cheaper next generation sequencing techniques to identify genetic signatures of adaptation to the selection constraints. Obtaining individual sequencing data is often unrealistic due to cost and sample issues, so we focus on pooled genomic data. We explore a series of statistical tests for selection using pooled case (under selection) and control populations. The tests generally capture skews in the scaled frequency spectrum of alleles in a region, which are indicative of a selective sweep. Extensive simulations are used to show that these approaches work well for a wide range of population divergence times and strong selective pressures. Control vs control simulations are used to determine an empirical False Positive Rate, and regions under selection are determined using a 1% FPR level. We show that pooling does not have a significant impact on statistical power. The tests are also robust to reasonable variations in several different parameters, including window size, base-calling error rate, and sequencing coverage. We then demonstrate the viability (and the challenges) of one of these methods in two independent Drosophila populations (Drosophila melanogaster) bred under selection for hypoxia and accelerated development, respectively. Testing for extreme hypoxia tolerance showed clear signals of selection, pointing to loci that are important for hypoxia adaptation. Overall, we outline a strategy for finding regions under selection using pooled sequences, then devise optimal tests for that strategy. The approaches show promise for

Personalized therapy algorithms for type 2 diabetes: a phenotype-based approach

Directory of Open Access Journals (Sweden)

Ceriello A

2014-06-01

treatment is related to the identified phenotype. With one exception, these algorithms contain a stepwise approach for patients with type 2 diabetes who are metformin-intolerant. The glycemic targets (HbA1c, fasting/preprandial and postprandial glycemia are also personalized. This accessible and easy to use algorithm may help physicians to choose a personalized treatment plan for each patient and to optimize it in a timely manner, thereby lessening clinical inertia.Keywords: type 2 diabetes, treatment guidelines, personalized treatment, Italian Association of Medical Diabetologists, Italian algorithm

Examination of taxonomic uncertainties surrounding Brucella abortus bv. 7 by phenotypic and molecular approaches.

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Garin-Bastuji, Bruno; Mick, Virginie; Le Carrou, Gilles; Allix, Sebastien; Perrett, Lorraine L; Dawson, Claire E; Groussaud, Pauline; Stubberfield, Emma J; Koylass, Mark; Whatmore, Adrian M

2014-03-01

Brucella taxonomy is perpetually being reshuffled, at both the species and intraspecies levels. Biovar 7 of Brucella abortus was suspended from the Approved Lists of Bacterial Names Brucella classification in 1988, because of unpublished evidence that the reference strain 63/75 was a mixture of B. abortus biovars 3 and 5. To formally clarify the situation, all isolates previously identified as B. abortus bv. 7 in the AHVLA and ANSES strain collections were characterized by classical microbiological and multiple molecular approaches. Among the 14 investigated strains, including strain 63/75, only four strains, isolated in Kenya, Turkey, and Mongolia, were pure and showed a phenotypic profile in agreement with the former biovar 7, particularly agglutination with both anti-A/anti-M monospecific sera. These results were strengthened by molecular strategies. Indeed, genus- and species-specific methods allowed confirmation that the four pure strains belonged to the B. abortus species. The combination of most approaches excluded their affiliation with the recognized biovars (biovars 1 to 6 and 9), while some suggested that they were close to biovar 3.These assays were complemented by phylogenetic and/or epidemiological methods, such as multilocus sequence analysis (MLSA) and variable-number tandem repeat (VNTR) analysis. The results of this polyphasic investigation allow us to propose the reintroduction of biovar 7 into the Brucella classification, with at least three representative strains. Interestingly, the Kenyan strain, sharing the same biovar 7 phenotype, was genetically divergent from other three isolates. These discrepancies illustrate the complexity of Brucella taxonomy. This study suggests that worldwide collections could include strains misidentified as B. abortus bv. 7, and it highlights the need to verify their real taxonomic position.

CADDIS Volume 4. Data Analysis: Selecting an Analysis Approach

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An approach for selecting statistical analyses to inform causal analysis. Describes methods for determining whether test site conditions differ from reference expectations. Describes an approach for estimating stressor-response relationships.

Tests of Selection in Pooled Case-Control Data: An Empirical Study

Directory of Open Access Journals (Sweden)

Nitin eUdpa

2011-11-01

Full Text Available For smaller organisms with faster breeding cycles, artificial selection can be used to create sub-populations with different phenotypic traits. Genetic tests can be employed to identify the causal markers for the phenotypes, as a precursor to engineering strains with a combination of traits. Traditional approaches involve analyzing crosses of inbred strains to test for co-segregation with genetic markers. Here we take advantage of cheaper next generation sequencing techniques to identifygenetic signatures of adaptation to the selection constraints. Obtaining individual sequencing data is often unrealistic due to cost and sample issues, so we focus on pooled genomic data.In this paper, we explore a series of statistical tests for selection using pooled case (under selection and control populations. Extensive simulations are used to show that these approaches work well for a wide range of population divergence times and strong selective pressures. We show that pooling does not have a significant impact on statistical power. The tests are also robust to reasonable variations in several different parameters, including window size, base-calling error rate, and sequencing coverage. We then demonstrate the viability (and the challenges of one of these methods in two independent Drosophila populations (Drosophila melanogaster bred under selectionfor hypoxia and accelerated development, respectively. Testing for extreme hypoxia tolerance showed clear signals of selection, pointing to loci that are important for hypoxia adaptation.Overall, we outline a strategy for finding regions under selection using pooled sequences, then devise optimal tests for that strategy. The approaches show promise for detecting selection, even several generations after fixation of the beneficial allele has occurred.

Federated Tensor Factorization for Computational Phenotyping

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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

Phenotypic selection on leaf water use efficiency and related ecophysiological traits for natural populations of desert sunflowers.

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Donovan, Lisa A; Dudley, Susan A; Rosenthal, David M; Ludwig, Fulco

2007-05-01

Plant water-use efficiency (WUE) is expected to affect plant fitness and thus be under natural selection in arid habitats. Although many natural population studies have assessed plant WUE, only a few related WUE to fitness. The further determination of whether selection on WUE is direct or indirect through functionally related traits has yielded no consistent results. For natural populations of two desert annual sunflowers, Helianthus anomalus and H. deserticola, we used phenotypic selection analysis with vegetative biomass as the proxy for fitness to test (1) whether there was direct and indirect selection on WUE (carbon isotope ratio) and related traits (leaf N, area, succulence) and (2) whether direct selection was consistent with hypothesized drought/dehydration escape and avoidance strategies. There was direct selection for lower WUE in mesic and dry H. anomalus populations, consistent with dehydration escape, even though it is the longer lived of the two species. For mesic H. anomalus, direct selection favored lower WUE and higher N, suggesting that plants may be "wasting water" to increase N delivery via the transpiration stream. For the shorter lived H. deserticola in the direr habitat, there was indirect selection for lower WUE, inconsistent with drought escape. There was also direct selection for higher leaf N, succulence and leaf size. There was no direct selection for higher WUE consistent with dehydration avoidance in either species. Thus, in these natural populations of two desert dune species higher fitness was associated with some combination direct and indirect selection for lower WUE, higher leaf N and larger leaf size. Our understanding of the adaptive value of plant ecophysiological traits will benefit from further consideration of related traits such as leaf nitrogen and more tests in natural populations.

Supplier selection problem: A fuzzy multicriteria approach | Allouche ...

African Journals Online (AJOL)

The purpose of this paper is to suggest a fuzzy multi-criteria approach to solve the supplier selection problem, an approach based on the fuzzy analytic hierarchy process and imprecise goal programming. To deal with decision-maker (DM) preferences, the concept of satisfaction function is introduced. The proposed ...

Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.

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Hayden, Kathleen M; Kuchibhatla, Maragatha; Romero, Heather R; Plassman, Brenda L; Burke, James R; Browndyke, Jeffrey N; Welsh-Bohmer, Kathleen A

2014-11-01

Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline. To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis. The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership. Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment. Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Stock selection using a hybrid MCDM approach

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Tea Poklepović

2014-12-01

Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

Glycolytic activity in breast cancer using 18F-FDG PET/CT as prognostic predictor: A molecular phenotype approach.

Science.gov (United States)

Garcia Vicente, A M; Soriano Castrejón, A; Amo-Salas, M; Lopez Fidalgo, J F; Muñoz Sanchez, M M; Alvarez Cabellos, R; Espinosa Aunion, R; Muñoz Madero, V

2016-01-01

To explore the relationship between basal (18)F-FDG uptake in breast tumors and survival in patients with breast cancer (BC) using a molecular phenotype approach. This prospective and multicentre study included 193 women diagnosed with BC. All patients underwent an (18)F-FDG PET/CT prior to treatment. Maximum standardized uptake value (SUVmax) in tumor (T), lymph nodes (N), and the N/T index was obtained in all the cases. Metabolic stage was established. As regards biological prognostic parameters, tumors were classified into molecular sub-types and risk categories. Overall survival (OS) and disease free survival (DFS) were obtained. An analysis was performed on the relationship between semi-quantitative metabolic parameters with molecular phenotypes and risk categories. The effect of molecular sub-type and risk categories in prognosis was analyzed using Kaplan-Meier and univariate and multivariate tests. Statistical differences were found in both SUVT and SUVN, according to the molecular sub-types and risk classifications, with higher semi-quantitative values in more biologically aggressive tumors. No statistical differences were observed with respect to the N/T index. Kaplan-Meier analysis revealed that risk categories were significantly related to DFS and OS. In the multivariate analysis, metabolic stage and risk phenotype showed a significant association with DFS. High-risk phenotype category showed a worst prognosis with respect to the other categories with higher SUVmax in primary tumor and lymph nodes. Copyright © 2015 Elsevier España, S.L.U. and SEMNIM. All rights reserved.

Integrating phenotype ontologies with PhenomeNET

KAUST Repository

Rodriguez-Garcia, Miguel Angel

2017-12-19

Background Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.

Localization of canine brachycephaly using an across breed mapping approach.

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Danika Bannasch

2010-03-01

Full Text Available The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30 and control (20-60 samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

Improving the phenotypic expression of rice genotypes: Rethinking “intensification” for production systems and selection practices for rice breeding

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Norman Uphoff

2015-06-01

Full Text Available Intensification in rice crop production is generally understood as requiring increased use of material inputs: water, inorganic fertilizers, and agrochemicals. However, this is not the only kind of intensification available. More productive crop phenotypes, with traits such as more resistance to biotic and abiotic stresses and shorter crop cycles, are possible through modifications in the management of rice plants, soil, water, and nutrients, reducing rather than increasing material inputs. Greater factor productivity can be achieved through the application of new knowledge and more skill, and (initially more labor, as seen from the System of Rice Intensification (SRI, whose practices are used in various combinations by as many as 10 million farmers on about 4 million hectares in over 50 countries. The highest yields achieved with these management methods have come from hybrids and improved rice varieties, confirming the importance of making genetic improvements. However, unimproved varieties are also responsive to these changes, which induce better growth and functioning of rice root systems and more abundance, diversity, and activity of beneficial soil organisms. Some of these organisms as symbiotic endophytes can affect and enhance the expression of rice plants' genetic potential as well as their phenotypic resilience to multiple stresses, including those of climate change. SRI experience and data suggest that decades of plant breeding have been selecting for the best crop genetic endowments under suboptimal growing conditions, with crowding of plants that impedes their photosynthesis and growth, flooding of rice paddies that causes roots to degenerate and forgoes benefits derived from aerobic soil organisms, and overuse of agrochemicals that adversely affect these organisms as well as soil and human health. This review paper reports evidence from research in India and Indonesia that changes in crop and water management can improve the

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

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

2011-01-01

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

A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

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Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

2016-09-01

In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

Phenotype and genetic parameters for body measurements, reproductive traits and gut lenght of Nile tilapia (Oreochromis niloticus) selected for growth in low-input earthen ponds

NARCIS (Netherlands)

Charo-Karisa, H.; Bovenhuis, H.; Rezk, M.A.; Ponzoni, R.W.; Arendonk, van J.A.M.; Komen, J.

2007-01-01

In this study we present estimates of phenotypic and genetic parameters for body size measurements, reproductive traits, and gut length for Nile tilapia (Oreochromis niloticus) selected for growth in fertilized earthen ponds for two generations. Throughout the experiment, ponds were fertilized daily

Lethal mutagenesis: targeting the mutator phenotype in cancer.

Science.gov (United States)

Fox, Edward J; Loeb, Lawrence A

2010-10-01

The evolution of cancer and RNA viruses share many similarities. Both exploit high levels of genotypic diversity to enable extensive phenotypic plasticity and thereby facilitate rapid adaptation. In order to accumulate large numbers of mutations, we have proposed that cancers express a mutator phenotype. Similar to cancer cells, many viral populations, by replicating their genomes with low fidelity, carry a substantial mutational load. As high levels of mutation are potentially deleterious, the viral mutation frequency is thresholded at a level below which viral populations equilibrate in a traditional mutation-selection balance, and above which the population is no longer viable, i.e., the population undergoes an error catastrophe. Because their mutation frequencies are fine-tuned just below this error threshold, viral populations are susceptible to further increases in mutational load and, recently this phenomenon has been exploited therapeutically by a concept that has been termed lethal mutagenesis. Here we review the application of lethal mutagenesis to the treatment of HIV and discuss how lethal mutagenesis may represent a novel therapeutic approach for the treatment of solid cancers. Copyright © 2010 Elsevier Ltd. All rights reserved.

Phenotypic flexibility of traits related to energy acquisition in mice divergently selected for basal metabolic rate (BMR).

Science.gov (United States)

Ksiazek, Aneta; Czerniecki, Jan; Konarzewski, Marek

2009-03-01

Theoretical considerations suggest that one of the main factors determining phenotypic flexibility of the digestive system is the size (mass) of internal organs. To test this, we used mice from two lines selected for high and low levels of basal metabolic rate (BMR). Mice with higher BMRs also have larger internal organs and higher daily food consumption (C) under non-stressful conditions. We exposed animals from both lines to a sudden cold exposure by transferring them (without prior acclimation) from an ambient temperature of 23 degrees C to 5 degrees C. Cold exposure elicited a twofold increase in C and a 25% reduction of apparent digestive efficiency. For the same body mass-corrected C, small intestine, kidneys, heart and liver of cold-exposed low-BMR mice were smaller than those of the high-BMR line. Therefore, the internal organs of low-BMR animals were burdened with substantially higher metabolic loads (defined as C or digestible food intake per total mass of a particular organ). The mass-specific activity of citrate synthase (CS) in the liver and kidneys (but not heart) was also lower in the low-BMR mice. The magnitude of phenotypic flexibility of internal organ size and CS activity was strictly proportional to the organ mass (in the case of kidneys and liver, also mass-specific CS activity) prior to an increased energy demand. Thus, phenotypic flexibility had additive rather than multiplicative dynamics. Our results also suggest that variation in BMR positively correlates with the magnitude of an immediate spare capacity that fuels the initial response of internal organs to a sudden metabolic stress.

Phenotypic covariance at species' borders.

Science.gov (United States)

Caley, M Julian; Cripps, Edward; Game, Edward T

2013-05-28

Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.

Integration of curated databases to identify genotype-phenotype associations

Directory of Open Access Journals (Sweden)

Li Jianrong

2006-10-01

Full Text Available Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs. Results Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. Conclusion Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

FTO genotype is associated with phenotypic variability of body mass index

NARCIS (Netherlands)

Yang, J.; Loos, R.J.; Powell, J.E.; Medland, S.E.; Speliotes, E.K.; Chasman, D.I.; Rose, L.M.; Thorleifsson, G.; Steinthorsdottir, V.; Mägi, R.; Waite, L.; Smith, A.V.; Yerges-Armstrong, L.M.; Monda, K.L.; Hadley, D.; Mahajan, A.; Li, G.; Kapur, K.; Vitart, V.; Huffman, J.E.; Wang, S.R.; Palmer, C.; Esko, T.; Fischer, K.; Zhao, J.H.; Demirkan, A.; Isaacs, A.; Feitosa, M.F.; Luan, J.; Heard-Costa, N.L.; White, C.; Jackson, A.U.; Preuss, M; Ziegler, A.; Eriksson, J.; Kutalik, Z.; Frau, F.; Nolte, I.M.; van Vliet-Ostaptchouk, J.V.; Hottenga, J.J.; Jacobs, K.B.; Verweij, N.; Goel, A.; Medina-Gomez, C.; Estrada, K.; Bragg-Gresham, J.L.; Sanna, S.; Sidore, C.; Tyrer, J.; Teumer, A.; Prokopenko, I.; Mangino, M.; Lindgren, C.M.; Assimes, T.L.; Shuldiner, A.R.; Hui, J.; Beilby, J.P.; McArdle, W.L.; Hall, P.; Haritunians, T.; Zgaga, L.; Kolcic, I.; Polasek, O.; Zemunik, T.; Oostra, B.A.; Junttila, M.J.; Grönberg, H.; Schreiber, S; Peters, A.; Hicks, A.A.; Stephens, J.; Foad, N.S.; Laitinen, J.; Pouta, A.; Kaakinen, M.; Willemsen, G.; Vink, J.M.; Wild, S.H.; Navis, G.; Asselbergs, F.W.; Homuth, G.; John, U.; Iribarren, C.; Harris, T.; Launer, L.J.; Gudnason, V.; O'Connell, J.R.; Boerwinkle, E.; Cadby, G.; Palmer, L.J.; James, A.L.; Musk, A.W.; Ingelsson, E.; Psaty, B.M.; Beckmann, J.S.; Waeber, G.; Vollenweider, P.; Hayward, C.; Wright, A.F.; Rudan, I.; Groop, L.C.; Metspalu, A.; Thee Khaw, K.; van Duijn, C.M.; Borecki, I.B.; Province, M.A.; Wareham, N.J.; Tardif, J.C.; Huikuri, H.V.; Cupples, L.A.; Atwood, L.D.; Fox, C.S.; Boehnke, M.; Collins, F.S.; Mohlke, K.L.; Erdmann, J.; Schunkert, H.; Hengstenberg, C.; Stark, K.; Lorentzon, M.; Ohlsson, C.; Cusi, D.; Staessen, J.A.; van der Klauw, M.M.; Pramstaller, P.P.; Kathiresan, S.; Jolley, D.J.; Ripatti, S.; Jarvelin, M.-R.; de Geus, E.J.C.; Boomsma, D.I.; Penninx, B.W.J.H.; Wilson, J.F.; Campbell, H.; Chanock, S.J.; van der Harst, P.; Hamsten, A.; Watkins, H.; Hofman, A.; Witteman, J.C.; Zillikens, M.C.; Uitterlinden, A.G.; Rivadeneira, F.; Kiemeney, L.A.; Vermeulen, S.H.; Abecasis, G.R.; Schlessinger, D.; Schipf, S.; Stumvoll, M.; Tönjes, A.; Spector, T.D.; North, K.E.; Lettre, G.; McCarthy, M.I.; Berndt, S.I.; Heath, A.C.; Madden, P.A.F.; Nyholt, DR; Montgomery, G.W.; Martin, N.G.; McKnight, B.; Strachan, D.P.; Hill, W.G.; Snieder, H.; Ridker, P.M.; Thorsteinsdottir, U.; Stefansson, K.; Frayling, T.M.; Hirschhorn, J.N.; Goddard, M.E.; Visscher, P.M.

2012-01-01

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human

A “genetics first” approach to selection

Science.gov (United States)

A different approach for using genomic information in genetic improvement is proposed. Past research in population genetics and animal breeding combined with information on sequence variants suggest the possibility that selection might be able to capture a portion of inbreeding and heterosis effect...

NF1 Neuronal Genotype Phenotype Relationships

Science.gov (United States)

2017-06-01

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

Cell-type Dependent Alzheimer's Disease Phenotypes: Probing the Biology of Selective Neuronal Vulnerability

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Christina R. Muratore

2017-12-01

Full Text Available Summary: Alzheimer's disease (AD induces memory and cognitive impairment in the absence of motor and sensory deficits during its early and middle course. A major unresolved question is the basis for this selective neuronal vulnerability. Aβ, which plays a central role in AD pathogenesis, is generated throughout the brain, yet some regions outside of the limbic and cerebral cortices are relatively spared from Aβ plaque deposition and synapse loss. Here, we examine neurons derived from iPSCs of patients harboring an amyloid precursor protein mutation to quantify AD-relevant phenotypes following directed differentiation to rostral fates of the brain (vulnerable and caudal fates (relatively spared in AD. We find that both the generation of Aβ and the responsiveness of TAU to Aβ are affected by neuronal cell type, with rostral neurons being more sensitive than caudal neurons. Thus, cell-autonomous factors may in part dictate the pattern of selective regional vulnerability in human neurons in AD. : In this article, Muratore et al. examine differential vulnerability of neuronal subtypes in AD by directing iPSC lines from control and familial AD subjects to different regional neuronal fates. APP processing and TAU proteostasis are differentially affected between regional fates, such that neuronal cell type dictates generation of and responsiveness to Aβ. Keywords: Alzheimer's disease, disease modeling, iPSCs, neural stem cells, Abeta, Tau, selective vulnerability, amyloid, familial AD, differential susceptibility

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

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Jonathan D Mosley

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

Selective amygdalohippocampectomy via trans-superior temporal gyrus keyhole approach

OpenAIRE

Mathon , Bertrand; Clemenceau , Stéphane

2016-01-01

International audience; BackgroundHippocampal sclerosis is the most common cause of drug-resistant epilepsy amenable for surgical treatment and seizure control. The rationale of the selective amygdalohippocampectomy is to spare cerebral tissue not included in the seizure generator.MethodDescribe the selective amygdalohippocampectomy through the trans-superior temporal gyrus keyhole approach.ConclusionSelective amygdalohippocampectomy for temporal lobe epilepsy is performed when the data (semi...

Accuracy of genomic selection in biparental populations of flax (Linum usitatissimum L.

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Frank M. You

2016-08-01

Full Text Available Flax is an important economic crop for seed oil and stem fiber. Phenotyping of traits such as seed yield, seed quality, stem fiber yield, and quality characteristics is expensive and time consuming. Genomic selection (GS refers to a breeding approach aimed at selecting preferred individuals based on genomic estimated breeding values predicted by a statistical model based on the relationship between phenotypes and genome-wide genetic markers. We evaluated the prediction accuracy of GS (rMP and the efficiency of GS relative to phenotypic selection (RE for three GS models: ridge regression best linear unbiased prediction (RR-BLUP, Bayesian LASSO (BL, and Bayesian ridge regression (BRR, for seed yield, oil content, iodine value, linoleic, and linolenic acid content with a full and a common set of genome-wide simple sequence repeat markers in each of three biparental populations. The three GS models generated similar rMP and RE, while BRR displayed a higher coefficient of determination (R2 of the fitted models than did RR-BLUP or BL. The mean rMP and RE varied for traits with different heritabilities and was affected by the genetic variation of the traits in the populations. GS for seed yield generated a mean RE of 1.52 across populations and marker sets, a value significantly superior to that for direct phenotypic selection. Our empirical results provide the first validation of GS in flax and demonstrate that GS could increase genetic gain per unit time for linseed breeding. Further studies for selection of training populations and markers are warranted.

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection

OpenAIRE

Daetwyler, Hans D.; Hayden, Matthew J.; Spangenberg, German C.; Hayes, Ben J.

2015-01-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selec...

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

Science.gov (United States)

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

2008-01-01

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

How phenotypic plasticity made its way into molecular biology

Indian Academy of Sciences (India)

2009-08-03

Aug 3, 2009 ... Phenotypic plasticity has been fashionable in recent years. It has never been absent from the studies of evolutionary biologists, although the availability of stable animal models has limited its role. Although opposed by the reductionist and deterministic approach of molecular biology, phenotypic plasticity ...

The role of environment and core-margin effects on range-wide phenotypic variation in a montane grasshopper.

Science.gov (United States)

Noguerales, V; García-Navas, V; Cordero, P J; Ortego, J

2016-11-01

The integration of genetic information with ecological and phenotypic data constitutes an effective approach to gain insight into the mechanisms determining interpopulation variability and the evolutionary processes underlying local adaptation and incipient speciation. Here, we use the Pyrenean Morales grasshopper (Chorthippus saulcyi moralesi) as study system to (i) analyse the relative role of genetic drift and selection in range-wide patterns of phenotypic differentiation and (ii) identify the potential selective agents (environment, elevation) responsible for variation. We also test the hypothesis that (iii) the development of dispersal-related traits is associated with different parameters related to population persistence/turnover, including habitat suitability stability over the last 120 000 years, distance to the species distribution core and population genetic variability. Our results indicate that selection shaped phenotypic differentiation across all the studied morphological traits (body size, forewing length and shape). Subsequent analyses revealed that among-population differentiation in forewing length was significantly explained by a temperature gradient, suggesting an adaptive response to thermoregulation or flight performance under contrasting temperature regimes. We found support for our hypothesis predicting a positive association between the distance to the species distribution core and the development of dispersal-related morphology, which suggests an increased dispersal capability in populations located at range edges that, in turn, exhibit lower levels of genetic variability. Overall, our results indicate that range-wide patterns of phenotypic variation are partially explained by adaptation in response to local environmental conditions and differences in habitat persistence between core and peripheral populations. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary

Revealing plant cryptotypes: defining meaningful phenotypes among infinite traits.

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Chitwood, Daniel H; Topp, Christopher N

2015-04-01

The plant phenotype is infinite. Plants vary morphologically and molecularly over developmental time, in response to the environment, and genetically. Exhaustive phenotyping remains not only out of reach, but is also the limiting factor to interpreting the wealth of genetic information currently available. Although phenotyping methods are always improving, an impasse remains: even if we could measure the entirety of phenotype, how would we interpret it? We propose the concept of cryptotype to describe latent, multivariate phenotypes that maximize the separation of a priori classes. Whether the infinite points comprising a leaf outline or shape descriptors defining root architecture, statistical methods to discern the quantitative essence of an organism will be required as we approach measuring the totality of phenotype. Copyright © 2015 Elsevier Ltd. All rights reserved.

Colorectal cancer chemoprevention: the potential of a selective approach.

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Ben-Amotz, Oded; Arber, Nadir; Kraus, Sarah

2010-10-01

Colorectal cancer (CRC) is a leading cause of cancer death, and therefore demands special attention. Novel recent approaches for the chemoprevention of CRC focus on selective targeting of key pathways. We review the study by Zhang and colleagues, evaluating a selective approach targeting APC-deficient premalignant cells using retinoid-based therapy and TNF-related apoptosis-inducing ligand (TRAIL). This study demonstrates that induction of TRAIL-mediated death signaling contributes to the chemopreventive value of all-trans-retinyl acetate (RAc) by sensitizing premalignant adenoma cells for apoptosis without affecting normal cells. We discuss these important findings, raise few points that deserve consideration, and may further contribute to the development of RAc-based combination therapies with improved efficacy. The authors clearly demonstrate a synergistic interaction between TRAIL, RAc and APC, which leads to the specific cell death of premalignant target cells. The study adds to the growing body of literature related to CRC chemoprevention, and provides solid data supporting a potentially selective approach for preventing CRC using RAc and TRAIL.

Phenotypic Resistance to Antibiotics

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Jose L. Martinez

2013-04-01

Full Text Available The development of antibiotic resistance is usually associated with genetic changes, either to the acquisition of resistance genes, or to mutations in elements relevant for the activity of the antibiotic. However, in some situations resistance can be achieved without any genetic alteration; this is called phenotypic resistance. Non-inherited resistance is associated to specific processes such as growth in biofilms, a stationary growth phase or persistence. These situations might occur during infection but they are not usually considered in classical susceptibility tests at the clinical microbiology laboratories. Recent work has also shown that the susceptibility to antibiotics is highly dependent on the bacterial metabolism and that global metabolic regulators can modulate this phenotype. This modulation includes situations in which bacteria can be more resistant or more susceptible to antibiotics. Understanding these processes will thus help in establishing novel therapeutic approaches based on the actual susceptibility shown by bacteria during infection, which might differ from that determined in the laboratory. In this review, we discuss different examples of phenotypic resistance and the mechanisms that regulate the crosstalk between bacterial metabolism and the susceptibility to antibiotics. Finally, information on strategies currently under development for diminishing the phenotypic resistance to antibiotics of bacterial pathogens is presented.

Multi-Layer Approach for the Detection of Selective Forwarding Attacks.

Science.gov (United States)

Alajmi, Naser; Elleithy, Khaled

2015-11-19

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

Multi-Layer Approach for the Detection of Selective Forwarding Attacks

Directory of Open Access Journals (Sweden)

Naser Alajmi

2015-11-01

Full Text Available Security breaches are a major threat in wireless sensor networks (WSNs. WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD. The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

Selection for production-related traits in Pelargonium zonale: improved design and analysis make all the difference.

Science.gov (United States)

Molenaar, Heike; Glawe, Martin; Boehm, Robert; Piepho, Hans-Peter

2017-01-01

Ornamental plant variety improvement is limited by current phenotyping approaches and neglected use of experimental designs. The present study was conducted to show the benefits of using an experimental design and corresponding analysis in ornamental breeding regarding simulated response to selection in Pelargonium zonale for production-related traits. This required establishment of phenotyping protocols for root formation and stem cutting counts, with which 974 genotypes were assessed in a two-phase experimental design. The present paper evaluates this protocol. The possibility of varietal improvement through indirect selection on secondary traits such as branch count and flower count was assessed by genetic correlations. Simulated response to selection varied greatly, depending on the genotypic variances of the breeding population and traits. A varietal improvement of over 20% is possible for stem cutting count, root formation, branch count and flower count. In contrast, indirect selection of stem cutting count by branch count or flower count was found to be ineffective. The established phenotypic protocols and two-phase experimental designs are valuable tools for breeding of P. zonale .

Genome-wide selection signatures in Pinzgau cattle

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Radovan Kasarda

2015-08-01

Full Text Available The aim of this study was to identify the evidence of recent selection based on estimation of the integrated Haplotype Score (iHS, population differentiation index (FST and characterize affected regions near QTL associated with traits under strong selection in Pinzgau cattle. In total 21 Austrian and 19 Slovak purebreed bulls genotyped with Illumina bovineHD and  bovineSNP50 BeadChip were used to identify genomic regions under selection. Only autosomal loci with call rate higher than 90%, minor allele frequency higher than 0.01 and Hardy-Weinberg equlibrium limit of 0.001 were included in the subsequent analyses of selection sweeps presence. The final dataset was consisted from 30538 SNPs with 81.86 kb average adjacent SNPs spacing. The iHS score were averaged into non-overlapping 500 kb segments across the genome. The FST values were also plotted against genome position based on sliding windows approach and averaged over 8 consecutive SNPs. Based on integrated Haplotype Score evaluation only 7 regions with iHS score higher than 1.7 was found. The average iHS score observed for each adjacent syntenic regions indicated slight effect of recent selection in analysed group of Pinzgau bulls. The level of genetic differentiation between Austrian and Slovak bulls estimated based on FST index was low. Only 24% of FST values calculated for each SNP was greather than 0.01. By using sliding windows approach was found that 5% of analysed windows had higher value than 0.01. Our results indicated use of similar selection scheme in breeding programs of Slovak and Austrian Pinzgau bulls. The evidence for genome-wide association between signatures of selection and regions affecting complex traits such as milk production was insignificant, because the loci in segments identified as affected by selection were very distant from each other. Identification of genomic regions that may be under pressure of selection for phenotypic traits to better understanding of the

Phycoerythrin evolution and diversification of spectral phenotype in marine Synechococcus and related picocyanobacteria.

Science.gov (United States)

Everroad, R Craig; Wood, A Michelle

2012-09-01

In marine Synechococcus there is evidence for the adaptive evolution of spectrally distinct forms of the major light harvesting pigment phycoerythrin (PE). Recent research has suggested that these spectral forms of PE have a different evolutionary history than the core genome. However, a lack of explicit statistical testing of alternative hypotheses or for selection on these genes has made it difficult to evaluate the evolutionary relationships between spectral forms of PE or the role horizontal gene transfer (HGT) may have had in the adaptive phenotypic evolution of the pigment system in marine Synechococcus. In this work, PE phylogenies of picocyanobacteria with known spectral phenotypes, including newly co-isolated strains of marine Synechococcus from the Gulf of Mexico, were constructed to explore the diversification of spectral phenotype and PE evolution in this group more completely. For the first time, statistical evaluation of competing evolutionary hypotheses and tests for positive selection on the PE locus in picocyanobacteria were performed. Genes for PEs associated with specific PE spectral phenotypes formed strongly supported monophyletic clades within the PE tree with positive directional selection driving evolution towards higher phycourobilin (PUB) content. The presence of the PUB-lacking phenotype in PE-containing marine picocyanobacteria from cyanobacterial lineages identified as Cyanobium is best explained by HGT into this group from marine Synechococcus. Taken together, these data provide strong examples of adaptive evolution of a single phenotypic trait in bacteria via mutation, positive directional selection and horizontal gene transfer. Copyright © 2012 Elsevier Inc. All rights reserved.

Induction of appropriate Th-cell phenotypes: cellular decision-making in heterogeneous environments.

Science.gov (United States)

van den Ham, H-J; Andeweg, A C; de Boer, R J

2013-11-01

Helper T (Th)-cell differentiation is a key event in the development of the adaptive immune response. By the production of a range of cytokines, Th cells determine the type of immune response that is raised against an invading pathogen. Th cells can adopt many different phenotypes, and Th-cell phenotype decision-making is crucial in mounting effective host responses. This review discusses the different Th-cell phenotypes that have been identified and how Th cells adopt a particular phenotype. The regulation of Th-cell phenotypes has been studied extensively using mathematical models, which have explored the role of regulatory mechanisms such as autocrine cytokine signalling and cross-inhibition between self-activating transcription factors. At the single cell level, Th responses tend to be heterogeneous, but corrections can be made soon after T-cell activation. Although pathogens and the innate immune system provide signals that direct the induction of Th-cell phenotypes, these instructive mechanisms could be easily subverted by pathogens. We discuss that a model of success-driven feedback would select the most appropriate phenotype for clearing a pathogen. Given the heterogeneity in the induction phase of the Th response, such a success-driven feedback loop would allow the selection of effective Th-cell phenotypes while terminating incorrect responses. © 2013 John Wiley & Sons Ltd.

Innovative Approach for IBS Vendor Selection Problem

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Omar Mohd Faizal

2016-01-01

Full Text Available Supply chain management in Industrialised Building System (IBS construction management has significantly determined the successful of company and project performance. Due to the wide variety of criteria and vendor available, the vendor selection process for a specific project needs is becoming more difficult. The need of decision aid for vendor selection in other areas is widely discussed in previous research. However, study on vendor selection for IBS project is largely neglected. Decision Support System (DSS is proposed for this purpose. Yet, most of the DSS models are impractical since they are complicated and difficult for a layman such as project managers to use. Research indicates that the rapid development of ICT has highly potential towards simple and effective DSS. Thus, this paper highlights the importance and research approach for vendor selection in IBS project management. The study is based on Design Science Research Methodology with combination of case studies. It is anticipates that this study will yield an effective value-for-money decision making platform to manage vendor selection process.

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

Science.gov (United States)

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

2017-09-01

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

Emerging semantics to link phenotype and environment

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Anne E. Thessen

2015-12-01

Full Text Available Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1 use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2 two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3 two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE and the Biological Collections Ontology (BCO; these provide a starting point for the development of a data model linking phenotypes and environments.

Marker-assisted selection in forestry species

International Nuclear Information System (INIS)

Butcher, P.; Southerton, S.

2007-01-01

The primary goal of tree breeding is to increase the quantity and quality of wood products from plantations. Major gains have been achieved using recurrent selection in genetically diverse breeding populations to capture additive variation. However, the long generation times of trees, together with poor juvenile-mature trait correlations, have promoted interest in marker-assisted selection (MAS) to accelerate breeding through early selection. MAS relies on identifying DNA markers, which explain a high proportion of variation in phenotypic traits. Genetic linkage maps have been developed for most commercial tree species and these can be used to locate chromosomal regions where DNA markers co-segregate with quantitative traits (quantitative trait loci, QTL). MAS based on QTL is most likely to be used for within-family selection in a limited number of elite families that can be clonally propagated. Limitations of the approach include the low resolution of marker-trait associations, the small proportion of phenotypic variation explained by QTL and the low success rate in validating QTL in different genetic backgrounds and environments. This has led to a change in research focus towards association mapping to identify variation in the DNA sequence of genes directly controlling phenotypic variation (gene-assisted selection, GAS). The main advantages of GAS are the high resolution of marker-trait associations and the ability to transfer markers across families and even species. Association studies are being used to examine the adaptive significance of variation in genes controlling wood formation and quality, pathogen resistance, cold tolerance and drought tolerance. Single nucleotide polymorphisms (SNPs) in these gene sequences that are significantly associated with trait variation can then be used for early selection. Markers for SNPs can be transferred among individuals regardless of pedigree or family relationship, increasing opportunities for their application in

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

KAUST Repository

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

2015-01-01

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

High-Throughput Non-destructive Phenotyping of Traits that Contribute to Salinity Tolerance in Arabidopsis thaliana

KAUST Repository

Awlia, Mariam

2016-09-28

Reproducible and efficient high-throughput phenotyping approaches, combined with advances in genome sequencing, are facilitating the discovery of genes affecting plant performance. Salinity tolerance is a desirable trait that can be achieved through breeding, where most have aimed at selecting for plants that perform effective ion exclusion from the shoots. To determine overall plant performance under salt stress, it is helpful to investigate several plant traits collectively in one experimental setup. Hence, we developed a quantitative phenotyping protocol using a high-throughput phenotyping system, with RGB and chlorophyll fluorescence (ChlF) imaging, which captures the growth, morphology, color and photosynthetic performance of Arabidopsis thaliana plants in response to salt stress. We optimized our salt treatment by controlling the soil-water content prior to introducing salt stress. We investigated these traits over time in two accessions in soil at 150, 100, or 50 mM NaCl to find that the plants subjected to 100 mM NaCl showed the most prominent responses in the absence of symptoms of severe stress. In these plants, salt stress induced significant changes in rosette area and morphology, but less prominent changes in rosette coloring and photosystem II efficiency. Clustering of ChlF traits with plant growth of nine accessions maintained at 100 mM NaCl revealed that in the early stage of salt stress, salinity tolerance correlated with non-photochemical quenching processes and during the later stage, plant performance correlated with quantum yield. This integrative approach allows the simultaneous analysis of several phenotypic traits. In combination with various genetic resources, the phenotyping protocol described here is expected to increase our understanding of plant performance and stress responses, ultimately identifying genes that improve plant performance in salt stress conditions.

Phenotypic characterization of glioblastoma identified through shape descriptors

Science.gov (United States)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

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

Towards precision medicine-based therapies for glioblastoma: interrogating human disease genomics and mouse phenotypes.

Science.gov (United States)

Chen, Yang; Gao, Zhen; Wang, Bingcheng; Xu, Rong

2016-08-22

Glioblastoma (GBM) is the most common and aggressive brain tumors. It has poor prognosis even with optimal radio- and chemo-therapies. Since GBM is highly heterogeneous, drugs that target on specific molecular profiles of individual tumors may achieve maximized efficacy. Currently, the Cancer Genome Atlas (TCGA) projects have identified hundreds of GBM-associated genes. We develop a drug repositioning approach combining disease genomics and mouse phenotype data towards predicting targeted therapies for GBM. We first identified disease specific mouse phenotypes using the most recently discovered GBM genes. Then we systematically searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with GBM. We evaluated the ranks for approved and novel GBM drugs, and compared with an existing approach, which also use the mouse phenotype data but not the disease genomics data. We achieved significantly higher ranks for the approved and novel GBM drugs than the earlier approach. For all positive examples of GBM drugs, we achieved a median rank of 9.2 45.6 of the top predictions have been demonstrated effective in inhibiting the growth of human GBM cells. We developed a computational drug repositioning approach based on both genomic and phenotypic data. Our approach prioritized existing GBM drugs and outperformed a recent approach. Overall, our approach shows potential in discovering new targeted therapies for GBM.

Juglans regia L., phenotypic selection and assessment of genetic variation within a simulated seed orchard

Directory of Open Access Journals (Sweden)

Fulvio Ducci

2010-12-01

Full Text Available Normal 0 14 false false false MicrosoftInternetExplorer4 Noble hardwoods are very important for the Italian furniture industry. Since 1985, approximately 170,000 ha have been planted in Italy with noble hardwoods. Among them, about 50% of species are represented by walnuts. Walnut (Juglans regia L., not native in Italy, has been the focus of a substantial research effort for breeding and improvement programmes. The priority has been to preserve the in situ genetic resource still existing after intensive felling. Phenotypes suitable for timber production showing important traits such as straight stem, nice branch architecture, dominance and adaptation (phenology have needed to be developed and selected. In order to reach this goals, selection of valuable progenies and the evaluation of the interaction genotype x environment, methods based essentially on a multi-trait Selection Index, were developed. Studies have been undertaken also to measure the variation of phenological traits, more correlated to traits valuable for architecture; in addition, neutral markers were used to assess genetic variation among different intensities of the adopted selections. The individual genetic component was found to be higher than at the inter-population level. Results showed that a hypothetical seed orchard made with progenies selected by morphology, phenology and genetic traits could provide material with a good performance and supply a variability similar to larger populations as the total plantation or the pseudo-natural system chosen for comparison. st1\\:*{behavior:url(#ieooui } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabella normale"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso

A multi-scale convolutional neural network for phenotyping high-content cellular images.

Science.gov (United States)

Godinez, William J; Hossain, Imtiaz; Lazic, Stanley E; Davies, John W; Zhang, Xian

2017-07-01

Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters. Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. The network specifications and solver definitions are provided in Supplementary Software 1. william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. 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

Statistical Methods for Comparative Phenomics Using High-Throughput Phenotype Microarrays

KAUST Repository

Sturino, Joseph

2010-01-24

We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform.

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Science.gov (United States)

Daetwyler, Hans D; Hayden, Matthew J; Spangenberg, German C; Hayes, Ben J

2015-08-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic diversity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations. Copyright © 2015 by the Genetics Society of America.

Genome wide selection in Citrus breeding.

Science.gov (United States)

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

2016-10-17

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

Application of integrated QFD and fuzzy AHP approach in selection of suppliers

Directory of Open Access Journals (Sweden)

Bojana Jovanović

2014-10-01

Full Text Available Supplier selection is a widely considered issue in the field of management, especially in quality management. In this paper, in the selection of suppliers of electronic components we used the integrated QFD and fuzzy AHP approaches. The QFD method is used as a tool for translating stakeholder needs into evaluating criteria for suppliers. The fuzzy AHP approach is used as a tool for prioritizing stakeholders, stakeholders’ requirements, evaluating criteria and, finally, for prioritizing suppliers. The paper showcases a case study of implementation of the integrated QFD and fuzzy AHP approaches in the selection of the electronic components supplier in one Serbian company that produces electronic devices. Also presented is the algorithm of implementation of the proposed approach. To the best of our knowledge, this is the first implementation of the proposed approach in a Serbian company.

Seed predators exert selection on the subindividual variation of seed size.

Science.gov (United States)

Sobral, M; Guitián, J; Guitián, P; Larrinaga, A R

2014-07-01

Subindividual variation among repeated organs in plants constitutes an overlooked level of variation in phenotypic selection studies, despite being a major component of phenotypic variation. Animals that interact with plants could be selective agents on subindividual variation. This study examines selective pressures exerted during post-dispersal seed predation and germination on the subindividual variation of seed size in hawthorn (Crataegus monogyna). With a seed offering experiment and a germination test, we estimated phenotypic selection differentials for average and subindividual variation of seed size due to seed predation and germination. Seed size affects germination, growth rate and the probability of an individual seed of escaping predation. Longer seeds showed higher germination rates, but this did not result in significant selection on phenotypes of the maternal trees. On the other hand, seed predators avoided wider seeds, and by doing so exerted phenotypic selection on adult average and subindividual variation of seed size. The detected selection on subindividual variation suggests that the levels of phenotypic variation within individual plants may be, at least partly, the adaptive consequence of animal-mediated selection. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

The role of spatial variations of abiotic factors in mediating intratumour phenotypic heterogeneity

KAUST Repository

Lorenzi, Tommaso

2018-05-08

We present here a space- and phenotype-structured model of selection dynamics between cancer cells within a solid tumour. In the framework of this model, we combine formal analyses with numerical simulations to investigate in silico the role played by the spatial distribution of abiotic components of the tumour microenvironment in mediating phenotypic selection of cancer cells. Numerical simulations are performed both on the 3D geometry of an in silico multicellular tumour spheroid and on the 3D geometry of an in vivo human hepatic tumour, which was imaged using computerised tomography. The results obtained show that inhomogeneities in the spatial distribution of oxygen, currently observed in solid tumours, can promote the creation of distinct local niches and lead to the selection of different phenotypic variants within the same tumour. This process fosters the emergence of stable phenotypic heterogeneity and supports the presence of hypoxic cells resistant to cytotoxic therapy prior to treatment. Our theoretical results demonstrate the importance of integrating spatial data with ecological principles when evaluating the therapeutic response of solid tumours to cytotoxic therapy.

The role of spatial variations of abiotic factors in mediating intratumour phenotypic heterogeneity

KAUST Repository

Lorenzi, Tommaso; Venkataraman, Chandrasekhar; Lorz, Alexander; Chaplain, Mark A.J.

2018-01-01

We present here a space- and phenotype-structured model of selection dynamics between cancer cells within a solid tumour. In the framework of this model, we combine formal analyses with numerical simulations to investigate in silico the role played by the spatial distribution of abiotic components of the tumour microenvironment in mediating phenotypic selection of cancer cells. Numerical simulations are performed both on the 3D geometry of an in silico multicellular tumour spheroid and on the 3D geometry of an in vivo human hepatic tumour, which was imaged using computerised tomography. The results obtained show that inhomogeneities in the spatial distribution of oxygen, currently observed in solid tumours, can promote the creation of distinct local niches and lead to the selection of different phenotypic variants within the same tumour. This process fosters the emergence of stable phenotypic heterogeneity and supports the presence of hypoxic cells resistant to cytotoxic therapy prior to treatment. Our theoretical results demonstrate the importance of integrating spatial data with ecological principles when evaluating the therapeutic response of solid tumours to cytotoxic therapy.

Somatic mitochondrial DNA mutations in cancer escape purifying selection and high pathogenicity mutations lead to the oncocytic phenotype: pathogenicity analysis of reported somatic mtDNA mutations in tumors

International Nuclear Information System (INIS)

Pereira, Luísa; Soares, Pedro; Máximo, Valdemar; Samuels, David C

2012-01-01

The presence of somatic mitochondrial DNA (mtDNA) mutations in cancer cells has been interpreted in controversial ways, ranging from random neutral accumulation of mutations, to positive selection for high pathogenicity, or conversely to purifying selection against high pathogenicity variants as occurs at the population level. Here we evaluated the predicted pathogenicity of somatic mtDNA mutations described in cancer and compare these to the distribution of variations observed in the global human population and all possible protein variations that could occur in human mtDNA. We focus on oncocytic tumors, which are clearly associated with mitochondrial dysfunction. The protein variant pathogenicity was predicted using two computational methods, MutPred and SNPs&GO. The pathogenicity score of the somatic mtDNA variants were significantly higher in oncocytic tumors compared to non-oncocytic tumors. Variations in subunits of Complex I of the electron transfer chain were significantly more common in tumors with the oncocytic phenotype, while variations in Complex V subunits were significantly more common in non-oncocytic tumors. Our results show that the somatic mtDNA mutations reported over all tumors are indistinguishable from a random selection from the set of all possible amino acid variations, and have therefore escaped the effects of purifying selection that act strongly at the population level. We show that the pathogenicity of somatic mtDNA mutations is a determining factor for the oncocytic phenotype. The opposite associations of the Complex I and Complex V variants with the oncocytic and non-oncocytic tumors implies that low mitochondrial membrane potential may play an important role in determining the oncocytic phenotype

Sequence analysis of chromosome 1 revealed different selection patterns between Chinese wild mice and laboratory strains.

Science.gov (United States)

Xu, Fuyi; Hu, Shixian; Chao, Tianzhu; Wang, Maochun; Li, Kai; Zhou, Yuxun; Xu, Hongyan; Xiao, Junhua

2017-10-01

Both natural and artificial selection play a critical role in animals' adaptation to the environment. Detection of the signature of selection in genomic regions can provide insights for understanding the function of specific phenotypes. It is generally assumed that laboratory mice may experience intense artificial selection while wild mice more natural selection. However, the differences of selection signature in the mouse genome and underlying genes between wild and laboratory mice remain unclear. In this study, we used two mouse populations: chromosome 1 (Chr 1) substitution lines (C1SLs) derived from Chinese wild mice and mouse genome project (MGP) sequenced inbred strains and two selection detection statistics: Fst and Tajima's D to identify the signature of selection footprint on Chr 1. For the differentiation between the C1SLs and MGP, 110 candidate selection regions containing 47 protein coding genes were detected. A total of 149 selection regions which encompass 7.215 Mb were identified in the C1SLs by Tajima's D approach. While for the MGP, we identified nearly twice selection regions (243) compared with the C1SLs which accounted for 13.27 Mb Chr 1 sequence. Through functional annotation, we identified several biological processes with significant enrichment including seven genes in the olfactory transduction pathway. In addition, we searched the phenotypes associated with the 47 candidate selection genes identified by Fst. These genes were involved in behavior, growth or body weight, mortality or aging, and immune systems which align well with the phenotypic differences between wild and laboratory mice. Therefore, the findings would be helpful for our understanding of the phenotypic differences between wild and laboratory mice and applications for using this new mouse resource (C1SLs) for further genetics studies.

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

KAUST Repository

Hoehndorf, Robert

2015-02-19

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

Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle

Directory of Open Access Journals (Sweden)

Moore Stephen

2011-06-01

Full Text Available Abstract Background 'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS| and population differentiation index (FST--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle. Results We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian FST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases the extreme FST values were found to be positioned in poor gene content regions which deviated significantly (p ST values were found in regions of some relevant genes such as SMCP and FGF1. Conclusions Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and FST suggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life

Selection on skewed characters and the paradox of stasis.

Science.gov (United States)

Bonamour, Suzanne; Teplitsky, Céline; Charmantier, Anne; Crochet, Pierre-André; Chevin, Luis-Miguel

2017-11-01

Observed phenotypic responses to selection in the wild often differ from predictions based on measurements of selection and genetic variance. An overlooked hypothesis to explain this paradox of stasis is that a skewed phenotypic distribution affects natural selection and evolution. We show through mathematical modeling that, when a trait selected for an optimum phenotype has a skewed distribution, directional selection is detected even at evolutionary equilibrium, where it causes no change in the mean phenotype. When environmental effects are skewed, Lande and Arnold's (1983) directional gradient is in the direction opposite to the skew. In contrast, skewed breeding values can displace the mean phenotype from the optimum, causing directional selection in the direction of the skew. These effects can be partitioned out using alternative selection estimates based on average derivatives of individual relative fitness, or additive genetic covariances between relative fitness and trait (Robertson-Price identity). We assess the validity of these predictions using simulations of selection estimation under moderate sample sizes. Ecologically relevant traits may commonly have skewed distributions, as we here exemplify with avian laying date - repeatedly described as more evolutionarily stable than expected - so this skewness should be accounted for when investigating evolutionary dynamics in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Six Sigma Project Selection Using Fuzzy TOPSIS Decision Making Approach

Directory of Open Access Journals (Sweden)

Rajeev Rathi

2015-05-01

Full Text Available Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.

Performance of Genomic Selection in Mice

OpenAIRE

Legarra, Andrés; Robert-Granié, Christèle; Manfredi, Eduardo; Elsen, Jean-Michel

2008-01-01

Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as “genomic selection.” There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http://...

ERP system implementation costs and selection factors of an implementation approach

DEFF Research Database (Denmark)

Johansson, Björn; Sudzina, Frantisek; Newman, Mike

2011-01-01

, which influence the implementation approach in an ERP project, cause also an increase of the project cost in a European context? Our survey was conducted in Denmark, Slovakia and Slovenia and focused on this issue. Our main findings are that: 1) the number of implemented modules influences selection......Different approaches on implementation of enterprise resource planning (ERPs) systems exist. In this article, we investigate relationship between factors influencing selection of implementation approach and companies' ability to stay within budget when implementing ERPs. The question is: do factors...... of an implementation approach; 2) companies with information strategies are more likely to stay within budget regarding ERP systems implementation. However, we also found that: 3) implementation approach does not significantly influence ability to stay within budget; 4) a clear relationship between factors influencing...

Genomic analysis of natural selection and phenotypic variation in high-altitude mongolians.

Directory of Open Access Journals (Sweden)

Jinchuan Xing

Full Text Available Deedu (DU Mongolians, who migrated from the Mongolian steppes to the Qinghai-Tibetan Plateau approximately 500 years ago, are challenged by environmental conditions similar to native Tibetan highlanders. Identification of adaptive genetic factors in this population could provide insight into coordinated physiological responses to this environment. Here we examine genomic and phenotypic variation in this unique population and present the first complete analysis of a Mongolian whole-genome sequence. High-density SNP array data demonstrate that DU Mongolians share genetic ancestry with other Mongolian as well as Tibetan populations, specifically in genomic regions related with adaptation to high altitude. Several selection candidate genes identified in DU Mongolians are shared with other Asian groups (e.g., EDAR, neighboring Tibetan populations (including high-altitude candidates EPAS1, PKLR, and CYP2E1, as well as genes previously hypothesized to be associated with metabolic adaptation (e.g., PPARG. Hemoglobin concentration, a trait associated with high-altitude adaptation in Tibetans, is at an intermediate level in DU Mongolians compared to Tibetans and Han Chinese at comparable altitude. Whole-genome sequence from a DU Mongolian (Tianjiao1 shows that about 2% of the genomic variants, including more than 300 protein-coding changes, are specific to this individual. Our analyses of DU Mongolians and the first Mongolian genome provide valuable insight into genetic adaptation to extreme environments.

Phenotypic plasticity and genetic adaptation to high-altitude hypoxia in vertebrates.

Science.gov (United States)

Storz, Jay F; Scott, Graham R; Cheviron, Zachary A

2010-12-15

High-altitude environments provide ideal testing grounds for investigations of mechanism and process in physiological adaptation. In vertebrates, much of our understanding of the acclimatization response to high-altitude hypoxia derives from studies of animal species that are native to lowland environments. Such studies can indicate whether phenotypic plasticity will generally facilitate or impede adaptation to high altitude. Here, we review general mechanisms of physiological acclimatization and genetic adaptation to high-altitude hypoxia in birds and mammals. We evaluate whether the acclimatization response to environmental hypoxia can be regarded generally as a mechanism of adaptive phenotypic plasticity, or whether it might sometimes represent a misdirected response that acts as a hindrance to genetic adaptation. In cases in which the acclimatization response to hypoxia is maladaptive, selection will favor an attenuation of the induced phenotypic change. This can result in a form of cryptic adaptive evolution in which phenotypic similarity between high- and low-altitude populations is attributable to directional selection on genetically based trait variation that offsets environmentally induced changes. The blunted erythropoietic and pulmonary vasoconstriction responses to hypoxia in Tibetan humans and numerous high-altitude birds and mammals provide possible examples of this phenomenon. When lowland animals colonize high-altitude environments, adaptive phenotypic plasticity can mitigate the costs of selection, thereby enhancing prospects for population establishment and persistence. By contrast, maladaptive plasticity has the opposite effect. Thus, insights into the acclimatization response of lowland animals to high-altitude hypoxia can provide a basis for predicting how altitudinal range limits might shift in response to climate change.

practical common weight maximin approach for technology selection

African Journals Online (AJOL)

2014-06-30

Jun 30, 2014 ... proposes a multi-objective decision tool for industrial robot selection, which does not require subjective assessments ... Over the past several decades, manufacturers who have been faced with intense competition ... three groups: economic analysis techniques, analytical methods and strategic approaches.

Transbrachial artery approach for selective cerebral angiography

International Nuclear Information System (INIS)

Touho, Hajime; Karasawa, Jun; Shishido, Hisashi; Morisako, Toshitaka; Numazawa, Shinichi; Yamada, Keisuke; Nagai, Shigeki; Shibamoto, Kenji

1990-01-01

Transaxillary or transbrachial approaches to the cerebral vessels have been reported, but selective angiography of all four vessels has not been possible through one route. In this report, a new technique for selective cerebral angiography with transbrachial approach is described. One hundred and twenty three patients with cerebral infarction, vertebrobasilar insufficiency, intracerebral hemorrhage, epilepsy, or cerebral tumor were examined. Those patients consisted of 85 outpatients and 38 inpatients whose age ranged from 15 years old to 82 years old. The patients were examined via the transbrachial approach (97 cases via the right brachial, 29 cases via the left). Materials included a DSA system (Digital Fluorikon 5000, General Electric Co.), a 4 French tight J-curved Simmons 80-cm catheter, a 19-gauge extra-thin-wall Seldinger needle, and a J/Straight floppy 125-cm guide-wire. Generally, the volume of the contrast agent (300 mgI/ml iopamidol) used in the common carotid artery angiogram was 6 ml, while that used in the vertebral artery angiogram was 4 ml. If catheterization of the vertebral artery or right common carotid artery was unsuccessful, about 8 ml of the contrast agent was injected into the subclavian or branchiocephalic artery. Definitive diagnosis and a decision on proper treatment of the patients can be easily obtained, and the results were clinically satisfactory. Moreover, no complications were encountered in this study. This new technique making a transbrachial approach to the cerebral vessels using the DSA system is introduced here. Neurosurgeons can use this technique easily, and they will find that it provides them with all the information they need about the patient. (author)

An integrated approach towards future ballistic neck protection materials selection.

Science.gov (United States)

Breeze, John; Helliker, Mark; Carr, Debra J

2013-05-01

Ballistic protection for the neck has historically taken the form of collars attached to the ballistic vest (removable or fixed), but other approaches, including the development of prototypes incorporating ballistic material into the collar of an under body armour shirt, are now being investigated. Current neck collars incorporate the same ballistic protective fabrics as the soft armour of the remaining vest, reflecting how ballistic protective performance alone has historically been perceived as the most important property for neck protection. However, the neck has fundamental differences from the thorax in terms of anatomical vulnerability, flexibility and equipment integration, necessitating a separate solution from the thorax in terms of optimal materials selection. An integrated approach towards the selection of the most appropriate combination of materials to be used for each of the two potential designs of future neck protection has been developed. This approach requires evaluation of the properties of each potential material in addition to ballistic performance alone, including flexibility, mass, wear resistance and thermal burden. The aim of this article is to provide readers with an overview of this integrated approach towards ballistic materials selection and an update of its current progress in the development of future ballistic neck protection.

De-anonymizing Genomic Databases Using Phenotypic Traits

Directory of Open Access Journals (Sweden)

Humbert Mathias

2015-06-01

Full Text Available People increasingly have their genomes sequenced and some of them share their genomic data online. They do so for various purposes, including to find relatives and to help advance genomic research. An individual’s genome carries very sensitive, private information such as its owner’s susceptibility to diseases, which could be used for discrimination. Therefore, genomic databases are often anonymized. However, an individual’s genotype is also linked to visible phenotypic traits, such as eye or hair color, which can be used to re-identify users in anonymized public genomic databases, thus raising severe privacy issues. For instance, an adversary can identify a target’s genome using known her phenotypic traits and subsequently infer her susceptibility to Alzheimer’s disease. In this paper, we quantify, based on various phenotypic traits, the extent of this threat in several scenarios by implementing de-anonymization attacks on a genomic database of OpenSNP users sequenced by 23andMe. Our experimental results show that the proportion of correct matches reaches 23% with a supervised approach in a database of 50 participants. Our approach outperforms the baseline by a factor of four, in terms of the proportion of correct matches, in most scenarios. We also evaluate the adversary’s ability to predict individuals’ predisposition to Alzheimer’s disease, and we observe that the inference error can be halved compared to the baseline. We also analyze the effect of the number of known phenotypic traits on the success rate of the attack. As progress is made in genomic research, especially for genotype-phenotype associations, the threat presented in this paper will become more serious.

Materials selection in micromechanical design: an application of the Ashby approach

OpenAIRE

Srikar, V.T.; Spearing, S.M.

2003-01-01

The set of materials available to microsystems designers is rapidly expanding. Techniques now exist to introduce and integrate a large number of metals, alloys, ceramics, glasses, polymers, and elastomers into microsystems, motivating the need for a rational approach for materials selection in microsystems design. As a step toward such an approach, we focus on the initial stages of materials selection for micromechanical structures with minimum feature sizes greater than 1 /spl mu/m. The vari...

A genome-wide scan for signatures of directional selection in domesticated pigs.

Science.gov (United States)

Moon, Sunjin; Kim, Tae-Hun; Lee, Kyung-Tai; Kwak, Woori; Lee, Taeheon; Lee, Si-Woo; Kim, Myung-Jick; Cho, Kyuho; Kim, Namshin; Chung, Won-Hyong; Sung, Samsun; Park, Taesung; Cho, Seoae; Groenen, Martien Am; Nielsen, Rasmus; Kim, Yuseob; Kim, Heebal

2015-02-25

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication. Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness. We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

FeNO as biomarker for asthma phenotyping and management.

Science.gov (United States)

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

2015-01-01

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

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

Science.gov (United States)

Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes; Holmstrup, Martin; Nielsen, Niels Chr.; Loeschcke, Volker

2013-05-01

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic 1H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.

Dissecting high-dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matrices.

Science.gov (United States)

Runcie, Daniel E; Mukherjee, Sayan

2013-07-01

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism's entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse - affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.

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

Science.gov (United States)

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

2018-02-01

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

Animal biometrics: quantifying and detecting phenotypic appearance.

Science.gov (United States)

Kühl, Hjalmar S; Burghardt, Tilo

2013-07-01

Animal biometrics is an emerging field that develops quantified approaches for representing and detecting the phenotypic appearance of species, individuals, behaviors, and morphological traits. It operates at the intersection between pattern recognition, ecology, and information sciences, producing computerized systems for phenotypic measurement and interpretation. Animal biometrics can benefit a wide range of disciplines, including biogeography, population ecology, and behavioral research. Currently, real-world applications are gaining momentum, augmenting the quantity and quality of ecological data collection and processing. However, to advance animal biometrics will require integration of methodologies among the scientific disciplines involved. Such efforts will be worthwhile because the great potential of this approach rests with the formal abstraction of phenomics, to create tractable interfaces between different organizational levels of life. Copyright © 2013 Elsevier Ltd. All rights reserved.

Source selection for analogical reasoning an empirical approach

Energy Technology Data Exchange (ETDEWEB)

Stubblefield, W.A. [Sandia National Labs., Albuquerque, NM (United States); Luger, G.F. [Univ. of New Mexico, Albuquerque, NM (United States)

1996-12-31

The effectiveness of an analogical reasoner depends upon its ability to select a relevant analogical source. In many problem domains, however, too little is known about target problems to support effective source selection. This paper describes the design and evaluation of SCAVENGER, an analogical reasoner that applies two techniques to this problem: (1) An assumption-based approach to matching that allows properties of candidate sources to match unknown target properties in the absence of evidence to the contrary. (2) The use of empirical learning to improve memory organization based on problem solving experience.

Multi criteria decision making approaches for green supplier evaluation and selection

DEFF Research Database (Denmark)

Govindan, Kannan; Rajendran, S.; Sarkis, J.

2015-01-01

A large and growing body of literature to supplier evaluation and selection exists. Literature on green supplier evaluation that considers environmental factors are relatively limited. Recently, in supply chain management decision making, approaches for evaluating green supplier performance have ...... us to identify improvements for green supplier selection process and possible future directions.......A large and growing body of literature to supplier evaluation and selection exists. Literature on green supplier evaluation that considers environmental factors are relatively limited. Recently, in supply chain management decision making, approaches for evaluating green supplier performance have...... used both qualitative and quantitative environmental data. Given this evolving research field, the goal and purpose of this paper is to analyze research in international scientific journals and international conference proceedings that focus on green supplier selection. We propose the following...

An overview of potential molecular mechanisms involved in VSMC phenotypic modulation.

Science.gov (United States)

Zhang, Ming-Jie; Zhou, Yi; Chen, Lei; Wang, Yan-Qin; Wang, Xu; Pi, Yan; Gao, Chang-Yue; Li, Jing-Cheng; Zhang, Li-Li

2016-02-01

The fully differentiated medial vascular smooth muscle cells (VSMCs) of mature vessels keep quiescent and contractile. However, VSMC can exhibit the plasticity in phenotype switching from a differentiated and contractile phenotype to a dedifferentiated state in response to alterations in local environmental cues, which is called phenotypic modulation or switching. Distinguishing from its differentiated state expressing more smooth muscle (SM)-specific/selective proteins, the phenotypic modulation in VSMC is characterized by an increased rate of proliferation, migration, synthesis of extracellular matrix proteins and decreased expression of SM contractile proteins. Although it has been well demonstrated that phenotypic modulation of VSMC contributes to the occurrence and progression of many proliferative vascular diseases, little is known about the details of the molecular mechanisms of VSMC phenotypic modulation. Growing evidence suggests that variety of molecules including microRNAs, cytokines and biochemical factors, membrane receptors, ion channels, cytoskeleton and extracellular matrix play important roles in controlling VSMC phenotype. The focus of the present review is to provide an overview of potential molecular mechanisms involved in VSMC phenotypic modulation in recent years. To clarify VSMC differentiation and phenotypic modulation mechanisms will contribute to producing cell-based therapeutic interventions for aberrant VSMC differentiation-related diseases.

The expanding spectrum of COL2A1 gene variants IN 136 patients with a skeletal dysplasia phenotype.

Science.gov (United States)

Barat-Houari, Mouna; Dumont, Bruno; Fabre, Aurélie; Them, Frédéric Tm; Alembik, Yves; Alessandri, Jean-Luc; Amiel, Jeanne; Audebert, Séverine; Baumann-Morel, Clarisse; Blanchet, Patricia; Bieth, Eric; Brechard, Marie; Busa, Tiffany; Calvas, Patrick; Capri, Yline; Cartault, François; Chassaing, Nicolas; Ciorca, Vidrica; Coubes, Christine; David, Albert; Delezoide, Anne-Lise; Dupin-Deguine, Delphine; El Chehadeh, Salima; Faivre, Laurence; Giuliano, Fabienne; Goldenberg, Alice; Isidor, Bertrand; Jacquemont, Marie-Line; Julia, Sophie; Kaplan, Josseline; Lacombe, Didier; Lebrun, Marine; Marlin, Sandrine; Martin-Coignard, Dominique; Martinovic, Jelena; Masurel, Alice; Melki, Judith; Mozelle-Nivoix, Monique; Nguyen, Karine; Odent, Sylvie; Philip, Nicole; Pinson, Lucile; Plessis, Ghislaine; Quélin, Chloé; Shaeffer, Elise; Sigaudy, Sabine; Thauvin, Christel; Till, Marianne; Touraine, Renaud; Vigneron, Jacqueline; Baujat, Geneviève; Cormier-Daire, Valérie; Le Merrer, Martine; Geneviève, David; Touitou, Isabelle

2016-07-01

Heterozygous COL2A1 variants cause a wide spectrum of skeletal dysplasia termed type II collagenopathies. We assessed the impact of this gene in our French series. A decision tree was applied to select 136 probands (71 Stickler cases, 21 Spondyloepiphyseal dysplasia congenita cases, 11 Kniest dysplasia cases, and 34 other dysplasia cases) before molecular diagnosis by Sanger sequencing. We identified 66 different variants among the 71 positive patients. Among those patients, 18 belonged to multiplex families and 53 were sporadic. Most variants (38/44, 86%) were located in the triple helical domain of the collagen chain and glycine substitutions were mainly observed in severe phenotypes, whereas arginine to cysteine changes were more often encountered in moderate phenotypes. This series of skeletal dysplasia is one of the largest reported so far, adding 44 novel variants (15%) to published data. We have confirmed that about half of our Stickler patients (46%) carried a COL2A1 variant, and that the molecular spectrum was different across the phenotypes. To further address the question of genotype-phenotype correlation, we plan to screen our patients for other candidate genes using a targeted next-generation sequencing approach.

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

KAUST Repository

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

2016-01-01

traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based

Distribution and Outcomes of a Phenotype-Based Approach to Guide COPD Management: Results from the CHAIN Cohort.

Directory of Open Access Journals (Sweden)

Borja G Cosio

Full Text Available The Spanish guideline for COPD (GesEPOC recommends COPD treatment according to four clinical phenotypes: non-exacerbator phenotype with either chronic bronchitis or emphysema (NE, asthma-COPD overlap syndrome (ACOS, frequent exacerbator phenotype with emphysema (FEE or frequent exacerbator phenotype with chronic bronchitis (FECB. However, little is known on the distribution and outcomes of the four suggested phenotypes.We aimed to determine the distribution of these COPD phenotypes, and their relation with one-year clinical outcomes.We followed a cohort of well-characterized patients with COPD up to one-year. Baseline characteristics, health status (CAT, BODE index, rate of exacerbations and mortality up to one year of follow-up were compared between the four phenotypes.Overall, 831 stable COPD patients were evaluated. They were distributed as NE, 550 (66.2%; ACOS, 125 (15.0%; FEE, 38 (4.6%; and FECB, 99 (11.9%; additionally 19 (2.3% COPD patients with frequent exacerbations did not fulfill the criteria for neither FEE nor FECB. At baseline, there were significant differences in symptoms, FEV1 and BODE index (all p<0.05. The FECB phenotype had the highest CAT score (17.1±8.2, p<0.05 compared to the other phenotypes. Frequent exacerbator groups (FEE and FECB were receiving more pharmacological treatment at baseline, and also experienced more exacerbations the year after (all p<0.05 with no differences in one-year mortality. Most of NE (93% and half of exacerbators were stable after one year.There is an uneven distribution of COPD phenotypes in stable COPD patients, with significant differences in demographics, patient-centered outcomes and health care resources use.

Seleção recorrente fenotípica para florescimento precoce de feijoeiro 'Carioca' Phenotypic recurrent selection for early flowering of 'Carioca' common bean

Directory of Open Access Journals (Sweden)

Flávia Barbosa Silva

2007-10-01

Full Text Available O objetivo deste trabalho foi avaliar a eficiência da seleção recorrente fenotípica em relação ao número de dias para o início do florescimento em feijoeiro e verificar se a seleção afeta outros caracteres. Utilizou-se uma população proveniente da mistura das populações F2 (S0 de 11 combinações híbridas, avaliadas para a precocidade. As plantas S0 (ciclo 0, que floresceram mais precocemente, foram intercruzadas para a obtenção do ciclo I. As sementes obtidas foram utilizadas para a continuidade da seleção, e o processo foi repetido até o quinto ciclo seletivo. O progresso genético foi avaliado com cinqüenta e três progênies, provenientes da mistura das sementes das plantas S0 após uma autofecundação (S1:2 de cada ciclo. Os caracteres avaliados foram: número de dias para o florescimento, severidade da mancha-angular (Phaeoisariopsis griseola, número de dias para a maturação, produtividade e tipo de grãos. Constatou-se que o progresso com a seleção foi de 2,2% ao ano, o que indica que a seleção recorrente fenotípica foi efetiva em reduzir o número de dias para o florescimento. Não houve resposta correlacionada à seleção quanto ao número de dias para o florescimento nos demais caracteres avaliados, do que se depreende ser possível a seleção de progênies que associem florescimento precoce à expressão fenotípica dos demais caracteres, conforme o interesse dos melhoristas.The objective of this work was to evaluate the efficiency of phenotypic recurrent selection for the number of days until blooming in common bean, and to verify if this selection affected other traits. One S0 population derived from the mixture of the F2 populations of 11 hybrid combinations evaluated for earliness was used. The plants of the S0 (cycle 0 which bloomed first were crossed to obtain cycle I. To go on with the selection the obtained seeds were used. The process was repeated until the fifth selection cycle. Fifty-three S1

Treatment to sustain a Th17-type phenotype to prevent skewing toward Treg and to limit premalignant lesion progression to cancer.

Science.gov (United States)

Young, M Rita I; Levingston, Corinne A; Johnson, Sara D

2016-05-15

While immune suppression is a hallmark of head and neck squamous cell carcinoma (HSNCC), the immunological impact of premalignant oral lesions, which often precedes development of HNSCC, is unknown. The present study assessed the changes in splenic and draining lymph node CD4(+) cell populations and their production of select cytokines that occur in mice with carcinogen-induced premalignant oral lesions and the changes that occur as lesions progress to oral cancer. These studies found skewing toward Th1 and Th17-type phenotypes in the spleen and lymph nodes of mice with premalignant oral lesions and a shift to Treg as lesions progress to cancer. Since the role of Th17 cells in the progression from premalignant lesions to cancer is not clear, studies determined the immunological and clinical effect of treating mice bearing premalignant oral lesions with a TGF-β type 1 receptor inhibitor plus IL-23 as an approach to sustain the Th17 phenotype. These studies showed that the treatment approach not only sustained the Th17 phenotype, but also increased distal spleen cell and regional lymph node cell production of other stimulatory/inflammatory mediators and slowed premalignant lesion progression to cancer. © 2016 UICC.

A new approach to the LILW repository site selection

International Nuclear Information System (INIS)

Mele, I.; Zeleznik, N.

1998-01-01

After the failure of site selection, which was performed between 1990-1993, the Agency for Radwaste Management was urged to start a new site selection process for low and intermediate level waste (LILW). Since this is the most sensitive and delicate phase of the whole disposal project extensive analyses of foreign and domestic experiences in siting were performed. Three different models were studied and discussed at a workshop on preparation of the siting procedure for LILW repository. The participants invited to the workshop supported the combined approach, to the site selection, which is presented in this paper.(author)

A Fuzzy Decision Making Approach for Supplier Selection in Healthcare Industry

OpenAIRE

Zeynep Sener; Mehtap Dursun

2014-01-01

Supplier evaluation and selection is one of the most important components of an effective supply chain management system. Due to the expanding competition in healthcare, selecting the right medical device suppliers offers great potential for increasing quality while decreasing costs. This paper proposes a fuzzy decision making approach for medical supplier selection. A real-world medical device supplier selection problem is presented to illustrate the application of the proposed decision meth...

Current Approaches for Phenotyping as a Target for Precision Medicine in COPD Management.

Science.gov (United States)

Lopez-Campos, Jose Luis; Centanni, Stefano

2018-03-20

The study of airway diseases continues to present several challenges for modern medicine. The different disease presentations with variables and overlapping features may result in a real challenge for the clinician. In this context, the concept of precision medicine has started to emerge in order to give answers to some of these challenges from a diagnostic and therapeutic point of view. The main reasons to target for precision medicine in chronic obstructive pulmonary disease (COPD) include that there is variability in the clinical presentation, there is no correlation between the different clinical variables at the patient level, there are a number of relevant clinical variables associated with outcomes, we do have specific therapies for specific patient types, and that there is variability in the clinical response to different therapies. To bring precision medicine into clinical practice several approaches have been used, including the use of independent variables to identify subjects, the use of multidimensional indexes, the so-called clinical phenotypes, and the approximation by the so-called treatable traits. All these approaches have their strengths and weaknesses which are reviewed in the present document. Although there is no universally accepted proposal, the available initiatives provide us with a framework on which to start working and move toward precision medicine in COPD, with the ultimate goal of bringing the best possible medicine to each patient in particular.

Phenotypic and functional characterization of earthworm coelomocyte subsets

DEFF Research Database (Denmark)

Engelmann, Péter; Hayashi, Yuya; Bodo, Kornélia

2016-01-01

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

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

Science.gov (United States)

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.

Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants

Czech Academy of Sciences Publication Activity Database

Großkinsky, D.K.; Syaifullah, S. J.; Roitsch, Thomas

2017-01-01

Roč. 99, č. 99 (2017), s. 1-20 ISSN 0022-0957 R&D Projects: GA MŠk(CZ) LO1415 Institutional support: RVO:67179843 Keywords : integrated approaches * multi-omics * phenomics * plant development * plant–environment interactions * plant phenotyping * plant physiology * plant senescence * senescence programme * systems biology Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 5.830, year: 2016

Developing, Approving and Maintaining Qualifications: Selected International Approaches. Research Report

Science.gov (United States)

Misko, Josie

2015-01-01

There are lessons for Australia in the key approaches to the development, approval, maintenance and quality assurance of qualifications adopted in countries overseas. This research takes into account a range of approaches used in selected European Union (EU) member states (Germany, Finland and Sweden), the United Kingdom (England, Northern Ireland…

Understanding mammalian genetic systems: the challenge of phenotyping in the mouse.

Directory of Open Access Journals (Sweden)

Steve D M Brown

2006-08-01

Full Text Available Understanding mammalian genetic systems is predicated on the determination of the relationship between genetic variation and phenotype. Several international programmes are under way to deliver mutations in every gene in the mouse genome. The challenge for mouse geneticists is to develop approaches that will provide comprehensive phenotype datasets for these mouse mutant libraries. Several factors are critical to success in this endeavour. It will be important to catalogue assay and environment and where possible to adopt standardised procedures for phenotyping tests along with common environmental conditions to ensure comparable datasets of phenotypes. Moreover, the scale of the task underlines the need to invest in technological development improving both the speed and cost of phenotyping platforms. In addition, it will be necessary to develop new informatics standards that capture the phenotype assay as well as other factors, genetic and environmental, that impinge upon phenotype outcome.

Comparison of a rational vs. high throughput approach for rapid salt screening and selection.

Science.gov (United States)

Collman, Benjamin M; Miller, Jonathan M; Seadeek, Christopher; Stambek, Julie A; Blackburn, Anthony C

2013-01-01

In recent years, high throughput (HT) screening has become the most widely used approach for early phase salt screening and selection in a drug discovery/development setting. The purpose of this study was to compare a rational approach for salt screening and selection to those results previously generated using a HT approach. The rational approach involved a much smaller number of initial trials (one salt synthesis attempt per counterion) that were selected based on a few strategic solubility determinations of the free form combined with a theoretical analysis of the ideal solvent solubility conditions for salt formation. Salt screening results for sertraline, tamoxifen, and trazodone using the rational approach were compared to those previously generated by HT screening. The rational approach produced similar results to HT screening, including identification of the commercially chosen salt forms, but with a fraction of the crystallization attempts. Moreover, the rational approach provided enough solid from the very initial crystallization of a salt for more thorough and reliable solid-state characterization and thus rapid decision-making. The crystallization techniques used in the rational approach mimic larger-scale process crystallization, allowing smoother technical transfer of the selected salt to the process chemist.

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

Directory of Open Access Journals (Sweden)

Himel eMallick

2016-03-01

Full Text Available 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

Low level of polyandry constrains phenotypic plasticity of male body size in mites.

Directory of Open Access Journals (Sweden)

Peter Schausberger

Full Text Available Polyandry, i.e. females mating with multiple males, is more common than previously anticipated and potentially provides both direct and indirect fitness benefits to females. The level of polyandry (defined by the lifetime number of male mates of a female is an important determinant of the occurrence and intensity of sexual selection acting on male phenotypes. While the forces of sexual selection acting on phenotypic male traits such as body size are relatively well understood, sexual selection acting on phenotypic plasticity of these traits is unexplored. We tackled this issue by scrutinizing the link between polyandry and phenotypic plasticity of male body size in two sympatric plant-inhabiting predatory mite species, Phytoseiulus persimilis and Neoseiulus californicus. These two species are similar in life history, ecological niche requirements, mating behavior, polygyny and female body size plasticity but strikingly differ in the level of both polyandry and phenotypic plasticity of male body size (both lower in P. persimilis. We hypothesized that deviations from standard body size, i.e. the size achieved under favorable conditions, incur higher costs for males in the less polyandrous P. persimilis. To test our hypotheses, we conducted two experiments on (i the effects of male body size on spermatophore transfer in singly mating females and (ii the effects of mate sequence (switching the order of standard-sized and small males on mating behavior and paternity success in doubly mating females. In P. persimilis but not N. californicus, small males transferred fewer but larger spermatophores to the females; in both species, females re-mated more likely with standard-sized following small than small following standard-sized males; in P. persimilis, first standard-sized males sired a higher proportion of offspring produced after re-mating by the female than first small males, whereas in N. californicus the paternity success of small and standard

Low level of polyandry constrains phenotypic plasticity of male body size in mites.

Science.gov (United States)

Schausberger, Peter; Walzer, Andreas; Murata, Yasumasa; Osakabe, Masahiro

2017-01-01

Polyandry, i.e. females mating with multiple males, is more common than previously anticipated and potentially provides both direct and indirect fitness benefits to females. The level of polyandry (defined by the lifetime number of male mates of a female) is an important determinant of the occurrence and intensity of sexual selection acting on male phenotypes. While the forces of sexual selection acting on phenotypic male traits such as body size are relatively well understood, sexual selection acting on phenotypic plasticity of these traits is unexplored. We tackled this issue by scrutinizing the link between polyandry and phenotypic plasticity of male body size in two sympatric plant-inhabiting predatory mite species, Phytoseiulus persimilis and Neoseiulus californicus. These two species are similar in life history, ecological niche requirements, mating behavior, polygyny and female body size plasticity but strikingly differ in the level of both polyandry and phenotypic plasticity of male body size (both lower in P. persimilis). We hypothesized that deviations from standard body size, i.e. the size achieved under favorable conditions, incur higher costs for males in the less polyandrous P. persimilis. To test our hypotheses, we conducted two experiments on (i) the effects of male body size on spermatophore transfer in singly mating females and (ii) the effects of mate sequence (switching the order of standard-sized and small males) on mating behavior and paternity success in doubly mating females. In P. persimilis but not N. californicus, small males transferred fewer but larger spermatophores to the females; in both species, females re-mated more likely with standard-sized following small than small following standard-sized males; in P. persimilis, first standard-sized males sired a higher proportion of offspring produced after re-mating by the female than first small males, whereas in N. californicus the paternity success of small and standard-sized males was

The temporal distribution of directional gradients under selection for an optimum.

Science.gov (United States)

Chevin, Luis-Miguel; Haller, Benjamin C

2014-12-01

Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population- and individual-based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Metformin treatment in different phenotypes of polycystic ovary syndrome.

Science.gov (United States)

Hosseini, Marzieh Agha; Alleyassin, Ashraf; Sarvi, Fatemeh; Safdarian, Leila; Kokab, Abas; Fanisalek, Mehran

2013-11-01

The aim of this study was to evaluate the effectiveness of Metformin on ovulation and eventual clinical pregnancy in different phenotypes of polycystic ovary syndrome (PCOS). A total of 359 subjects who had proven PCOS according to Rotterdam criteria were prospectively selected. Patients' PCOS phenotypes were determined and recorded. All patients were younger than 35 years. Clinical and biochemical assays in all patients were initially obtained. Then patients were divided into two separate groups. One group received both 1,500 mg of Metformin and 1 mg of folic acid per day and the other group received only 1 mg of folic acid for a total of 2 months. Subsequently, all patients underwent ovulation stimulation with 5 mg of Letrozole per day for 5 days followed by an intra-uterine insemination. Finally, ovulation and pregnancy rates were evaluated for all four PCOS phenotypes. Effect of Metformin therapy was evaluated for each group and each phenotype. The pregnancy rate in Metformin and non-Metformin groups were, respectively, as follows: in phenotype A (39.2 vs. 33.7 %, p = 0.270), phenotype B (43.8 vs. 20 %, p = 0.210), phenotype C (44 vs. 20 %, p = 0.064), and phenotype D (36.5 vs. 28.6 %, p = 0.279). Although there was a little improvement in ovulation and pregnancy rates among patients with B and C phenotypes, there was not a statistically significant difference between the two groups. Based on our study, Metformin therapy does not change the ovulation and pregnancy rate.

Williams' paradox and the role of phenotypic plasticity in sexual systems.

Science.gov (United States)

Leonard, Janet L

2013-10-01

As George Williams pointed out in 1975, although evolutionary explanations, based on selection acting on individuals, have been developed for the advantages of simultaneous hermaphroditism, sequential hermaphroditism and gonochorism, none of these evolutionary explanations adequately explains the current distribution of these sexual systems within the Metazoa (Williams' Paradox). As Williams further pointed out, the current distribution of sexual systems is explained largely by phylogeny. Since 1975, we have made a great deal of empirical and theoretical progress in understanding sexual systems. However, we still lack a theory that explains the current distribution of sexual systems in animals and we do not understand the evolutionary transitions between hermaphroditism and gonochorism. Empirical data, collected over the past 40 years, demonstrate that gender may have more phenotypic plasticity than was previously realized. We know that not only sequential hermaphrodites, but also simultaneous hermaphrodites have phenotypic plasticity that alters sex allocation in response to social and environmental conditions. A focus on phenotypic plasticity suggests that one sees a continuum in animals between genetically determined gonochorism on the one hand and simultaneous hermaphroditism on the other, with various types of sequential hermaphroditism and environmental sex determination as points along the spectrum. Here I suggest that perhaps the reason we have been unable to resolve Williams' Paradox is because the problem was not correctly framed. First, because, for example, simultaneous hermaphroditism provides reproductive assurance or dioecy ensures outcrossing does not mean that there are no other evolutionary paths that can provide adaptive responses to those selective pressures. Second, perhaps the question we need to ask is: What selective forces favor increased versus reduced phenotypic plasticity in gender expression? It is time to begin to look at the question

Comparing geological and statistical approaches for element selection in sediment tracing research

Science.gov (United States)

Laceby, J. Patrick; McMahon, Joe; Evrard, Olivier; Olley, Jon

2015-04-01

Elevated suspended sediment loads reduce reservoir capacity and significantly increase the cost of operating water treatment infrastructure, making the management of sediment supply to reservoirs of increasingly importance. Sediment fingerprinting techniques can be used to determine the relative contributions of different sources of sediment accumulating in reservoirs. The objective of this research is to compare geological and statistical approaches to element selection for sediment fingerprinting modelling. Time-integrated samplers (n=45) were used to obtain source samples from four major subcatchments flowing into the Baroon Pocket Dam in South East Queensland, Australia. The geochemistry of potential sources were compared to the geochemistry of sediment cores (n=12) sampled in the reservoir. The geochemical approach selected elements for modelling that provided expected, observed and statistical discrimination between sediment sources. Two statistical approaches selected elements for modelling with the Kruskal-Wallis H-test and Discriminatory Function Analysis (DFA). In particular, two different significance levels (0.05 & 0.35) for the DFA were included to investigate the importance of element selection on modelling results. A distribution model determined the relative contributions of different sources to sediment sampled in the Baroon Pocket Dam. Elemental discrimination was expected between one subcatchment (Obi Obi Creek) and the remaining subcatchments (Lexys, Falls and Bridge Creek). Six major elements were expected to provide discrimination. Of these six, only Fe2O3 and SiO2 provided expected, observed and statistical discrimination. Modelling results with this geological approach indicated 36% (+/- 9%) of sediment sampled in the reservoir cores were from mafic-derived sources and 64% (+/- 9%) were from felsic-derived sources. The geological and the first statistical approach (DFA0.05) differed by only 1% (σ 5%) for 5 out of 6 model groupings with only

Genotypic and Phenotypic Analysis of Dairy Lactococcus lactis Biodiversity in Milk: Volatile Organic Compounds as Discriminating Markers

Science.gov (United States)

Dhaisne, Amandine; Guellerin, Maeva; Laroute, Valérie; Laguerre, Sandrine; Le Bourgeois, Pascal; Loubiere, Pascal

2013-01-01

The diversity of nine dairy strains of Lactococcus lactis subsp. lactis in fermented milk was investigated by both genotypic and phenotypic analyses. Pulsed-field gel electrophoresis and multilocus sequence typing were used to establish an integrated genotypic classification. This classification was coherent with discrimination of the L. lactis subsp. lactis bv. diacetylactis lineage and reflected clonal complex phylogeny and the uniqueness of the genomes of these strains. To assess phenotypic diversity, 82 variables were selected as important dairy features; they included physiological descriptors and the production of metabolites and volatile organic compounds (VOCs). Principal-component analysis (PCA) demonstrated the phenotypic uniqueness of each of these genetically closely related strains, allowing strain discrimination. A method of variable selection was developed to reduce the time-consuming experimentation. We therefore identified 20 variables, all associated with VOCs, as phenotypic markers allowing discrimination between strain groups. These markers are representative of the three metabolic pathways involved in flavor: lipolysis, proteolysis, and glycolysis. Despite great phenotypic diversity, the strains could be divided into four robust phenotypic clusters based on their metabolic orientations. Inclusion of genotypic diversity in addition to phenotypic characters in the classification led to five clusters rather than four being defined. However, genotypic characters make a smaller contribution than phenotypic variables (no genetic distances selected among the most contributory variables). This work proposes an original method for the phenotypic differentiation of closely related strains in milk and may be the first step toward a predictive classification for the manufacture of starters. PMID:23709512

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

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Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

A simulated annealing approach to supplier selection aware inventory planning

OpenAIRE

Turk, Seda; Miller, Simon; Özcan, Ender; John, Robert

2015-01-01

Selection of an appropriate supplier is a crucial and challenging task in the effective management of a supply chain. Also, appropriate inventory management is critical to the success of a supply chain operation. In recent years, there has been a growing interest in the area of selection of an appropriate vendor and creating good inventory planning using supplier selection information. In this paper, we consider both of these tasks in a two-stage approach employing Interval Type-2 Fuzzy Sets ...

Semi-supervised Learning for Phenotyping Tasks.

Science.gov (United States)

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.

Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

Directory of Open Access Journals (Sweden)

Rakesh Garg

2015-06-01

Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

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

DEFF Research Database (Denmark)

Kring, Sofia Inez Iqbal; Larsen, Lesli Hingstrup; Holst, Claus

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....

A potential approach for low flow selection in water resource supply and management

Science.gov (United States)

Ouyang, Ying

2012-08-01

SummaryLow flow selections are essential to water resource management, water supply planning, and watershed ecosystem restoration. In this study, a new approach, namely the frequent-low (FL) approach (or frequent-low index), was developed based on the minimum frequent-low flow or level used in minimum flows and/or levels program in northeast Florida, USA. This FL approach was then compared to the conventional 7Q10 approach for low flow selections prior to its applications, using the USGS flow data from the freshwater environment (Big Sunflower River, Mississippi) as well as from the estuarine environment (St. Johns River, Florida). Unlike the FL approach that is associated with the biological and ecological impacts, the 7Q10 approach could lead to the selections of extremely low flows (e.g., near-zero flows) that may hinder its use for establishing criteria to prevent streams from significant harm to biological and ecological communities. Additionally, the 7Q10 approach could not be used when the period of data records is less than 10 years by definition while this may not the case for the FL approach. Results from both approaches showed that the low flows from the Big Sunflower River and the St. Johns River decreased as time elapsed, demonstrating that these two rivers have become drier during the last several decades with a potential of salted water intrusion to the St. Johns River. Results from the FL approach further revealed that the recurrence probability of low flow increased while the recurrence interval of low flow decreased as time elapsed in both rivers, indicating that low flows occurred more frequent in these rivers as time elapsed. This report suggests that the FL approach, developed in this study, is a useful alternative for low flow selections in addition to the 7Q10 approach.

Distributions of Mutational Effects and the Estimation of Directional Selection in Divergent Lineages of Arabidopsis thaliana.

Science.gov (United States)

Park, Briton; Rutter, Matthew T; Fenster, Charles B; Symonds, V Vaughan; Ungerer, Mark C; Townsend, Jeffrey P

2017-08-01

Mutations are crucial to evolution, providing the ultimate source of variation on which natural selection acts. Due to their key role, the distribution of mutational effects on quantitative traits is a key component to any inference regarding historical selection on phenotypic traits. In this paper, we expand on a previously developed test for selection that could be conducted assuming a Gaussian mutation effect distribution by developing approaches to also incorporate any of a family of heavy-tailed Laplace distributions of mutational effects. We apply the test to detect directional natural selection on five traits along the divergence of Columbia and Landsberg lineages of Arabidopsis thaliana , constituting the first test for natural selection in any organism using quantitative trait locus and mutation accumulation data to quantify the intensity of directional selection on a phenotypic trait. We demonstrate that the results of the test for selection can depend on the mutation effect distribution specified. Using the distributions exhibiting the best fit to mutation accumulation data, we infer that natural directional selection caused divergence in the rosette diameter and trichome density traits of the Columbia and Landsberg lineages. Copyright © 2017 by the Genetics Society of America.

Cell and small animal models for phenotypic drug discovery

Directory of Open Access Journals (Sweden)

Szabo M

2017-06-01

Full Text Available Mihaly Szabo,1 Sara Svensson Akusjärvi,1 Ankur Saxena,1 Jianping Liu,2 Gayathri Chandrasekar,1 Satish S Kitambi1 1Department of Microbiology Tumor, and Cell Biology, 2Department of Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden Abstract: 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. Keywords: phenotype, screening, PDD, discovery, zebrafish, drug

Phenotype prediction for mucopolysaccharidosis type I by in silico analysis.

Science.gov (United States)

Ou, Li; Przybilla, Michael J; Whitley, Chester B

2017-07-04

Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease due to deficiency of α-L-iduronidase (IDUA), a lysosomal enzyme that degrades glycosaminoglycans (GAG) heparan and dermatan sulfate. To achieve optimal clinical outcomes, early and proper treatment is essential, which requires early diagnosis and phenotype severity prediction. To establish a genotype/phenotype correlation of MPS I disease, a combination of bioinformatics tools including SIFT, PolyPhen, I-Mutant, PROVEAN, PANTHER, SNPs&GO and PHD-SNP are utilized. Through analyzing single nucleotide polymorphisms (SNPs) by these in silico approaches, 28 out of 285 missense SNPs were predicted to be damaging. By integrating outcomes from these in silico approaches, a prediction algorithm (sensitivity 94%, specificity 80%) was thereby developed. Three dimensional structural analysis of 5 candidate SNPs (P533R, P496R, L346R, D349G, T374P) were performed by SWISS PDB viewer, which revealed specific structural changes responsible for the functional impacts of these SNPs. Additionally, SNPs in the untranslated region were analyzed by UTRscan and PolymiRTS. Moreover, by investigating known pathogenic mutations and relevant patient phenotypes in previous publications, phenotype severity (severe, intermediate or mild) of each mutation was deduced. Collectively, these results identified potential candidate SNPs with functional significance for studying MPS I disease. This study also demonstrates the effectiveness, reliability and simplicity of these in silico approaches in addressing complexity of underlying genetic basis of MPS I disease. Further, a step-by-step guideline for phenotype prediction of MPS I disease is established, which can be broadly applied in other lysosomal diseases or genetic disorders.

SAP is required for the development of innate phenotype in H2-M3-restricted CD8+ T cells1

Science.gov (United States)

Bediako, Yaw; Bian, Yao; Zhang, Hong; Cho, Hoonsik; Stein, Paul L.; Wang, Chyung-Ru

2012-01-01

H2-M3-restricted T cells have a pre-activated surface phenotype, rapidly expand and produce cytokines upon stimulation and as such, are classified as innate T cells. Unlike most innate T cells, M3-restricted T cells also express CD8αβ co-receptors and a diverse TCR repertoire: hallmarks of conventional MHC Ia-restricted CD8+ T cells. Although iNKT cells are also innate lymphocytes, they are selected exclusively on hematopoietic cells (HC), while M3-restricted T cells can be selected on either hematopoietic or thymic epithelial cells (TEC). Moreover, their phenotypes differ depending on what cells mediate their selection. Though there is a clear correlation between selection on HC and development of innate phenotype, the underlying mechanism remains unclear. SAP is required for the development of iNKT cells and mediates signals from SLAM receptors that are exclusively expressed on HC. Based on their dual selection pathway, M3-restricted T cells present a unique model for studying the development of innate T cell phenotype. Using both polyclonal and transgenic mouse models we demonstrate that while M3-restricted T cells are capable of developing in the absence of SAP, SAP is required for HC-mediated selection, development of pre-activated phenotype and heightened effector functions of M3-restricted T cells. These findings are significant because they directly demonstrate the need for SAP in HC-mediated acquisition of innate T cell phenotype and suggest that due to their SAP-dependent HC-mediated selection, M3-restricted T cells develop a pre-activated phenotype and an intrinsic ability to proliferate faster upon stimulation, allowing for an important role in the early response to infection. PMID:23041566

Cow genotyping strategies for genomic selection in a small dairy cattle population.

Science.gov (United States)

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants.

Science.gov (United States)

Großkinsky, Dominik K; Syaifullah, Syahnada Jaya; Roitsch, Thomas

2018-02-12

The study of senescence in plants is complicated by diverse levels of temporal and spatial dynamics as well as the impact of external biotic and abiotic factors and crop plant management. Whereas the molecular mechanisms involved in developmentally regulated leaf senescence are very well understood, in particular in the annual model plant species Arabidopsis, senescence of other organs such as the flower, fruit, and root is much less studied as well as senescence in perennials such as trees. This review addresses the need for the integration of multi-omics techniques and physiological phenotyping into holistic phenomics approaches to dissect the complex phenomenon of senescence. That became feasible through major advances in the establishment of various, complementary 'omics' technologies. Such an interdisciplinary approach will also need to consider knowledge from the animal field, in particular in relation to novel regulators such as small, non-coding RNAs, epigenetic control and telomere length. Such a characterization of phenotypes via the acquisition of high-dimensional datasets within a systems biology approach will allow us to systematically characterize the various programmes governing senescence beyond leaf senescence in Arabidopsis and to elucidate the underlying molecular processes. Such a multi-omics approach is expected to also spur the application of results from model plants to agriculture and their verification for sustainable and environmentally friendly improvement of crop plant stress resilience and productivity and contribute to improvements based on postharvest physiology for the food industry and the benefit of its customers. © The Author(s) 2017. 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 quantitative genetics of phenotypic variation in animals

NARCIS (Netherlands)

Hill, W.G.; Mulder, H.A.; Zhang, X.S.

2007-01-01

Considerable attention has been paid to estimating genetic variability in quantitative traits and to how it is maintained and changed by selection in natural and domesticated populations, but rather little attention has been paid to how levels of environmental and phenotypic variance are influenced.

Selecting the Best: Evolutionary Engineering of Chemical Production in Microbes.

Science.gov (United States)

Shepelin, Denis; Hansen, Anne Sofie Lærke; Lennen, Rebecca; Luo, Hao; Herrgård, Markus J

2018-05-11

Microbial cell factories have proven to be an economical means of production for many bulk, specialty, and fine chemical products. However, we still lack both a holistic understanding of organism physiology and the ability to predictively tune enzyme activities in vivo, thus slowing down rational engineering of industrially relevant strains. An alternative concept to rational engineering is to use evolution as the driving force to select for desired changes, an approach often described as evolutionary engineering. In evolutionary engineering, in vivo selections for a desired phenotype are combined with either generation of spontaneous mutations or some form of targeted or random mutagenesis. Evolutionary engineering has been used to successfully engineer easily selectable phenotypes, such as utilization of a suboptimal nutrient source or tolerance to inhibitory substrates or products. In this review, we focus primarily on a more challenging problem-the use of evolutionary engineering for improving the production of chemicals in microbes directly. We describe recent developments in evolutionary engineering strategies, in general, and discuss, in detail, case studies where production of a chemical has been successfully achieved through evolutionary engineering by coupling production to cellular growth.

PhenoTips: patient phenotyping software for clinical and research use.

Science.gov (United States)

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.

A New Spectral Shape-Based Record Selection Approach Using Np and Genetic Algorithms

Directory of Open Access Journals (Sweden)

Edén Bojórquez

2013-01-01

Full Text Available With the aim to improve code-based real records selection criteria, an approach inspired in a parameter proxy of spectral shape, named Np, is analyzed. The procedure is based on several objectives aimed to minimize the record-to-record variability of the ground motions selected for seismic structural assessment. In order to select the best ground motion set of records to be used as an input for nonlinear dynamic analysis, an optimization approach is applied using genetic algorithms focuse on finding the set of records more compatible with a target spectrum and target Np values. The results of the new Np-based approach suggest that the real accelerograms obtained with this procedure, reduce the scatter of the response spectra as compared with the traditional approach; furthermore, the mean spectrum of the set of records is very similar to the target seismic design spectrum in the range of interest periods, and at the same time, similar Np values are obtained for the selected records and the target spectrum.

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

Science.gov (United States)

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

2017-10-01

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

Efficient selection against categorically scored hip dysplasia in dogs is possible using best linear unbiased prediction and optimum contribution selection: a simulation study

DEFF Research Database (Denmark)

Malm, S; Sørensen, Anders Christian; Fikse, W F

2013-01-01

Breeding to reduce the prevalence of categorically scored hip dysplasia (HD), based on phenotypic assessment of radiographic hip status, has had limited success. The aim of this study was to evaluate two selection strategies for improved hip status: truncation selection based on phenotypic record...

Wine Expertise Predicts Taste Phenotype.

Science.gov (United States)

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.

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

A Diagnostic Approach to Increase Reusable Dinnerware Selection in a Cafeteria

Science.gov (United States)

Manuel, Jennifer C.; Sunseri, Mary Anne; Olson, Ryan; Scolari, Miranda

2007-01-01

The current project tested a diagnostic approach to selecting interventions to increase patron selection of reusable dinnerware in a cafeteria. An assessment survey, completed by a sample of 43 patrons, suggested that the primary causes of wasteful behavior were (a) environmental arrangement of dinnerware options and (b) competing motivational…

The macroevolutionary consequences of phenotypic integration: from development to deep time.

Science.gov (United States)

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.

Accounting for linkage disequilibrium in genome scans for selection without individual genotypes: The local score approach.

Science.gov (United States)

Fariello, María Inés; Boitard, Simon; Mercier, Sabine; Robelin, David; Faraut, Thomas; Arnould, Cécile; Recoquillay, Julien; Bouchez, Olivier; Salin, Gérald; Dehais, Patrice; Gourichon, David; Leroux, Sophie; Pitel, Frédérique; Leterrier, Christine; SanCristobal, Magali

2017-07-01

Detecting genomic footprints of selection is an important step in the understanding of evolution. Accounting for linkage disequilibrium in genome scans increases detection power, but haplotype-based methods require individual genotypes and are not applicable on pool-sequenced samples. We propose to take advantage of the local score approach to account for linkage disequilibrium in genome scans for selection, cumulating (possibly small) signals from single markers over a genomic segment, to clearly pinpoint a selection signal. Using computer simulations, we demonstrate that this approach detects selection with higher power than several state-of-the-art single-marker, windowing or haplotype-based approaches. We illustrate this on two benchmark data sets including individual genotypes, for which we obtain similar results with the local score and one haplotype-based approach. Finally, we apply the local score approach to Pool-Seq data obtained from a divergent selection experiment on behaviour in quail and obtain precise and biologically coherent selection signals: while competing methods fail to highlight any clear selection signature, our method detects several regions involving genes known to act on social responsiveness or autistic traits. Although we focus here on the detection of positive selection from multiple population data, the local score approach is general and can be applied to other genome scans for selection or other genomewide analyses such as GWAS. © 2017 John Wiley & Sons Ltd.

Dissecting molecular stress networks: identifying nodes of divergence between life-history phenotypes.

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Schwartz, Tonia S; Bronikowski, Anne M

2013-02-01

The complex molecular network that underlies physiological stress response is comprised of nodes (proteins, metabolites, mRNAs, etc.) whose connections span cells, tissues and organs. Variable nodes are points in the network upon which natural selection may act. Thus, identifying variable nodes will reveal how this molecular stress network may evolve among populations in different habitats and how it might impact life-history evolution. Here, we use physiological and genetic assays to test whether laboratory-born juveniles from natural populations of garter snakes (Thamnophis elegans), which have diverged in their life-history phenotypes, vary concomitantly at candidate nodes of the stress response network, (i) under unstressed conditions and (ii) in response to an induced stress. We found that two common measures of stress (plasma corticosterone and liver gene expression of heat shock proteins) increased under stress in both life-history phenotypes. In contrast, the phenotypes diverged at four nodes both under unstressed conditions and in response to stress: circulating levels of reactive oxygen species (superoxide, H(2)O(2)); liver gene expression of GPX1 and erythrocyte DNA damage. Additionally, allele frequencies for SOD2 diverge from neutral markers, suggesting diversifying selection on SOD2 alleles. This study supports the hypothesis that these life-history phenotypes have diverged at the molecular level in how they respond to stress, particularly in nodes regulating oxidative stress. Furthermore, the differences between the life-history phenotypes were more pronounced in females. We discuss the responses to stress in the context of the associated life-history phenotype and the evolutionary pressures thought to be responsible for divergence between the phenotypes. © 2012 Blackwell Publishing Ltd.

Exome sequencing for gene discovery in lethal fetal disorders--harnessing the value of extreme phenotypes.

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Filges, Isabel; Friedman, Jan M

2015-10-01

Massively parallel sequencing has revolutionized our understanding of Mendelian disorders, and many novel genes have been discovered to cause disease phenotypes when mutant. At the same time, next-generation sequencing approaches have enabled non-invasive prenatal testing of free fetal DNA in maternal blood. However, little attention has been paid to using whole exome and genome sequencing strategies for gene identification in fetal disorders that are lethal in utero, because they can appear to be sporadic and Mendelian inheritance may be missed. We present challenges and advantages of applying next-generation sequencing approaches to gene discovery in fetal malformation phenotypes and review recent successful discovery approaches. We discuss the implication and significance of recessive inheritance and cross-species phenotyping in fetal lethal conditions. Whole exome sequencing can be used in individual families with undiagnosed lethal congenital anomaly syndromes to discover causal mutations, provided that prior to data analysis, the fetal phenotype can be correlated to a particular developmental pathway in embryogenesis. Cross-species phenotyping allows providing further evidence for causality of discovered variants in genes involved in those extremely rare phenotypes and will increase our knowledge about normal and abnormal human developmental processes. Ultimately, families will benefit from the option of early prenatal diagnosis. © 2014 John Wiley & Sons, Ltd.

Selecting appropriate wastewater treatment technologies using a choosing-by-advantages approach.

Science.gov (United States)

Arroyo, Paz; Molinos-Senante, María

2018-06-01

Selecting the most sustainable wastewater treatment (WWT) technology among possible alternatives is a very complex task because the choice must integrate economic, environmental, and social criteria. Traditionally, several multi-criteria decision-making approaches have been applied, with the most often used being the analytical hierarchical process (AHP). However, AHP allows users to offset poor environmental and/or social performance with low cost. To overcome this limitation, our study examines a choosing-by-advantages (CBA) approach to rank seven WWT technologies for secondary WWT. CBA results were compared with results obtained by using the AHP approach. The rankings of WWT alternatives differed, depending on whether the CBA or AHP approach was used, which highlights the importance of the method used to support decision-making processes, particularly ones that rely on subjective interpretations by experts. This paper uses a holistic perspective to demonstrate the benefits of using the CBA approach to support a decision-making process when a group of experts must come to a consensus in selecting the most suitable WWT technology among several available. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

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Pound, Michael P; Atkinson, Jonathan A; Townsend, Alexandra J; Wilson, Michael H; Griffiths, Marcus; Jackson, Aaron S; Bulat, Adrian; Tzimiropoulos, Georgios; Wells, Darren M; Murchie, Erik H; Pridmore, Tony P; French, Andrew P

2017-10-01

In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, hence the motivation for finding a fully automated approach. Deep learning is an emerging field that promises unparalleled results on many data analysis problems. Building on artificial neural networks, deep approaches have many more hidden layers in the network, and hence have greater discriminative and predictive power. We demonstrate the use of such approaches as part of a plant phenotyping pipeline. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping and demonstrate state-of-the-art results (>97% accuracy) for root and shoot feature identification and localization. We use fully automated trait identification using deep learning to identify quantitative trait loci in root architecture datasets. The majority (12 out of 14) of manually identified quantitative trait loci were also discovered using our automated approach based on deep learning detection to locate plant features. We have shown deep learning-based phenotyping to have very good detection and localization accuracy in validation and testing image sets. We have shown that such features can be used to derive meaningful biological traits, which in turn can be used in quantitative trait loci discovery pipelines. This process can be completely automated. We predict a paradigm shift in image-based phenotyping bought about by such deep learning approaches, given sufficient training sets. © The Authors 2017. Published by Oxford University Press.

Transbasal versus endoscopic endonasal versus combined approaches for olfactory groove meningiomas: importance of approach selection.

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Liu, James K; Silva, Nicole A; Sevak, Ilesha A; Eloy, Jean Anderson

2018-04-01

OBJECTIVE There has been much debate regarding the optimal surgical approach for resecting olfactory groove meningiomas (OGMs). In this paper, the authors analyzed the factors involved in approach selection and reviewed the surgical outcomes in a series of OGMs. METHODS A retrospective review of 28 consecutive OGMs from a prospective database was conducted. Each tumor was treated via one of 3 approaches: transbasal approach (n = 15), pure endoscopic endonasal approach (EEA; n = 5), and combined (endoscope-assisted) transbasal-EEA (n = 8). RESULTS The mean tumor volume was greatest in the transbasal (92.02 cm 3 ) and combined (101.15 cm 3 ) groups. Both groups had significant lateral dural extension over the orbits (transbasal 73.3%, p 95%) was achieved in 20% of transbasal and 37.5% of combined cases, all due to tumor adherence to the critical neurovascular structures. The rate of CSF leakage was 0% in the transbasal and combined groups, and there was 1 leak in the EEA group (20%), resulting in an overall CSF leakage rate of 3.6%. Olfaction was preserved in 66.7% in the transbasal group. There was no significant difference in length of stay or 30-day readmission rate between the 3 groups. The mean modified Rankin Scale score was 0.79 after the transbasal approach, 2.0 after EEA, and 2.4 after the combined approach (p = 0.0604). The mean follow-up was 14.5 months (range 1-76 months). CONCLUSIONS The transbasal approach provided the best clinical outcomes with the lowest rate of complications for large tumors (> 40 mm) and for smaller tumors (OGMs invading the sinonasal cavity. Careful patient selection using an individualized, tailored strategy is important to optimize surgical outcomes.

Molecular genetics and livestock selection. Approaches, opportunities and risks

International Nuclear Information System (INIS)

Williams, J.L.

2005-01-01

Following domestication, livestock were selected both naturally through adaptation to their environments and by man so that they would fulfil a particular use. As selection methods have become more sophisticated, rapid progress has been made in improving those traits that are easily measured. However, selection has also resulted in decreased diversity. In some cases, improved breeds have replaced local breeds, risking the loss of important survival traits. The advent of molecular genetics provides the opportunity to identify the genes that control particular traits by a gene mapping approach. However, as with selection, the early mapping studies focused on traits that are easy to measure. Where molecular genetics can play a valuable role in livestock production is by providing the means to select effectively for traits that are difficult to measure. Identifying the genes underpinning particular traits requires a population in which these traits are segregating. Fortunately, several experimental populations have been created that have allowed a wide range of traits to be studied. Gene mapping work in these populations has shown that the role of particular genes in controlling variation in a given trait can depend on the genetic background. A second finding is that the most favourable alleles for a trait may in fact. be present in animals that perform poorly for the trait. In the long term, knowledge of -the genes controlling particular traits, and the way they interact with the genetic background, will allow introgression between breeds and the assembly of genotypes that are best suited to particular environments, producing animals with the desired characteristics. If used wisely, this approach will maintain genetic diversity while improving performance over a wide range of desired traits. (author)

Phenotypic and genetic characterization of Piscirickettsia salmonis from Chilean and Canadian salmonids.

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Otterlei, Alexander; Brevik, Øyvind J; Jensen, Daniel; Duesund, Henrik; Sommerset, Ingunn; Frost, Petter; Mendoza, Julio; McKenzie, Peter; Nylund, Are; Apablaza, Patricia

2016-03-15

The study presents the phenotypic and genetic characterization of selected P. salmonis isolates from Atlantic salmon and rainbow trout suffering from SRS (salmonid rickettsial septicemia) in Chile and in Canada. The phenotypic characterization of the P. salmonis isolates were based on growth on different agar media (including a newly developed medium), different growth temperatures, antibiotics susceptibility and biochemical tests. This is the first study differentiating Chilean P. salmonis isolates into two separate genetic groups. Genotyping, based on 16S rRNA-ITS and concatenated housekeeping genes grouped the selected isolates into two clades, constituted by the Chilean strains, while the Canadian isolates form a branch in the phylogenetic tree. The latter consisted of two isolates that were different in both genetic and phenotypic characteristics. The phylogenies and the MLST do not reflect the origin of the isolates with respect to host species. The isolates included were heterogeneous in phenotypic tests. The genotyping methods developed in this study provided a tool for separation of P. salmonis isolates into distinct clades. The SRS outbreaks in Chile are caused by minimum two different genetic groups of P. salmonis. This heterogeneity should be considered in future development of vaccines against this bacterium in Chile. Two different strains of P. salmonis, in regards to genetic and phenotypic characteristics, can occur in the same contemporary outbreak of SRS.

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

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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.

Multidimensionality of behavioural phenotypes in Atlantic cod, Gadus morhua.

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Meager, Justin J; Fernö, Anders; Skjæraasen, Jon Egil; Järvi, Torbjörn; Rodewald, Petra; Sverdrup, Gisle; Winberg, Svante; Mayer, Ian

2012-06-25

Much of the inter-individual variation observed in animal behaviour is now attributed to the existence of behavioural phenotypes or animal personalities. Such phenotypes may be fundamental to fisheries and aquaculture, yet there have been few detailed studies of this phenomenon in exploited marine animals. We investigated the behavioural and neuroendocrine responses of Atlantic cod (Gadus morhua L.), to situations reflecting critical ecological challenges: predator attacks and territorial challenges. Both hatchery-reared and wild fish were tested and behavioural profiles were compared with baseline conditions. We then used an objective, multivariate approach, rather than assigning individuals along one-dimensional behavioural axes, to examine whether distinct behavioural phenotypes were present. Our results indicate that two distinct behavioural phenotypes were evident in fish from each background. In hatchery-reared fish, phenotypes displayed divergent locomotor activity, sheltering, brain monoamine concentrations and responses to competitive challenges. In wild fish, phenotypes were distinguished primarily by locomotor activity, sheltering and responsiveness to predator stimuli. Hatcheries presumably represent a more stressful social environment, and social behaviour and neuroendocrine responses were important in discerning behavioural phenotypes in hatchery fish, whereas antipredator responses were important in discerning phenotypes in wild fish that have previously encountered predators. In both fish types, behavioural and physiological traits that classified individuals into phenotypes were not the same as those that were correlated across situations. These results highlight the multidimensionality of animal personalities, and that the processes that regulate one suite of behavioural traits may be very different to the processes that regulate other behaviours. Copyright © 2012 Elsevier Inc. All rights reserved.

Optimizing the phenotyping of rodent ASD models: enrichment analysis of mouse and human neurobiological phenotypes associated with high-risk autism genes identifies morphological, electrophysiological, neurological, and behavioral features

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Buxbaum Joseph D

2012-02-01

Full Text Available Abstract Background There is interest in defining mouse neurobiological phenotypes useful for studying autism spectrum disorders (ASD in both forward and reverse genetic approaches. A recurrent focus has been on high-order behavioral analyses, including learning and memory paradigms and social paradigms. However, well-studied mouse models, including for example Fmr1 knockout mice, do not show dramatic deficits in such high-order phenotypes, raising a question as to what constitutes useful phenotypes in ASD models. Methods To address this, we made use of a list of 112 disease genes etiologically involved in ASD to survey, on a large scale and with unbiased methods as well as expert review, phenotypes associated with a targeted disruption of these genes in mice, using the Mammalian Phenotype Ontology database. In addition, we compared the results with similar analyses for human phenotypes. Findings We observed four classes of neurobiological phenotypes associated with disruption of a large proportion of ASD genes, including: (1 Changes in brain and neuronal morphology; (2 electrophysiological changes; (3 neurological changes; and (4 higher-order behavioral changes. Alterations in brain and neuronal morphology represent quantitative measures that can be more widely adopted in models of ASD to understand cellular and network changes. Interestingly, the electrophysiological changes differed across different genes, indicating that excitation/inhibition imbalance hypotheses for ASD would either have to be so non-specific as to be not falsifiable, or, if specific, would not be supported by the data. Finally, it was significant that in analyses of both mouse and human databases, many of the behavioral alterations were neurological changes, encompassing sensory alterations, motor abnormalities, and seizures, as opposed to higher-order behavioral changes in learning and memory and social behavior paradigms. Conclusions The results indicated that mutations

Quantum mechanics new approaches to selected topics

CERN Document Server

Lipkin, Harry Jeannot

1973-01-01

Acclaimed as ""excellent"" (Nature) and ""very original and refreshing"" (Physics Today), this collection of self-contained studies is geared toward advanced undergraduates and graduate students. Its broad selection of topics includes the Mössbauer effect, many-body quantum mechanics, scattering theory, Feynman diagrams, and relativistic quantum mechanics.Author Harry J. Lipkin, a well-known teacher at Israel's Weizmann Institute, takes an unusual approach by introducing many interesting physical problems and mathematical techniques at a much earlier point than in conventional texts. This meth

Association of haptoglobin phenotypes with susceptibility to Falciparum Malaria in Sudan

International Nuclear Information System (INIS)

Elagib, Atif Abdel Rahman

1999-09-01

The predisposing factors for the development of serious and diverse complications caused by falciparum are not very well understood. The search for host molecular markers which the disease presentation and prognosis, is an important issue in malaria research. Along this time line, the haptoglobin phenotype of Sudanese individuals infected with falciparum malaria both complicated and non-complicated, and non-infected controls, from randomly selected individuals were determined. Anti-human Haptoglobin antibodies was radiolabelled with 125 I , using chloramine T-method.Haptoglobin phenotype determination was performed by electrophoresis separation of sera on polyacrylamide gel followed by benzidine staining, which was shown to be time and material saving, and as sensitive as Western blotting. The distribution of the haptoglobin (1-1), (2-1) among 273 uncomplicated falicparm malaria patients, was found to be 60.8%, 29.2% and 6.9%, respectively. The distribution among 208 randomly selected individuals infected with falciparm malaria both controls, from randomly selected individuals were determined. Hyptogolobin phenotype was performed by electrophoresis separation of sera on polyacrylamide gel followed by benzidine staining, which was shown to be time and material saving, and as sensitive as Western blotting. The distribution of the haptoglobin phenotypes (1-1), (2-1) and (2-2) among 273 uncomplicated facilparum malaria patients, was found to be 60.8 % , 29.7 % and 6.9 %, respectively. The distribution among 208 randomly selected healthy controls was 26.0 %, 55.8 % and 18.3 % respectively . The results show that the number of individuals with haptoglobin phentype (1-1) is significantly higher among patients with falcilparum malaria (complicated and complicated) when compared to the controls. However, the controls showed a normal distribution of the phenotypes comparable to available data obtained from similar African populations. Consequently, we suggest that the

A direct comparison of remote sensing approaches for high-throughput phenotyping in plant breeding

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Maria Tattaris

2016-08-01

Full Text Available Remote sensing (RS of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle, with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT and a vegetation index (NDVI, to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30-100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5-1m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 x 2.4 m due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.

Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance.

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Majumdar, Arunabha; Witte, John S; Ghosh, Saurabh

2015-12-01

Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE

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

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Spanagel, Rainer

2013-01-01

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

Kin and multilevel selection in social evolution: a never-ending controversy? [version 1; referees: 4 approved

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Jos Kramer

2016-04-01

Full Text Available Kin selection and multilevel selection are two major frameworks in evolutionary biology that aim at explaining the evolution of social behaviors. However, the relationship between these two theories has been plagued by controversy for almost half a century and debates about their relevance and usefulness in explaining social evolution seem to rekindle at regular intervals. Here, we first provide a concise introduction into the kin selection and multilevel selection theories and shed light onto the roots of the controversy surrounding them. We then review two major aspects of the current debate: the presumed formal equivalency of the two theories and the question whether group selection can lead to group adaptation. We conclude by arguing that the two theories can offer complementary approaches to the study of social evolution: kin selection approaches usually focus on the identification of optimal phenotypes and thus on the endresult of a selection process, whereas multilevel selection approaches focus on the ongoing selection process itself. The two theories thus provide different perspectives that might be fruitfully combined to promote our understanding of the evolution in group-structured populations.

Strong signatures of selection in the domestic pig genome

DEFF Research Database (Denmark)

Rubin, Carl-Johan; Megens, Hendrik-Jan; Barrio, Alvaro Martinez

2012-01-01

Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that un...... to strong directional selection.......Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci...... that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig—the elongation of the back...

Model selection and inference a practical information-theoretic approach

CERN Document Server

Burnham, Kenneth P

1998-01-01

This book is unique in that it covers the philosophy of model-based data analysis and an omnibus strategy for the analysis of empirical data The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data Kullback-Leibler information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection The maximized log-likelihood function can be bias-corrected to provide an estimate of expected, relative Kullback-Leibler information This leads to Akaike's Information Criterion (AIC) and various extensions and these are relatively simple and easy to use in practice, but little taught in statistics classes and far less understood in the applied sciences than should be the case The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are ...

A Grey Fuzzy Logic Approach for Cotton Fibre Selection

Science.gov (United States)

Chakraborty, Shankar; Das, Partha Protim; Kumar, Vidyapati

2017-06-01

It is a well known fact that the quality of ring spun yarn predominantly depends on various physical properties of cotton fibre. Any variation in these fibre properties may affect the strength and unevenness of the final yarn. Thus, so as to achieve the desired yarn quality and characteristics, it becomes imperative for the spinning industry personnel to identify the most suitable cotton fibre from a set of feasible alternatives in presence of several conflicting properties/attributes. This cotton fibre selection process can be modelled as a Multi-Criteria Decision Making (MCDM) problem. In this paper, a grey fuzzy logic-based approach is proposed for selection of the most apposite cotton fibre from 17 alternatives evaluated based on six important fibre properties. It is observed that the preference order of the top-ranked cotton fibres derived using the grey fuzzy logic approach closely matches with that attained by the past researchers which proves the application potentiality of this method in solving varying MCDM problems in textile industries.

High-Throughput Non-destructive Phenotyping of Traits that Contribute to Salinity Tolerance in Arabidopsis thaliana

KAUST Repository

Awlia, Mariam Sahal Abdulaziz; Nigro, Arianna; Fajkus, Jiří ; Schmoeckel, Sandra Manuela; Negrã o, Só nia; Santelia, Diana; Trtí lek, Martin; Tester, Mark A.; Julkowska, Magdalena; Panzarová , Klá ra

2016-01-01

stage, plant performance correlated with quantum yield. This integrative approach allows the simultaneous analysis of several phenotypic traits. In combination with various genetic resources, the phenotyping protocol described here is expected

Evaluation of peptide selection approaches for epitope‐based vaccine design

DEFF Research Database (Denmark)

Schubert, B.; Lund, Ole; Nielsen, Morten

2013-01-01

A major challenge in epitope-based vaccine (EV) design stems from the vast genomic variation of pathogens and the diversity of the host cellular immune system. Several computational approaches have been published to assist the selection of potential T cell epitopes for EV design. So far, no thoro......A major challenge in epitope-based vaccine (EV) design stems from the vast genomic variation of pathogens and the diversity of the host cellular immune system. Several computational approaches have been published to assist the selection of potential T cell epitopes for EV design. So far...... in terms of in silico measurements simulating important vaccine properties like the ability of inducing protection against a multivariant pathogen in a population; the predicted immunogenicity; pathogen, allele, and population coverage; as well as the conservation of selected epitopes. Additionally, we...... evaluate the use of human leukocyte antigen (HLA) supertypes with regards to their applicability for population-spanning vaccine design. The results showed that in terms of induced protection methods that simultaneously aim to optimize pathogen and HLA coverage significantly outperform methods focusing...

Distance from Africa, not climate, explains within-population phenotypic diversity in humans

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Betti, Lia; Balloux, François; Amos, William; Hanihara, Tsunehiko; Manica, Andrea

2008-01-01

The relative importance of ancient demography and climate in determining worldwide patterns of human within-population phenotypic diversity is still open to debate. Several morphometric traits have been argued to be under selection by climatic factors, but it is unclear whether climate affects the global decline in morphological diversity with increasing geographical distance from sub-Saharan Africa. Using a large database of male and female skull measurements, we apply an explicit framework to quantify the relative role of climate and distance from Africa. We show that distance from sub-Saharan Africa is the sole determinant of human within-population phenotypic diversity, while climate plays no role. By selecting the most informative set of traits, it was possible to explain over half of the worldwide variation in phenotypic diversity. These results mirror those previously obtained for genetic markers and show that ‘bones and molecules’ are in perfect agreement for humans. PMID:19129123

An integrated MCDM approach to green supplier selection

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Morteza Yazdani

2014-06-01

Full Text Available Supplier selection management has been considered as an important subject for industrial organizations. In order to remain on the market, to gain profitability and to retain competitive advantage, business units need to establish an integrated and structured supplier selection system. In addition, environmental protection problems have been big solicitudes for organizations to consider green approach in supplier selection problem. However, finding proper suppliers involves several variables and it is critically a complex process. In this paper, the main attention is focused on finding the right supplier based on fuzzy multi criteria decision making (MCDM process. The weights of criteria are calculated by analytical hierarchical process (AHP and the final ranking is achieved by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS. TOPSIS advantage among the other similar methods is to obtain the best solution close to ideal solution. The paper attempts to express better understanding by an example of an automobile manufacturing supply chain.

Phenotypes of asthma in low-income children and adolescents: cluster analysis

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Anna Lucia Barros Cabral

Full Text Available ABSTRACT Objective: Studies characterizing asthma phenotypes have predominantly included adults or have involved children and adolescents in developed countries. Therefore, their applicability in other populations, such as those of developing countries, remains indeterminate. Our objective was to determine how low-income children and adolescents with asthma in Brazil are distributed across a cluster analysis. Methods: We included 306 children and adolescents (6-18 years of age with a clinical diagnosis of asthma and under medical treatment for at least one year of follow-up. At enrollment, all the patients were clinically stable. For the cluster analysis, we selected 20 variables commonly measured in clinical practice and considered important in defining asthma phenotypes. Variables with high multicollinearity were excluded. A cluster analysis was applied using a twostep agglomerative test and log-likelihood distance measure. Results: Three clusters were defined for our population. Cluster 1 (n = 94 included subjects with normal pulmonary function, mild eosinophil inflammation, few exacerbations, later age at asthma onset, and mild atopy. Cluster 2 (n = 87 included those with normal pulmonary function, a moderate number of exacerbations, early age at asthma onset, more severe eosinophil inflammation, and moderate atopy. Cluster 3 (n = 108 included those with poor pulmonary function, frequent exacerbations, severe eosinophil inflammation, and severe atopy. Conclusions: Asthma was characterized by the presence of atopy, number of exacerbations, and lung function in low-income children and adolescents in Brazil. The many similarities with previous cluster analyses of phenotypes indicate that this approach shows good generalizability.

A Bayesian Approach to Model Selection in Hierarchical Mixtures-of-Experts Architectures.

Science.gov (United States)

Tanner, Martin A.; Peng, Fengchun; Jacobs, Robert A.

1997-03-01

There does not exist a statistical model that shows good performance on all tasks. Consequently, the model selection problem is unavoidable; investigators must decide which model is best at summarizing the data for each task of interest. This article presents an approach to the model selection problem in hierarchical mixtures-of-experts architectures. These architectures combine aspects of generalized linear models with those of finite mixture models in order to perform tasks via a recursive "divide-and-conquer" strategy. Markov chain Monte Carlo methodology is used to estimate the distribution of the architectures' parameters. One part of our approach to model selection attempts to estimate the worth of each component of an architecture so that relatively unused components can be pruned from the architecture's structure. A second part of this approach uses a Bayesian hypothesis testing procedure in order to differentiate inputs that carry useful information from nuisance inputs. Simulation results suggest that the approach presented here adheres to the dictum of Occam's razor; simple architectures that are adequate for summarizing the data are favored over more complex structures. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

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

Science.gov (United States)

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

2010-01-01

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

Selecting concepts for a concept-based curriculum: application of a benchmark approach.

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Giddens, Jean Foret; Wright, Mary; Gray, Irene

2012-09-01

In response to a transformational movement in nursing education, faculty across the country are considering changes to curricula and approaches to teaching. As a result, an emerging trend in many nursing programs is the adoption of a concept-based curriculum. As part of the curriculum development process, the selection of concepts, competencies, and exemplars on which to build courses and base content is needed. This article presents a benchmark approach used to validate and finalize concept selection among educators developing a concept-based curriculum for a statewide nursing consortium. These findings are intended to inform other nurse educators who are currently involved with or are considering this curriculum approach. Copyright 2012, SLACK Incorporated.

A novel 3D imaging system for strawberry phenotyping

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Joe Q. He

2017-11-01

Full Text Available Abstract Background Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. Results A low cost multi-view stereo (MVS imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. Conclusion This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.

A novel 3D imaging system for strawberry phenotyping.

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He, Joe Q; Harrison, Richard J; Li, Bo

2017-01-01

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.

The geometry of the Pareto front in biological phenotype space

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

2013-01-01

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

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

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

2015-11-01

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

Phenotypic and genetic diversification of Pseudanabaena spp. (cyanobacteria)

NARCIS (Netherlands)

Acinas, S.G.; Haverkamp, T.H.A.; Huisman, J.; Stal, L.J.

2009-01-01

Pseudanabaena species are poorly known filamentous bloom-forming cyanobacteria closely related to Limnothrix. We isolated 28 Pseudanabaena strains from the Baltic Sea (BS) and the Albufera de Valencia (AV; Spain). By combining phenotypic and genotypic approaches, the phylogeny, diversity and

Phenotypic differentiation is associated with gender plasticity and its responsive delay to environmental changes in Alternanthera philoxeroides--phenotypic differentiation in alligator weed.

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Wei Liu

Full Text Available Phenotypic plasticity is common in many taxa, and it may increase an organism's fitness in heterogeneous environments. However, in some cases, the frequency of environmental changes can be faster than the ability of the individual to produce new adaptive phenotypes. The importance of such a time delay in terms of individual fitness and species adaptability has not been well studied. Here, we studied gender plasticity of Alternanthera philoxeroides to address this issue through a reciprocal transplant experiment. We observed that the genders of A. philoxeroides were plastic and reversible between monoclinous and pistillody depending on habitats, the offspring maintained the maternal genders in the first year but changed from year 2 to 5, and there was a cubic relationship between the rate of population gender changes and environmental variations. This relationship indicates that the species must overcome a threshold of environmental variations to switch its developmental path ways between the two genders. This threshold and the maternal gender stability cause a significant delay of gender changes in new environments. At the same time, they result in and maintain the two distinct habitat dependent gender phenotypes. We also observed that there was a significant and adaptive life-history differentiation between monoclinous and pistillody individuals and the gender phenotypes were developmentally linked with the life-history traits. Therefore, the gender phenotypes are adaptive. Low seed production, seed germination failure and matching phenotypes to habitats by gender plasticity indicate that the adaptive phenotypic diversity in A. philoxeroides may not be the result of ecological selection, but of gender plasticity. The delay of the adaptive gender phenotype realization in changing environments can maintain the differentiation between gender systems and their associated life-history traits, which may be an important component in evolution of novel

A Novel Drug-Mouse Phenotypic Similarity Method Detects Molecular Determinants of Drug Effects.

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Jeanette Prinz

2016-09-01

Full Text Available The molecular mechanisms that translate drug treatment into beneficial and unwanted effects are largely unknown. We present here a novel approach to detect gene-drug and gene-side effect associations based on the phenotypic similarity of drugs and single gene perturbations in mice that account for the polypharmacological property of drugs. We scored the phenotypic similarity of human side effect profiles of 1,667 small molecules and biologicals to profiles of phenotypic traits of 5,384 mouse genes. The benchmarking with known relationships revealed a strong enrichment of physical and indirect drug-target connections, causative drug target-side effect links as well as gene-drug links involved in pharmacogenetic associations among phenotypically similar gene-drug pairs. The validation by in vitro assays and the experimental verification of an unknown connection between oxandrolone and prokineticin receptor 2 reinforces the ability of this method to provide new molecular insights underlying drug treatment. Thus, this approach may aid in the proposal of novel and personalized treatments.

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

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

2017-01-31

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

Adaptive evolution of molecular phenotypes

International Nuclear Information System (INIS)

Held, Torsten; Nourmohammad, Armita; Lässig, Michael

2014-01-01

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

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

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Lauren Klabonski

2016-12-01

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

Maneuvering in the Complex Path from Genotype to Phenotype

Science.gov (United States)

Strohman, Richard

2002-04-01

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. These networks range from metabolic pathways to signaling pathways that regulate hormone action. When perturbed, networks alter their output of matter and energy which, depending on the environmental context, can produce either a pathological or a normal phenotype. Study of the dynamics of these networks by approaches such as metabolic control analysis may provide new insights into the pathogenesis and treatment of complex diseases.

Modulation of B16-BL6 murine melanoma metastatic phenotype by tyrosine and phenylalanine restriction in the absence of host selection pressures.

Science.gov (United States)

Elstad, C A; Meadows, G G

1993-01-01

We previously showed that restriction of tyrosine (Tyr) and phenylalanine (Phe) in vivo dramatically suppresses the metastatic phenotype of B16-BL6 (BL6) murine melanoma. Present results indicate a direct effect of Tyr and Phe restriction on the tumor in the absence of host selection pressures. Lung colonizing ability of BL6 is dramatically suppressed after one passage in vitro in media containing low levels of Tyr and Phe. This antimetastatic effect is immediate, stable for at least 5 in vitro passages in Tyr and Phe restricted media, and evident event after levels of Tyr and Phe are restored to normal. Heterogeneity for lung colonizing ability is suppressed, as evidence by fewer tumor colonies formed by clones following i.v. inoculation into mice fed normal diet. This suppression of BL6 metastatic phenotype is not due to differential clearance and retention in the lung or to decreased growth, but is specific for these two amino acids. As the mechanism(s) for the antitumor effects of Tyr and Phe restriction are detailed, the relevance of Tyr and Phe restriction as an early adjuvant to effective cancer treatment can be explored.

Genetic approaches in comparative and evolutionary physiology

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Bridgham, Jamie T.; Kelly, Scott A.; Garland, Theodore

2015-01-01

Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology. PMID:26041111

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

Science.gov (United States)

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

2012-07-31

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

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

Science.gov (United States)

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.

Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

Directory of Open Access Journals (Sweden)

Goutam Kumar Bose

2016-01-01

Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

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

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

2017-09-01

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

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

AlShahrani, Mona; Hoehndorf, Robert

2018-01-01

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease's (or patient's) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

Semantic Disease Gene Embeddings (SmuDGE): phenotype-based disease gene prioritization without phenotypes

KAUST Repository

Alshahrani, Mona

2018-04-30

In the past years, several methods have been developed to incorporate information about phenotypes into computational disease gene prioritization methods. These methods commonly compute the similarity between a disease\\'s (or patient\\'s) phenotypes and a database of gene-to-phenotype associations to find the phenotypically most similar match. A key limitation of these methods is their reliance on knowledge about phenotypes associated with particular genes which is highly incomplete in humans as well as in many model organisms such as the mouse. Results: We developed SmuDGE, a method that uses feature learning to generate vector-based representations of phenotypes associated with an entity. SmuDGE can be used as a trainable semantic similarity measure to compare two sets of phenotypes (such as between a disease and gene, or a disease and patient). More importantly, SmuDGE can generate phenotype representations for entities that are only indirectly associated with phenotypes through an interaction network; for this purpose, SmuDGE exploits background knowledge in interaction networks comprising of multiple types of interactions. We demonstrate that SmuDGE can match or outperform semantic similarity in phenotype-based disease gene prioritization, and furthermore significantly extends the coverage of phenotype-based methods to all genes in a connected interaction network.

A Phenotypic Cell-Binding Screen Identifies a Novel Compound Targeting Triple-Negative Breast Cancer.

Science.gov (United States)

Chen, Luxi; Long, Chao; Youn, Jonghae; Lee, Jiyong

2018-06-11

We describe a "phenotypic cell-binding screen" by which therapeutic candidate targeting cancer cells of a particular phenotype can be isolated without knowledge of drug targets. Chemical library beads are incubated with cancer cells of the phenotype of interest in the presence of cancer cells lacking the phenotype of interest, and then the beads bound to only cancer cells of the phenotype of interest are selected as hits. We have applied this screening strategy in discovering a novel compound (LC129-8) targeting triple-negative breast cancer (TNBC). LC129-8 displayed highly specific binding to TNBC in cancer cell lines and patient-derived tumor tissues. LC129-8 exerted anti-TNBC activity by inducing apoptosis, inhibiting proliferation, reversing epithelial-mesenchymal transition, downregulating cancer stem cell activity and blocking in vivo tumor growth.

Analysis on endocrine and metabolic features of different phenotypes of polycystic ovary syndrome patients.

Science.gov (United States)

Li, Feng; Yao, Li; Wu, Hong; Cao, Shihong

2016-09-01

To discuss the manifestations of endocrine and metabolism for polycystic ovary syndrome patients with different phenotype. This study selected 226 cases of Rotterdam Standard diagnosed polycystic ovary syndrome patients in People's Hospital of Zhengzhou from October 2013 to February 2015. The control group was the 100 cases of non hyperandrogen menstrual women as the control group. Polycystic ovary syndrome included 4 phenotype: /or anovulatio (O) combined with hyperandrogenism (H) and polycystic ovary morphology (P), phenotype of O and P, phenotype of H and P, and phenotype of O and P. All patients were detected for the clinical endocrine and metabolism related parameters. The phenotype of O and P occupied 55.8%, it had significant difference on the comparison between control group and the luteinizing hormone (LH) and luteinizing hormone/follicle stimulating hormone (LH/FSH) of phenotype of O, H and P, phenotype of O and H and phenotype of O and P; the testosterone (T) of phenotype of O,H and P and phenotype of O and H was apparently higher than phenotype of O and P and control group; The total cholesterol (TC) and triglyceride (TG) in phenotype of O, H and P was greatly higher than phenotype of O and P and control group. The phenotype of O and P was the most common phenotype in PCOS patients. It was same for the clinical endocrine and metabolism of two classic characteristics in PCOS. Compared to other PCOS phenotype, the metabolism in phenotype of O and P was lower. The phenotype classification of PCOS patients could better guide clinical individualized treatment in patients with PCOS.

Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments.

Science.gov (United States)

Gapare, Washington; Liu, Shiming; Conaty, Warren; Zhu, Qian-Hao; Gillespie, Vanessa; Llewellyn, Danny; Stiller, Warwick; Wilson, Iain

2018-03-20

Genomic selection (GS) has successfully been used in plant breeding to improve selection efficiency and reduce breeding time and cost. However, there has not been a study to evaluate GS prediction models that may be used for predicting cotton breeding lines across multiple environments. In this study, we evaluated the performance of Bayes Ridge Regression, BayesA, BayesB, BayesC and Reproducing Kernel Hilbert Spaces regression models. We then extended the single-site GS model to accommodate genotype × environment interaction (G×E) in order to assess the merits of multi- over single-environment models in a practical breeding and selection context in cotton, a crop for which this has not previously been evaluated. Our study was based on a population of 215 upland cotton ( Gossypium hirsutum ) breeding lines which were evaluated for fiber length and strength at multiple locations in Australia and genotyped with 13,330 single nucleotide polymorphic (SNP) markers. BayesB, which assumes unique variance for each marker and a proportion of markers to have large effects, while most other markers have zero effect, was the preferred model. GS accuracy for fiber length based on a single-site model varied across sites, ranging from 0.27 to 0.77 (mean = 0.38), while that of fiber strength ranged from 0.19 to 0.58 (mean = 0.35) using randomly selected sub-populations as the training population. Prediction accuracies from the M×E model were higher than those for single-site and across-site models, with an average accuracy of 0.71 and 0.59 for fiber length and strength, respectively. The use of the M×E model could therefore identify which breeding lines have effects that are stable across environments and which ones are responsible for G×E and so reduce the amount of phenotypic screening required in cotton breeding programs to identify adaptable genotypes. Copyright © 2018, G3: Genes, Genomes, Genetics.

Multiple Natural and Experimental Inflammatory Rabbit Lacrimal Gland Phenotypes

Science.gov (United States)

Mircheff, Austin K.; Wang, Yanru; Schechter, Joel E.; Li, Meng; Tong, Warren; Attar, Mayssa; Chengalvala, Murty; Harmuth, Joe; Prusakiewicz, Jeffery J.

2016-01-01

Purpose To investigate lacrimal gland (LG) immunophysiological and immune-mediated inflammatory process (IMIP) phenotype diversity. Methods Ex vivo matured dendritic cells (mDC) were loaded with acinar cell microparticles (MP). Peripheral blood lymphocytes (PBL) were activated in mixed cell reactions with mDC and injected directly into autologous, unilateral LG (1° ATD-LG) of two rabbit cohorts, one naïve, one immunized with a LG lysate membrane fraction (Pi). Autoimmune IgG titers were assayed by ELISA, MCR PBL stimulation indices (SI) by [3H]-thymidine incorporation. Schirmer tests without and with topical anesthetic (STT-I, STT-IA) and rose Bengal (RB) staining tests were performed. H&E and immunohistochemically stained sections were examined. RNA yields and selected transcript abundances were measured. Immune cell number and transcript abundance data were submitted to Principal Component Analysis (PCA). Results Immunizing Pi dose influenced SI but not IgG titers. STT scores were decreased, and rose Bengal scores increased, by day 118 after immunization. Previous immunization exacerbated scores in 1° ATD-eyes and exacerbated 1° ATD-LG atrophy. IMIP were evident in 2° ATD-LG as well as 1° ATD-LG. PCA described diverse immunophysiological phenotypes in control LG and diverse IMIP phenotypes in ATD-LG. IgG titers and SI pre-adoptive transfer were significantly associated with certain post-adoptive transfer IMIP phenotype features, and certain LG IMIP features were significantly associated with RB and STT IA scores. Conclusions The underlying variability of normal states may contribute to the diversity of experimental IMIP phenotypes. The ability to generate and characterize diverse phenotypes may lead to phenotype-specific diagnostic and therapeutic paradigms. PMID:27423911

Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach.

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LaBelle, Denise R; Walsh, Ryan R; Banks, Sarah J

2017-08-01

Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive

Phenotypic plasticity, costs of phenotypes, and costs of plasticity

DEFF Research Database (Denmark)

Callahan, Hilary S; Maughan, Heather; Steiner, Uli

2008-01-01

Why are some traits constitutive and others inducible? The term costs often appears in work addressing this issue but may be ambiguously defined. This review distinguishes two conceptually distinct types of costs: phenotypic costs and plasticity costs. Phenotypic costs are assessed from patterns...... of covariation, typically between a focal trait and a separate trait relevant to fitness. Plasticity costs, separable from phenotypic costs, are gauged by comparing the fitness of genotypes with equivalent phenotypes within two environments but differing in plasticity and fitness. Subtleties associated with both...... types of costs are illustrated by a body of work addressing predator-induced plasticity. Such subtleties, and potential interplay between the two types of costs, have also been addressed, often in studies involving genetic model organisms. In some instances, investigators have pinpointed the mechanistic...

Antiproliferative activity and phenotypic modification induced by selected Peruvian medicinal plants on human hepatocellular carcinoma Hep3B cells.

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Carraz, Maëlle; Lavergne, Cédric; Jullian, Valérie; Wright, Michel; Gairin, Jean Edouard; Gonzales de la Cruz, Mercedes; Bourdy, Geneviève

2015-05-26

human hepatocytes in vitro. Immunofluorescence experiments on Hep3B cells showed that crude extracts of Schkuhria pinnata and Orthrosanthus chimboracensis could block Hep3B cells in mitosis with an original phenotype. Crude extracts of Perezia coerulescens, Perezia multiflora, Achyrocline alata, Ophryosporus chilca, Otholobium pubescens and Hypericum laricifolium could modify the overall microtubule cytoskeletal dynamics of Hep3B cells in interphase by an original mechanism. Our method allowed us to select 9 extracts which displayed antiproliferative activities associated with original cellular phenotypes on Hep3B cells, regarding known microtubule-targeting drugs. Both chemical and cellular studies are ongoing in order to elucidate natural compounds and cellular mechanisms responsible of the activities described. Copyright © 2015. Published by Elsevier Ireland Ltd.

A Framework for Six Sigma Project Selection in Higher Educational Institutions, Using a Weighted Scorecard Approach

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Holmes, Monica C.; Jenicke, Lawrence O.; Hempel, Jessica L.

2015-01-01

Purpose: This paper discusses the importance of the Six Sigma selection process, describes a Six Sigma project in a higher educational institution and presents a weighted scorecard approach for project selection. Design/Methodology/Approach: A case study of the Six Sigma approach being used to improve student support at a university computer help…

Social selection parapatry in Afrotropical sunbirds

DEFF Research Database (Denmark)

McEntee, Jay P.; Peñalba, Joshua V.; Werema, Chacha

2016-01-01

The extent of range overlap of incipient and recent species depends on the type and magnitude of phenotypic divergence that separates them, and the consequences of phenotypic divergence on their interactions. Signal divergence by social selection likely initiates many speciation events, but may...... yield niche-conserved lineages predisposed to limit each others’ ranges via ecological competition. Here, we examine this neglected aspect of social selection speciation theory in relation to the discovery of a nonecotonal species border between sunbirds. We find that Nectarinia moreaui and Nectarinia...... fuelleborni meet in a ∼6 km wide contact zone, as estimated by molecular cline analysis. These species exploit similar bioclimatic niches, but sing highly divergent learned songs, consistent with divergence by social selection. Cline analyses suggest that within-species stabilizing social selection on song...

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

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Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

Training set optimization under population structure in genomic selection.

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Isidro, Julio; Jannink, Jean-Luc; Akdemir, Deniz; Poland, Jesse; Heslot, Nicolas; Sorrells, Mark E

2015-01-01

Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.

Heritability of eleven metabolic phenotypes in Danish and Chinese twins

DEFF Research Database (Denmark)

Li, Shuxia; Duan, Hongmei; Pang, Zengchang

2013-01-01

modeling was performed on full and nested models with the best fitting models selected. Results: Heritability estimates were compared between Danish and Chinese samples to identify differential genetic influences on each of the phenotypes. Except for hip circumference, all other body measures exhibited...

MODERN APPROACHES TO FRACTIONAL EXHALED NITRIC OXIDE AS A USEFUL BIOMARKER FOR ALLERGIC ASTHMA PHENOTYPING AND MANAGEMENT.

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Mgaloblishvili, N; Gotua, M

2017-12-01

Asthma is a pathologically heterogeneous disease, consisting of several phenotypes. Different types of airway inflammation are the cornerstone feature of this condition. Fraction of nitric oxide in exhaled air (FENO) has been proposed as a noninvasive, specific biomarker for eosinophilic airway inflammation and has been shown to be elevated in patients with allergic asthma phenotype. More recent studies indicate that FeNO identifies T-helper cell type 2 (Th2)-mediated airway inflammation with a high predictive value for identifying inhaled corticosteroid (ICS) responsive airway inflammation. Taking into account the accumulated evidence,it is possible to consider, that FeNO testing has an important role in the assessment of patients with suspected asthma and in the management of established asthmadiagnosis. In conjunction with symptom scores and lung function tests, FeNO measurement could provide a more useful and effective approach for asthma in terms of: (1) detecting the presence of Th2-mediated airway inflammation, (2) determining the likelihood of ICS responsive (and lack of course), (3) monitoring of airway inflammation to determine risk for future impairment or loss of asthma control during reduction/cessation of ICS treatment, (4) unmasking (otherwise unsuspected) non-adherence to corticosteroid therapy and (5) in severe asthma cases tailoring treatment with biological drugs. However, more work is still needed to address outstanding questions about its exact role in guiding asthma management and better define the use of FENO in different clinical settings.

Holistic and component plant phenotyping using temporal image sequence.

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Das Choudhury, Sruti; Bashyam, Srinidhi; Qiu, Yumou; Samal, Ashok; Awada, Tala

2018-01-01

Image-based plant phenotyping facilitates the extraction of traits noninvasively by analyzing large number of plants in a relatively short period of time. It has the potential to compute advanced phenotypes by considering the whole plant as a single object (holistic phenotypes) or as individual components, i.e., leaves and the stem (component phenotypes), to investigate the biophysical characteristics of the plants. The emergence timing, total number of leaves present at any point of time and the growth of individual leaves during vegetative stage life cycle of the maize plants are significant phenotypic expressions that best contribute to assess the plant vigor. However, image-based automated solution to this novel problem is yet to be explored. A set of new holistic and component phenotypes are introduced in this paper. To compute the component phenotypes, it is essential to detect the individual leaves and the stem. Thus, the paper introduces a novel method to reliably detect the leaves and the stem of the maize plants by analyzing 2-dimensional visible light image sequences captured from the side using a graph based approach. The total number of leaves are counted and the length of each leaf is measured for all images in the sequence to monitor leaf growth. To evaluate the performance of the proposed algorithm, we introduce University of Nebraska-Lincoln Component Plant Phenotyping Dataset (UNL-CPPD) and provide ground truth to facilitate new algorithm development and uniform comparison. The temporal variation of the component phenotypes regulated by genotypes and environment (i.e., greenhouse) are experimentally demonstrated for the maize plants on UNL-CPPD. Statistical models are applied to analyze the greenhouse environment impact and demonstrate the genetic regulation of the temporal variation of the holistic phenotypes on the public dataset called Panicoid Phenomap-1. The central contribution of the paper is a novel computer vision based algorithm for

Evolution of the androgen-induced male phenotype.

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Fuxjager, Matthew J; Miles, Meredith C; Schlinger, Barney A

2018-01-01

The masculine reproductive phenotype varies significantly across vertebrates. As a result, biologists have long recognized that many of the mechanisms that support these phenotypes-particularly the androgenic system-is evolutionarily labile, and thus susceptible to the effects of selection for different traits. However, exactly how androgenic signaling systems vary in a way which results in dramatically different functional outputs, remain largely unclear. We explore this topic here by outlining four key-but non-mutually exclusive-hypotheses that propose how the mechanisms of androgenic signaling might change over time to potentiate the emergence of phenotypical variation in masculine behavior and physiology. We anchor this framework in a review of our own studies of a tropical bird called the golden-collared manakin (Manacus vitellinus), which has evolved an exaggerated acrobatic courtship display that is heavily androgen-dependent. The result is an example of how the cellular basis of androgenic action can be modified to support a unique reproductive repertoire. We end this review by highlighting a broad pathway forward to further pursue the intricate ways by which the mechanisms of hormone action evolve to support processes of adaptation and animal design.

Model-independent phenotyping of C. elegans locomotion using scale-invariant feature transform.

Directory of Open Access Journals (Sweden)

Yelena Koren

Full Text Available 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.

Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.

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Adabor, Emmanuel S; Acquaah-Mensah, George K

2017-10-16

Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 receptor status. Breast cancer lacking estrogen receptors, progesterone receptors and HER2 receptors are difficult to treat. Regarding large data repositories such as The Cancer Genome Atlas, available wet-lab methods for establishing the presence of these receptors do not always conclusively cover all available samples. To this end, we introduce median-supplement methods to identify hormonal and HER2 receptor status phenotypes of breast cancer patients using gene expression profiles. In these approaches, supplementary instances based on median patient gene expression are introduced to balance a training set from which we build simple models to identify the receptor expression status of patients. In addition, for the purpose of benchmarking, we examine major machine learning approaches that are also applicable to the problem of finding receptor status in breast cancer. We show that our methods are robust and have high sensitivity with extremely low false-positive rates compared with the well-established methods. A successful application of these methods will permit the simultaneous study of large collections of samples of breast cancer patients as well as save time and cost while standardizing interpretation of outcomes of such studies. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reduced genetic variance among high fitness individuals: inferring stabilizing selection on male sexual displays in Drosophila serrata.

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Sztepanacz, Jacqueline L; Rundle, Howard D

2012-10-01

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low- compared to high-fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high- and low-fitness individuals and was greater among the low-fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Identification of QTL for UV-protective eye area pigmentation in cattle by progeny phenotyping and genome-wide association analysis.

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Hubert Pausch

Full Text Available Pigmentation patterns allow for the differentiation of cattle breeds. A dominantly inherited white head is characteristic for animals of the Fleckvieh (FV breed. However, a minority of the FV animals exhibits peculiar pigmentation surrounding the eyes (ambilateral circumocular pigmentation, ACOP. In areas where animals are exposed to increased solar ultraviolet radiation, ACOP is associated with a reduced susceptibility to bovine ocular squamous cell carcinoma (BOSCC, eye cancer. Eye cancer is the most prevalent malignant tumour affecting cattle. Selection for animals with ACOP rapidly reduces the incidence of BOSCC. To identify quantitative trait loci (QTL underlying ACOP, we performed a genome-wide association study using 658,385 single nucleotide polymorphisms (SNPs. The study population consisted of 3579 bulls of the FV breed with a total of 320,186 progeny with phenotypes for ACOP. The proportion of progeny with ACOP was used as a quantitative trait with high heritability (h(2 = 0.79. A variance component based approach to account for population stratification uncovered twelve QTL regions on seven chromosomes. The identified QTL point to MCM6, PAX3, ERBB3, KITLG, LEF1, DKK2, KIT, CRIM1, ATRN, GSDMC, MITF and NBEAL2 as underlying genes for eye area pigmentation in cattle. The twelve QTL regions explain 44.96% of the phenotypic variance of the proportion of daughters with ACOP. The chromosomes harbouring significantly associated SNPs account for 54.13% of the phenotypic variance, while another 19.51% of the phenotypic variance is attributable to chromosomes without identified QTL. Thus, the missing heritability amounts to 7% only. Our results support a polygenic inheritance pattern of ACOP in cattle and provide the basis for efficient genomic selection of animals that are less susceptible to serious eye diseases.

Fragment-based screening in tandem with phenotypic screening provides novel antiparasitic hits.

Science.gov (United States)

Blaazer, Antoni R; Orrling, Kristina M; Shanmugham, Anitha; Jansen, Chimed; Maes, Louis; Edink, Ewald; Sterk, Geert Jan; Siderius, Marco; England, Paul; Bailey, David; de Esch, Iwan J P; Leurs, Rob

2015-01-01

Methods to discover biologically active small molecules include target-based and phenotypic screening approaches. One of the main difficulties in drug discovery is elucidating and exploiting the relationship between drug activity at the protein target and disease modification, a phenotypic endpoint. Fragment-based drug discovery is a target-based approach that typically involves the screening of a relatively small number of fragment-like (molecular weight <300) molecules that efficiently cover chemical space. Here, we report a fragment screening on TbrPDEB1, an essential cyclic nucleotide phosphodiesterase (PDE) from Trypanosoma brucei, and human PDE4D, an off-target, in a workflow in which fragment hits and a series of close analogs are subsequently screened for antiparasitic activity in a phenotypic panel. The phenotypic panel contained T. brucei, Trypanosoma cruzi, Leishmania infantum, and Plasmodium falciparum, the causative agents of human African trypanosomiasis (sleeping sickness), Chagas disease, leishmaniasis, and malaria, respectively, as well as MRC-5 human lung cells. This hybrid screening workflow has resulted in the discovery of various benzhydryl ethers with antiprotozoal activity and low toxicity, representing interesting starting points for further antiparasitic optimization. © 2014 Society for Laboratory Automation and Screening.

How can we estimate natural selection on endocrine traits? Lessons from evolutionary biology.

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Bonier, Frances; Martin, Paul R

2016-11-30

An evolutionary perspective can enrich almost any endeavour in biology, providing a deeper understanding of the variation we see in nature. To this end, evolutionary endocrinologists seek to describe the fitness consequences of variation in endocrine traits. Much of the recent work in our field, however, follows a flawed approach to the study of how selection shapes endocrine traits. Briefly, this approach relies on among-individual correlations between endocrine phenotypes (often circulating hormone levels) and fitness metrics to estimate selection on those endocrine traits. Adaptive plasticity in both endocrine and fitness-related traits can drive these correlations, generating patterns that do not accurately reflect natural selection. We illustrate why this approach to studying selection on endocrine traits is problematic, referring to work from evolutionary biologists who, decades ago, described this problem as it relates to a variety of other plastic traits. We extend these arguments to evolutionary endocrinology, where the likelihood that this flaw generates bias in estimates of selection is unusually high due to the exceptional responsiveness of hormones to environmental conditions, and their function to induce adaptive life-history responses to environmental variation. We end with a review of productive approaches for investigating the fitness consequences of variation in endocrine traits that we expect will generate exciting advances in our understanding of endocrine system evolution. © 2016 The Author(s).

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

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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

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

Directory of Open Access Journals (Sweden)

Samuel Sunghwan Cho

Full Text Available 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

Genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah

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Ellen Grippi Lira

Full Text Available ABSTRACT: Sunflower (Helianthus annuus L. is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD, days to start flowering (DFL based on flowering date in R5, chapter length (CL, weight of a thousand achenes (WTA, plant height (H and oil content (OilC of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.

Natural selection on immune defense: A field experiment.

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Langeloh, Laura; Behrmann-Godel, Jasminca; Seppälä, Otto

2017-02-01

Predicting the evolution of phenotypic traits requires an understanding of natural selection on them. Despite its indispensability in the fight against parasites, selection on host immune defense has remained understudied. Theory predicts immune traits to be under stabilizing selection due to associated trade-offs with other fitness-related traits. Empirical studies, however, report mainly positive directional selection. This discrepancy could be caused by low phenotypic variation in the examined individuals and/or variation in host resource level that confounds trade-offs in empirical studies. In a field experiment where we maintained Lymnaea stagnalis snails individually in cages in a lake, we investigated phenotypic selection on two immune defense traits, phenoloxidase (PO)-like activity and antibacterial activity, in hemolymph. We used a diverse laboratory population and manipulated snail resource level by limiting their food supply. For six weeks, we followed immune activity, growth, and two fitness components, survival and fecundity of snails. We found that PO-like activity and growth were under stabilizing selection, while antibacterial activity was under positive directional selection. Selection on immune traits was mainly driven by variation in survival. The form of selection on immune defense apparently depends on the particular trait, possibly due to its importance for countering the present parasite community. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

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

KAUST Repository

Hoehndorf, Robert

2016-11-14

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

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

Science.gov (United States)

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

2016-11-14

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

Phenotype- and genotype-specific structural alterations in spasmodic dysphonia.

Science.gov (United States)

Bianchi, Serena; Battistella, Giovanni; Huddleston, Hailey; Scharf, Rebecca; Fleysher, Lazar; Rumbach, Anna F; Frucht, Steven J; Blitzer, Andrew; Ozelius, Laurie J; Simonyan, Kristina

2017-04-01

Spasmodic dysphonia is a focal dystonia characterized by involuntary spasms in the laryngeal muscles that occur selectively during speaking. Although hereditary trends have been reported in up to 16% of patients, the causative etiology of spasmodic dysphonia is unclear, and the influences of various phenotypes and genotypes on disorder pathophysiology are poorly understood. In this study, we examined structural alterations in cortical gray matter and white matter integrity in relationship to different phenotypes and putative genotypes of spasmodic dysphonia to elucidate the structural component of its complex pathophysiology. Eighty-nine patients with spasmodic dysphonia underwent high-resolution magnetic resonance imaging and diffusion-weighted imaging to examine cortical thickness and white matter fractional anisotropy in adductor versus abductor forms (distinct phenotypes) and in sporadic versus familial cases (distinct genotypes). Phenotype-specific abnormalities were localized in the left sensorimotor cortex and angular gyrus and the white matter bundle of the right superior corona radiata. Genotype-specific alterations were found in the left superior temporal gyrus, supplementary motor area, and the arcuate portion of the left superior longitudinal fasciculus. Our findings suggest that phenotypic differences in spasmodic dysphonia arise at the level of the primary and associative areas of motor control, whereas genotype-related pathophysiological mechanisms may be associated with dysfunction of regions regulating phonological and sensory processing. Identification of structural alterations specific to disorder phenotype and putative genotype provides an important step toward future delineation of imaging markers and potential targets for novel therapeutic interventions for spasmodic dysphonia. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Does the phenotypic selection affect the genetic structure and diversity? A study case on Walnut in eastern central Italy (the region of Marche

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Fulvio Ducci

2009-12-01

genetic variation of Marche’s population, compared to a reference system of 7 other Italian provenances, was used as a base to establish a possible improvement strategy together with basic guidelines to manage those genetic resources. Indeed, the very important individual component of the genetic variation suggested to select directly superior phenotypes in view of establishing a comparative multisite progeny test network. No substantial differences were detected concerning the genetic structure of the Italian population, neither within the Marche population, neither in the phenotypically selected material. Homozygosity was always high, probably due to genetic erosion, isolation and adaptation to extreme conditions. Given this general situation in the Marche area, a special care should be payed in the management of walnut reproductive materials, in order to maintain sufficient levels of variation in plantations.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

Science.gov (United States)

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

Targets of balancing selection in the human genome

DEFF Research Database (Denmark)

Andrés, Aida M; Hubisz, Melissa J; Indap, Amit

2009-01-01

Balancing selection is potentially an important biological force for maintaining advantageous genetic diversity in populations, including variation that is responsible for long-term adaptation to the environment. By serving as a means to maintain genetic variation, it may be particularly relevant...... to maintaining phenotypic variation in natural populations. Nevertheless, its prevalence and specific targets in the human genome remain largely unknown. We have analyzed the patterns of diversity and divergence of 13,400 genes in two human populations using an unbiased single-nucleotide polymorphism data set......, a genome-wide approach, and a method that incorporates demography in neutrality tests. We identified an unbiased catalog of genes with signatures of long-term balancing selection, which includes immunity genes as well as genes encoding keratins and membrane channels; the catalog also shows enrichment...

Heterozygote advantage: the effect of artificial selection in livestock and pets.

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Hedrick, Philip W

2015-01-01

There are a number of mutants in livestock and pets that have a heterozygote advantage because of artificial selection for these mutants in heterozygotes and strong detrimental effects from natural selection in homozygotes. In livestock, these mutants include ones that influence milk yield in dairy cattle, fecundity in sheep, litter size in pigs, muscling in beef cattle, color in horses, lean meat content in pigs, and comb morphology in chickens. In pets, these mutants include ones that influence tail length in cats and hairlessness, muscling, color, or ridgeback hair in dogs. A large variety of mutants are responsible, including small or large deletions or insertions and single base-pair nonsynonymous changes. Many of the mutants cause loss of function for the genes involved, a change that results in the pleiotropic effects of a desired phenotype in heterozygotes and low fitness or an undesirable phenotype in mutant homozygotes. I examine how selection changes the frequency of these mutants and provide an approach to estimate the amount of artificial selection that is necessary to maintain these mutants at the high frequencies often observed. The amount of artificial selection ranges from low selection favoring heterozygotes for double muscling in whippet dogs to very strong selection favoring the "flash" (part white, part solid) heterozygote in boxer dogs and the rose comb in chickens. In several examples (rose comb in Wyandotte chickens and the hair ridge in Rhodesian ridgeback dogs), there is actually stronger selection for the mutant than against it, making the frequency of the mutant greater than 50%. © The American Genetic Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Optimal Subinterval Selection Approach for Power System Transient Stability Simulation

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Soobae Kim

2015-10-01

Full Text Available Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. The performance of the proposed method is demonstrated with the GSO 37-bus system.

Simulation Experiment on Landing Site Selection Using a Simple Geometric Approach

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Zhao, W.; Tong, X.; Xie, H.; Jin, Y.; Liu, S.; Wu, D.; Liu, X.; Guo, L.; Zhou, Q.

2017-07-01

Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance) could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses). So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.

SIMULATION EXPERIMENT ON LANDING SITE SELECTION USING A SIMPLE GEOMETRIC APPROACH

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W. Zhao

2017-07-01

Full Text Available Safe landing is an important part of the planetary exploration mission. Even fine scale terrain hazards (such as rocks, small craters, steep slopes, which would not be accurately detected from orbital reconnaissance could also pose a serious risk on planetary lander or rover and scientific instruments on-board it. In this paper, a simple geometric approach on planetary landing hazard detection and safe landing site selection is proposed. In order to achieve full implementation of this algorithm, two easy-to-compute metrics are presented for extracting the terrain slope and roughness information. Unlike conventional methods which must do the robust plane fitting and elevation interpolation for DEM generation, in this work, hazards is identified through the processing directly on LiDAR point cloud. For safe landing site selection, a Generalized Voronoi Diagram is constructed. Based on the idea of maximum empty circle, the safest landing site can be determined. In this algorithm, hazards are treated as general polygons, without special simplification (e.g. regarding hazards as discrete circles or ellipses. So using the aforementioned method to process hazards is more conforming to the real planetary exploration scenario. For validating the approach mentioned above, a simulated planetary terrain model was constructed using volcanic ash with rocks in indoor environment. A commercial laser scanner mounted on a rail was used to scan the terrain surface at different hanging positions. The results demonstrate that fairly hazard detection capability and reasonable site selection was obtained compared with conventional method, yet less computational time and less memory usage was consumed. Hence, it is a feasible candidate approach for future precision landing selection on planetary surface.

Secular change in 13 metabolic phenotypes: A Chinese longitudinal twin study

DEFF Research Database (Denmark)

Li, Shuxia; Pang, Zengchang; Zhang, Dongfeng

in prospective investigations. Based on Chinese twin data collected from Danish-Chinese collaboration research, we perform twin modeling on 13 metabolic phenotypes (total cholesterol; triglyceride; high density lipoprotein (HDL); low density lipoprotein (LDL); urine acid (UA); glucose; weight; body mass index...... fitted to the secular changes in each of the 13 phenotypes with best fitting model selected based on model performance. Age and sex were included as covariates in the models to adjust for their effects on secular trend. Results: Variations in secular change in 3 lipids (total cholesterol; triglyceride...

Thoughts on the behavioural phenotypes in Prader-Willi syndrome and velo-cardio-facial syndrome: A novel approach

NARCIS (Netherlands)

Verhoeven, W.M.A.; Egger, J.I.M.; Tuinier, S.

2007-01-01

In both Prader-Willi syndrome (PWS) and 22q11 deletion syndrome [velo-cardio-facial syndrome (VCFS)], an increased risk for psychotic disorders is reported, which are as a rule not included in the behavioural phenotype of these two syndromes. For the description of a behavioural phenotype, the

Quantitative Framework and Management Expectation Tool for the Selection of Bioremediation Approaches at Chlorinated Solvent Sites

Science.gov (United States)

2015-03-19

Bioremediation Approaches at Chlorinated Solvent Sites March 19, 2015 SERDP & ESTCP Webinar Series (#11) SERDP & ESTCP Webinar Series Welcome and...Expectation Tool for the Selection of Bioremediation Approaches at Chlorinated Solvent Sites Ms. Carmen Lebrón, Independent Consultant (20 minutes + Q&A) Dr...ESTCP Webinar Series Quantitative Framework and Management Expectation Tool for the Selection of Bioremediation Approaches at Chlorinated

Genomic selection: genome-wide prediction in plant improvement.

Science.gov (United States)

Desta, Zeratsion Abera; Ortiz, Rodomiro

2014-09-01

Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Potential Approach for Low Flow Selection in Water Resource Supply and Management

Science.gov (United States)

Ying Ouyang

2012-01-01

Low flow selections are essential to water resource management, water supply planning, and watershed ecosystem restoration. In this study, a new approach, namely the frequent-low (FL) approach (or frequent-low index), was developed based on the minimum frequent-low flow or level used in minimum flows and/or levels program in northeast Florida, USA. This FL approach was...

An intutionistic fuzzy optimization approach to vendor selection problem

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Prabjot Kaur

2016-09-01

Full Text Available Selecting the right vendor is an important business decision made by any organization. The decision involves multiple criteria and if the objectives vary in preference and scope, then nature of decision becomes multiobjective. In this paper, a vendor selection problem has been formulated as an intutionistic fuzzy multiobjective optimization where appropriate number of vendors is to be selected and order allocated to them. The multiobjective problem includes three objectives: minimizing the net price, maximizing the quality, and maximizing the on time deliveries subject to supplier's constraints. The objection function and the demand are treated as intutionistic fuzzy sets. An intutionistic fuzzy set has its ability to handle uncertainty with additional degrees of freedom. The Intutionistic fuzzy optimization (IFO problem is converted into a crisp linear form and solved using optimization software Tora. The advantage of IFO is that they give better results than fuzzy/crisp optimization. The proposed approach is explained by a numerical example.

Label-free identification of macrophage phenotype by fluorescence lifetime imaging microscopy

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Alfonso-García, Alba; Smith, Tim D.; Datta, Rupsa; Luu, Thuy U.; Gratton, Enrico; Potma, Eric O.; Liu, Wendy F.

2016-04-01

Macrophages adopt a variety of phenotypes that are a reflection of the many functions they perform as part of the immune system. In particular, metabolism is a phenotypic trait that differs between classically activated, proinflammatory macrophages, and alternatively activated, prohealing macrophages. Inflammatory macrophages have a metabolism based on glycolysis while alternatively activated macrophages generally rely on oxidative phosphorylation to generate chemical energy. We employ this shift in metabolism as an endogenous marker to identify the phenotype of individual macrophages via live-cell fluorescence lifetime imaging microscopy (FLIM). We demonstrate that polarized macrophages can be readily discriminated with the aid of a phasor approach to FLIM, which provides a fast and model-free method for analyzing fluorescence lifetime images.

Multi-dimensional discovery of biomarker and phenotype complexes

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Huang Kun

2010-10-01

Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

Directional selection causes decanalization in a group I ribozyme.

Science.gov (United States)

Hayden, Eric J; Weikert, Christian; Wagner, Andreas

2012-01-01

A canalized genotype is robust to environmental or genetic perturbations. Canalization is expected to result from stabilizing selection on a well-adapted phenotype. Decanalization, the loss of robustness, might follow periods of directional selection toward a new optimum. The evolutionary forces causing decanalization are still unknown, in part because it is difficult to determine the fitness effects of mutations in populations of organisms with complex genotypes and phenotypes. Here, we report direct experimental measurements of robustness in a system with a simple genotype and phenotype, the catalytic activity of an RNA enzyme. We find that the robustness of a population of RNA enzymes decreases during a period of directional selection in the laboratory. The decrease in robustness is primarily caused by the selective sweep of a genotype that is decanalized relative to the wild-type, both in terms of mutational robustness and environmental robustness (thermodynamic stability). Our results experimentally demonstrate that directional selection can cause decanalization on short time scales, and demonstrate co-evolution of mutational and environmental robustness.

A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain.

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Umoh, Mfon E; Dammer, Eric B; Dai, Jingting; Duong, Duc M; Lah, James J; Levey, Allan I; Gearing, Marla; Glass, Jonathan D; Seyfried, Nicholas T

2018-01-01

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry-based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD Our systems-level analysis of the brain proteome integrated both differential expression and co-expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co-expression network analysis revealed 15 modules of co-expressed proteins, eight of which were significantly different across the ALS-FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell-type specificity that showed correlation with TDP-43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP-43 protein-protein interactions, revealing one module enriched with RNA-binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems-level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS-FTD disease spectrum in human brain. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Genome Scan for Selection in Structured Layer Chicken Populations Exploiting Linkage Disequilibrium Information.

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Mahmood Gholami

Full Text Available An increasing interest is being placed in the detection of genes, or genomic regions, that have been targeted by selection because identifying signatures of selection can lead to a better understanding of genotype-phenotype relationships. A common strategy for the detection of selection signatures is to compare samples from distinct populations and to search for genomic regions with outstanding genetic differentiation. The aim of this study was to detect selective signatures in layer chicken populations using a recently proposed approach, hapFLK, which exploits linkage disequilibrium information while accounting appropriately for the hierarchical structure of populations. We performed the analysis on 70 individuals from three commercial layer breeds (White Leghorn, White Rock and Rhode Island Red, genotyped for approximately 1 million SNPs. We found a total of 41 and 107 regions with outstanding differentiation or similarity using hapFLK and its single SNP counterpart FLK respectively. Annotation of selection signature regions revealed various genes and QTL corresponding to productions traits, for which layer breeds were selected. A number of the detected genes were associated with growth and carcass traits, including IGF-1R, AGRP and STAT5B. We also annotated an interesting gene associated with the dark brown feather color mutational phenotype in chickens (SOX10. We compared FST, FLK and hapFLK and demonstrated that exploiting linkage disequilibrium information and accounting for hierarchical population structure decreased the false detection rate.

An Examination of HR Strategic Recruitment and Selection Approaches in China

OpenAIRE

Zhou, Guozhen

2006-01-01

Abstract In the past two decades, the manner in which organisations in the People's Republic of China (PRC) managed their human resources has changed dramatically (Braun and Warner, 2002). As the economy grows and moves into higher value-added work, strategic recruitment and selection are vital to an organisation's success. This dissertation seeks to examine the recruitment and selection strategy approaches in China. This research is based on 15 well-known firms, of which 11 are multinati...

Convergent evolution and divergent selection: lizards at the White Sands ecotone.

Science.gov (United States)

Rosenblum, Erica Bree

2006-01-01

Ecological transition zones, where organismal phenotypes result from a delicate balance between selection and migration, highlight the interplay of local adaptation and gene flow. Here, I study the response of an entire species assemblage to natural selection across a common ecotone. Three lizard species, distributed along a dramatic environmental gradient in substrate color, display convergent adaptation of blanched coloration on the gypsum dunes of White Sands National Monument. I investigate the role of gene flow in modulating phenotypic response to selection by quantifying color variation and genetic variation across the ecotone. I find species differences in degree of background matching and in genetic connectivity of populations across the ecotone. Differences among species in phenotypic response to selection scale precisely to levels of genetic isolation. Species with higher levels of gene flow across the ecotone exhibit less dramatic responses to selection. Results also reveal a strong signal of ecologically mediated divergence for White Sands lizards. For all species, phenotypic variation is better explained by habitat similarity than genetic similarity. Convergent evolution of blanched coloration at White Sands clearly reflects the action of strong divergent selection; however, adaptive response appears to be modulated by gene flow and demographic history and can be predicted by divergence-with-gene-flow models.

Classic selective sweeps revealed by massive sequencing in cattle.

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Saber Qanbari

2014-02-01

Full Text Available Human driven selection during domestication and subsequent breed formation has likely left detectable signatures within the genome of modern cattle. The elucidation of these signatures of selection is of interest from the perspective of evolutionary biology, and for identifying domestication-related genes that ultimately may help to further genetically improve this economically important animal. To this end, we employed a panel of more than 15 million autosomal SNPs identified from re-sequencing of 43 Fleckvieh animals. We mainly applied two somewhat complementary statistics, the integrated Haplotype Homozygosity Score (iHS reflecting primarily ongoing selection, and the Composite of Likelihood Ratio (CLR having the most power to detect completed selection after fixation of the advantageous allele. We find 106 candidate selection regions, many of which are harboring genes related to phenotypes relevant in domestication, such as coat coloring pattern, neurobehavioral functioning and sensory perception including KIT, MITF, MC1R, NRG4, Erbb4, TMEM132D and TAS2R16, among others. To further investigate the relationship between genes with signatures of selection and genes identified in QTL mapping studies, we use a sample of 3062 animals to perform four genome-wide association analyses using appearance traits, body size and somatic cell count. We show that regions associated with coat coloring significantly (P<0.0001 overlap with the candidate selection regions, suggesting that the selection signals we identify are associated with traits known to be affected by selection during domestication. Results also provide further evidence regarding the complexity of the genetics underlying coat coloring in cattle. This study illustrates the potential of population genetic approaches for identifying genomic regions affecting domestication-related phenotypes and further helps to identify specific regions targeted by selection during speciation, domestication and

Improvement of neuromuscular synaptic phenotypes without enhanced survival and motor function in severe spinal muscular atrophy mice selectively rescued in motor neurons.

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Ximena Paez-Colasante

Full Text Available In the inherited childhood neuromuscular disease spinal muscular atrophy (SMA, lower motor neuron death and severe muscle weakness result from the reduction of the ubiquitously expressed protein survival of motor neuron (SMN. Although SMA mice recapitulate many features of the human disease, it has remained unclear if their short lifespan and motor weakness are primarily due to cell-autonomous defects in motor neurons. Using Hb9(Cre as a driver, we selectively raised SMN expression in motor neurons in conditional SMAΔ7 mice. Unlike a previous study that used choline acetyltransferase (ChAT(Cre+ as a driver on the same mice, and another report that used Hb9(Cre as a driver on a different line of conditional SMA mice, we found no improvement in survival, weight, motor behavior and presynaptic neurofilament accumulation. However, like in ChAT(Cre+ mice, we detected rescue of endplate size and mitigation of neuromuscular junction (NMJ denervation status. The rescue of endplate size occurred in the absence of an increase in myofiber size, suggesting endplate size is determined by the motor neuron in these animals. Real time-PCR showed that the expression of spinal cord SMN transcript was sharply reduced in Hb9(Cre+ SMA mice relative to ChAT(Cre+ SMA mice. This suggests that our lack of overall phenotypic improvement is most likely due to an unexpectedly poor recombination efficiency driven by Hb9(Cre . Nonetheless, the low levels of SMN were sufficient to rescue two NMJ structural parameters indicating that these motor neuron cell autonomous phenotypes are very sensitive to changes in motoneuronal SMN levels. Our results directly suggest that even those therapeutic interventions with very modest effects in raising SMN in motor neurons may provide mitigation of neuromuscular phenotypes in SMA patients.

A genome scan for positive selection in thoroughbred horses.

Science.gov (United States)

Gu, Jingjing; Orr, Nick; Park, Stephen D; Katz, Lisa M; Sulimova, Galina; MacHugh, David E; Hill, Emmeline W

2009-06-02

Thoroughbred horses have been selected for exceptional racing performance resulting in system-wide structural and functional adaptations contributing to elite athletic phenotypes. Because selection has been recent and intense in a closed population that stems from a small number of founder animals Thoroughbreds represent a unique population within which to identify genomic contributions to exercise-related traits. Employing a population genetics-based hitchhiking mapping approach we performed a genome scan using 394 autosomal and X chromosome microsatellite loci and identified positively selected loci in the extreme tail-ends of the empirical distributions for (1) deviations from expected heterozygosity (Ewens-Watterson test) in Thoroughbred (n = 112) and (2) global differentiation among four geographically diverse horse populations (F(ST)). We found positively selected genomic regions in Thoroughbred enriched for phosphoinositide-mediated signalling (3.2-fold enrichment; PThoroughbred athletic phenotype. We report for the first time candidate athletic-performance genes within regions targeted by selection in Thoroughbred horses that are principally responsible for fatty acid oxidation, increased insulin sensitivity and muscle strength: ACSS1 (acyl-CoA synthetase short-chain family member 1), ACTA1 (actin, alpha 1, skeletal muscle), ACTN2 (actinin, alpha 2), ADHFE1 (alcohol dehydrogenase, iron containing, 1), MTFR1 (mitochondrial fission regulator 1), PDK4 (pyruvate dehydrogenase kinase, isozyme 4) and TNC (tenascin C). Understanding the genetic basis for exercise adaptation will be crucial for the identification of genes within the complex molecular networks underlying obesity and its consequential pathologies, such as type 2 diabetes. Therefore, we propose Thoroughbred as a novel in vivo large animal model for understanding molecular protection against metabolic disease.

Multiparametric classification links tumor microenvironments with tumor cell phenotype.

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Bojana Gligorijevic

2014-11-01

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

Phenotyping for drought tolerance of crops in the genomics era

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Roberto eTuberosa

2012-09-01

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

Cognitive Phenotypes and the Evolution of Animal Decisions.

Science.gov (United States)

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

2016-11-01

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

Standing genetic variation as a major contributor to adaptation in the Virginia chicken lines selection experiment.

Science.gov (United States)

Sheng, Zheya; Pettersson, Mats E; Honaker, Christa F; Siegel, Paul B; Carlborg, Örjan

2015-10-01

Artificial selection provides a powerful approach to study the genetics of adaptation. Using selective-sweep mapping, it is possible to identify genomic regions where allele-frequencies have diverged during selection. To avoid false positive signatures of selection, it is necessary to show that a sweep affects a selected trait before it can be considered adaptive. Here, we confirm candidate, genome-wide distributed selective sweeps originating from the standing genetic variation in a long-term selection experiment on high and low body weight of chickens. Using an intercross between the two divergent chicken lines, 16 adaptive selective sweeps were confirmed based on their association with the body weight at 56 days of age. Although individual additive effects were small, the fixation for alternative alleles across the loci contributed at least 40 % of the phenotypic difference for the selected trait between these lines. The sweeps contributed about half of the additive genetic variance present within and between the lines after 40 generations of selection, corresponding to a considerable portion of the additive genetic variance of the base population. Long-term, single-trait, bi-directional selection in the Virginia chicken lines has resulted in a gradual response to selection for extreme phenotypes without a drastic reduction in the genetic variation. We find that fixation of several standing genetic variants across a highly polygenic genetic architecture made a considerable contribution to long-term selection response. This provides new fundamental insights into the dynamics of standing genetic variation during long-term selection and adaptation.

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

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Thirunavukkarasu Nepolean

2017-04-01

Full Text Available Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis. Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

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

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Yook Karen

2011-01-01

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

Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.

Science.gov (United States)

Harder, Nathalie; Mora-Bermúdez, Felipe; Godinez, William J; Wünsche, Annelie; Eils, Roland; Ellenberg, Jan; Rohr, Karl

2009-11-01

Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.

Dental management of amelogenesis imperfecta patients: a primer on genotype-phenotype correlations.

Science.gov (United States)

Ng, F K; Messer, L B

2009-01-01

Amelogenesis imperfecta (AI) represents a group of hereditary conditions which affects enamel formation in the primary and permanent dentitions. Mutations in genes critical for amelogenesis result in diverse phenotypes characterized by variably thin and/or defective enamel. To date, mutations in 5 genes are known to cause AI in humans. Understanding the molecular etiologies and associated inheritance patterns can assist in the early diagnosis of this condition. Recognition of genotype-phenotype correlations will allow clinicians to guide genetic testing and select appropriate management strategies for patients who express different phenotypes. The purpose of this paper was to provide a narrative review of the current literature on amelogenesis imperfecta, particularly regarding recent advances in the identification of candidate genes and the patterns of inheritance.

Evidence of directional and stabilizing selection in contemporary humans.

Science.gov (United States)

Sanjak, Jaleal S; Sidorenko, Julia; Robinson, Matthew R; Thornton, Kevin R; Visscher, Peter M

2018-01-02

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

A semiparametric graphical modelling approach for large-scale equity selection.

Science.gov (United States)

Liu, Han; Mulvey, John; Zhao, Tianqi

2016-01-01

We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to select stocks that are as independent as possible. The proposed elliptical-copula graphical model has a latent Gaussian representation; its structure can be effectively inferred using the regularized rank-based estimators. The resulting algorithm is computationally efficient and scales to large data-sets. To show the efficacy of the proposed method, we apply it to conduct equity selection based on a 16-year health care stock data-set and a large 34-year stock data-set. Empirical tests show that the proposed method is superior to alternative strategies including a principal component analysis-based approach and the classical Markowitz strategy based on the traditional buy-and-hold assumption.

Comparative Analysis of Selected Factors Affecting Fruit Phenotype ...

African Journals Online (AJOL)

type of subspecies and probably pollination intensity but not with farmers' selection pressure and intervention. ..... fruit properties usually in complex interactions, needing long ..... Dixon, G.O., (2004). Cassava breeding: opportunities and challenges. Plant. Molecular ... Journal of Ecology, 83, pp. ... Evolution, 40, pp. 117-128 ...

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1 that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons.

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

Science.gov (United States)

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

2016-02-24

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

Testing local host adaptation and phenotypic plasticity in a herbivore when alternative related host plants occur sympatrically.

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Lorena Ruiz-Montoya

Full Text Available Host race formation in phytophagous insects can be an early stage of adaptive speciation. However, the evolution of phenotypic plasticity in host use is another possible outcome. Using a reciprocal transplant experiment we tested the hypothesis of local adaptation in the aphid Brevicoryne brassicae. Aphid genotypes derived from two sympatric host plants, Brassica oleracea and B. campestris, were assessed in order to measure the extent of phenotypic plasticity in morphological and life history traits in relation to the host plants. We obtained an index of phenotypic plasticity for each genotype. Morphological variation of aphids was summarized by principal components analysis. Significant effects of recipient host on morphological variation and life history traits (establishment, age at first reproduction, number of nymphs, and intrinsic growth rate were detected. We did not detected genotype × host plant interaction; in general the genotypes developed better on B. campestris, independent of the host plant species from which they were collected. Therefore, there was no evidence to suggest local adaptation. Regarding plasticity, significant differences among genotypes in the index of plasticity were detected. Furthermore, significant selection on PC1 (general aphid body size on B. campestris, and on PC1 and PC2 (body length relative to body size on B. oleracea was detected. The elevation of the reaction norm of PC1 and the slope of the reaction norm for PC2 (i.e., plasticity were under directional selection. Thus, host plant species constitute distinct selective environments for B. brassicae. Aphid genotypes expressed different phenotypes in response to the host plant with low or nil fitness costs. Phenotypic plasticity and gene flow limits natural selection for host specialization promoting the maintenance of genetic variation in host exploitation.

Phenotypic heterogeneity in a bacteriophage population only appears as stress-induced mutagenesis.

Science.gov (United States)

Yosef, Ido; Edgar, Rotem; Qimron, Udi

2016-11-01

Stress-induced mutagenesis has been studied in cancer cells, yeast, bacteria, and archaea, but not in viruses. In a recent publication, we present a bacteriophage model showing an apparent stress-induced mutagenesis. We show that the stress does not drive the mutagenesis, but only selects the fittest mutants. The mechanism underlying the observed phenomenon is a phenotypic heterogeneity that resembles persistence of the viral population. The new findings, the background for the ongoing debate on stress-induced mutagenesis, and the phenotypic heterogeneity underlying a novel phage infection strategy are discussed in this short manuscript.

Asthma phenotypes in childhood.

Science.gov (United States)

Reddy, Monica B; Covar, Ronina A

2016-04-01

This review describes the literature over the past 18 months that evaluated childhood asthma phenotypes, highlighting the key aspects of these studies, and comparing these studies to previous ones in this area. Recent studies on asthma phenotypes have identified new phenotypes on the basis of statistical analyses (using cluster analysis and latent class analysis methodology) and have evaluated the outcomes and associated risk factors of previously established early childhood asthma phenotypes that are based on asthma onset and patterns of wheezing illness. There have also been investigations focusing on immunologic, physiologic, and genetic correlates of various phenotypes, as well as identification of subphenotypes of severe childhood asthma. Childhood asthma remains a heterogeneous condition, and investigations into these various presentations, risk factors, and outcomes are important since they can offer therapeutic and prognostic relevance. Further investigation into the immunopathology and genetic basis underlying childhood phenotypes is important so therapy can be tailored accordingly.

Log-Optimal Portfolio Selection Using the Blackwell Approachability Theorem

OpenAIRE

V'yugin, Vladimir

2014-01-01

We present a method for constructing the log-optimal portfolio using the well-calibrated forecasts of market values. Dawid's notion of calibration and the Blackwell approachability theorem are used for computing well-calibrated forecasts. We select a portfolio using this "artificial" probability distribution of market values. Our portfolio performs asymptotically at least as well as any stationary portfolio that redistributes the investment at each round using a continuous function of side in...

Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases

KAUST Repository

Hoehndorf, Robert

2015-06-08

Phenotypes are the observable characteristics of an organism arising from its response to the environment. Phenotypes associated with engineered and natural genetic variation are widely recorded using phenotype ontologies in model organisms, as are signs and symptoms of human Mendelian diseases in databases such as OMIM and Orphanet. Exploiting these resources, several computational methods have been developed for integration and analysis of phenotype data to identify the genetic etiology of diseases or suggest plausible interventions. A similar resource would be highly useful not only for rare and Mendelian diseases, but also for common, complex and infectious diseases. We apply a semantic text-mining approach to identify the phenotypes (signs and symptoms) associated with over 6,000 diseases. We evaluate our text-mined phenotypes by demonstrating that they can correctly identify known disease-associated genes in mice and humans with high accuracy. Using a phenotypic similarity measure, we generate a human disease network in which diseases that have similar signs and symptoms cluster together, and we use this network to identify closely related diseases based on common etiological, anatomical as well as physiological underpinnings.

Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases

Science.gov (United States)

Hoehndorf, Robert; Schofield, Paul N.; Gkoutos, Georgios V.

2015-06-01

Phenotypes are the observable characteristics of an organism arising from its response to the environment. Phenotypes associated with engineered and natural genetic variation are widely recorded using phenotype ontologies in model organisms, as are signs and symptoms of human Mendelian diseases in databases such as OMIM and Orphanet. Exploiting these resources, several computational methods have been developed for integration and analysis of phenotype data to identify the genetic etiology of diseases or suggest plausible interventions. A similar resource would be highly useful not only for rare and Mendelian diseases, but also for common, complex and infectious diseases. We apply a semantic text-mining approach to identify the phenotypes (signs and symptoms) associated with over 6,000 diseases. We evaluate our text-mined phenotypes by demonstrating that they can correctly identify known disease-associated genes in mice and humans with high accuracy. Using a phenotypic similarity measure, we generate a human disease network in which diseases that have similar signs and symptoms cluster together, and we use this network to identify closely related diseases based on common etiological, anatomical as well as physiological underpinnings.

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

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Xiong Li

2012-11-01

Full Text Available This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP with high efficiency. We first analyze agent and agent-based simulation framework, CNP and collaborators, and present agents interaction chain used to actualize CNP and establish agents trust network. We then obtain contractor's importance weight and dynamic trust by presenting fuzzy similarity-based algorithm and trust modifying algorithm, thus we propose contractor selecting approach based on maximum dynamic integrative trust. We validate the feasibility and capability of this approach by implementing simulation, analyzing compared results and checking the model.

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

NARCIS (Netherlands)

Kohler, S.; Doelken, S.C.; Mungall, C.J.; Bauer, S.; Firth, H.V.; Bailleul-Forestier, I.; Black, G.C.M.; Brown, D.L.; Brudno, M.; Campbell, J.; FitzPatrick, D.R.; Eppig, J.T.; Jackson, A.P.; Freson, K.; Girdea, M.; Helbig, I.; Hurst, J.A.; Jahn, J.; Jackson, L.G.; Kelly, A.M.; Ledbetter, D.H.; Mansour, S.; Martin, C.L.; Moss, C.; Mumford, A.; Ouwehand, W.H.; Park, S.M.; Riggs, E.R.; Scott, R.H.; Sisodiya, S.; Vooren, S. van der; Wapner, R.J.; Wilkie, A.O.; Wright, C.F.; Silfhout, A.T. van; Leeuw, N. de; Vries, B. de; Washingthon, N.L.; Smith, C.L.; Westerfield, M.; Schofield, P.; Ruef, B.J.; Gkoutos, G.V.; Haendel, M.; Smedley, D.; Lewis, S.E.; Robinson, P.N.

2014-01-01

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have

Global Phenotypic Characterization of Effects of Fluoroquinolone Resistance Selection on the Metabolic Activities and Drug Susceptibilities of Clostridium perfringens Strains

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Miseon Park

2014-01-01

Full Text Available Fluoroquinolone resistance affects toxin production of Clostridium perfringens strains differently. To investigate the effect of fluoroquinolone resistance selection on global changes in metabolic activities and drug susceptibilities, four C. perfringens strains and their norfloxacin-, ciprofloxacin-, and gatifloxacin-resistant mutants were compared in nearly 2000 assays, using phenotype microarray plates. Variations among mutant strains resulting from resistance selection were observed in all aspects of metabolism. Carbon utilization, pH range, osmotic tolerance, and chemical sensitivity of resistant strains were affected differently in the resistant mutants depending on both the bacterial genotype and the fluoroquinolone to which the bacterium was resistant. The susceptibilities to gentamicin and erythromycin of all resistant mutants except one increased, but some resistant strains were less susceptible to amoxicillin, cefoxitin, ceftriaxone, chloramphenicol, and metronidazole than their wild types. Sensitivity to ethidium bromide decreased in some resistant mutants and increased in others. Microarray analysis of two gatifloxacin-resistant mutants showed changes in metabolic activities that were correlated with altered expression of various genes. Both the chemical structures of fluoroquinolones and the genomic makeup of the wild types influenced the changes found in resistant mutants, which may explain some inconsistent reports of the effects of therapeutic use of fluoroquinolones on clinical isolates of bacteria.

Usefulness of selective cerebral intra-arterial digital subtraction angiography by transbrachial approach

International Nuclear Information System (INIS)

Matsunaga, Naofumi; Hayashi, Kuniaki; Uetani, Masataka; Hirao, Koichi; Fukuda, Toshio; Aikawa, Hisayuki; Iwao, Masaaki; Hombo, Zen-ichiro

1988-01-01

Selective cerebral intra-arterial digital subtraction angiography (IA-DSA) by the transbrachial approach was performed on 53 patients (including 34 outpatients) with suspected cerebrovascular diseases or brain tumors. 80-cm-long, 4F modified Simmons catheter was used. Success rates of selective catheterization to the common carotid and vertebral arteries were 86.0 % from right transbrachial approach (35 cases) and 79.6 % from left approach (18 cases). Successful catheterization to the common carotid and ipsilateral vertebral arteries is obtained in 91.3 % from right transbrachial approach, and 78.7 % from left approach. Righ common carotid artery could be catheterized in all 55 cases from right transbrachial approach, but in only 6 of 15 patients (40 %) from left approach. As for contrast material, 4 or 6 ml of Iopamidol 300 mgI/ml were mechanically injected into common carotid artery at a flow rate of 2 - 3 ml/sec, and 9 ml two-fold diluted Iopamidol were injected into the vertebral artery at a flow rate of 6 ml/sec. There was no recoil of the catheter. Visualization of the relatively small vessels such as cortical branches was excellent in most cases. However, smaller vessel such as meningohypophyseal trunk was not well visualized with IA-DSA. Spatial resolution of IA-DSA was generally satisfactory. However, conventional angiography was still required, particularly to clearly delineate small cerebral aneurysms. Major complications were never experienced. It was concluded that this procedure is useful, particularly for the screening and postoperative follow-up studies, and can also be applied to outpatients. (author)

Breeding approaches in simultaneous selection for multiple stress tolerance of maize in tropical environments