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Sample records for quantitative genetic bases

  1. Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

    Directory of Open Access Journals (Sweden)

    Shen Li

    2010-09-01

    Full Text Available Abstract Background An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task. Results Using yeast sporulation as a model system, we have assembled a genetic network from literature and exploited Boolean network to predict sporulation efficiency change upon deleting individual genes. We observe that predictions based on the curated network correlate well with the experimentally measured values. In addition, computational analysis reveals the robustness and hysteresis of the yeast sporulation network and uncovers several patterns of sporulation efficiency change caused by double gene deletion. These discoveries may guide future investigation of underlying mechanisms. We have also shown that a hybridized genetic network reconstructed from both temporal microarray data and literature is able to achieve a satisfactory prediction accuracy of the same quantitative phenotypes. Conclusions This case study illustrates the value of predicting quantitative phenotypes based on genetic network and provides a generic approach.

  2. Genetic algorithm based image binarization approach and its quantitative evaluation via pooling

    Science.gov (United States)

    Hu, Huijun; Liu, Ya; Liu, Maofu

    2015-12-01

    The binarized image is very critical to image visual feature extraction, especially shape feature, and the image binarization approaches have been attracted more attentions in the past decades. In this paper, the genetic algorithm is applied to optimizing the binarization threshold of the strip steel defect image. In order to evaluate our genetic algorithm based image binarization approach in terms of quantity, we propose the novel pooling based evaluation metric, motivated by information retrieval community, to avoid the lack of ground-truth binary image. Experimental results show that our genetic algorithm based binarization approach is effective and efficiency in the strip steel defect images and our quantitative evaluation metric on image binarization via pooling is also feasible and practical.

  3. A consensus map of rapeseed (Brassica napus L.) based on diversity array technology markers: applications in genetic dissection of qualitative and quantitative traits

    National Research Council Canada - National Science Library

    Raman, Harsh; Raman, Rosy; Kilian, Andrzej; Detering, Frank; Long, Yan; Edwards, David; Parkin, Isobel A P; Sharpe, Andrew G; Nelson, Matthew N; Larkan, Nick; Zou, Jun; Meng, Jinling; Aslam, M Naveed; Batley, Jacqueline; Cowling, Wallace A; Lydiate, Derek

    2013-01-01

    Dense consensus genetic maps based on high-throughput genotyping platforms are valuable for making genetic gains in Brassica napus through quantitative trait locus identification, efficient predictive...

  4. Quantitative genetic bases of anthocyanin variation in grape (Vitis vinifera L. ssp. sativa) berry: a quantitative trait locus to quantitative trait nucleotide integrated study.

    Science.gov (United States)

    Fournier-Level, Alexandre; Le Cunff, Loïc; Gomez, Camila; Doligez, Agnès; Ageorges, Agnès; Roux, Catherine; Bertrand, Yves; Souquet, Jean-Marc; Cheynier, Véronique; This, Patrice

    2009-11-01

    The combination of QTL mapping studies of synthetic lines and association mapping studies of natural diversity represents an opportunity to throw light on the genetically based variation of quantitative traits. With the positional information provided through quantitative trait locus (QTL) mapping, which often leads to wide intervals encompassing numerous genes, it is now feasible to directly target candidate genes that are likely to be responsible for the observed variation in completely sequenced genomes and to test their effects through association genetics. This approach was performed in grape, a newly sequenced genome, to decipher the genetic architecture of anthocyanin content. Grapes may be either white or colored, ranging from the lightest pink to the darkest purple tones according to the amount of anthocyanin accumulated in the berry skin, which is a crucial trait for both wine quality and human nutrition. Although the determinism of the white phenotype has been fully identified, the genetic bases of the quantitative variation of anthocyanin content in berry skin remain unclear. A single QTL responsible for up to 62% of the variation in the anthocyanin content was mapped on a Syrah x Grenache F(1) pseudo-testcross. Among the 68 unigenes identified in the grape genome within the QTL interval, a cluster of four Myb-type genes was selected on the basis of physiological evidence (VvMybA1, VvMybA2, VvMybA3, and VvMybA4). From a core collection of natural resources (141 individuals), 32 polymorphisms revealed significant association, and extended linkage disequilibrium was observed. Using a multivariate regression method, we demonstrated that five polymorphisms in VvMybA genes except VvMybA4 (one retrotransposon, three single nucleotide polymorphisms and one 2-bp insertion/deletion) accounted for 84% of the observed variation. All these polymorphisms led to either structural changes in the MYB proteins or differences in the VvMybAs promoters. We concluded that

  5. FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

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    Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

    2015-10-01

    Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

  6. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

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    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science.

  7. A Creative Helicobacter pylori Diagnosis Scheme Based on Multiple Genetic Analysis System: Qualification and Quantitation.

    Science.gov (United States)

    Zhou, Lifang; Zhao, Fuju; Hu, Binjie; Fang, Yi; Miao, Yingxin; Huang, Yiqin; Ji, Da'nian; Zhang, Jinghao; Xu, Lingli; Zhang, Yanmei; Bao, Zhijun; Zhao, Hu

    2015-10-01

    Currently, several diagnostic assays for Helicobacter pylori (H. pylori) are available, but each has some limitations. Further, a high-flux quantitative assay is required to assist clinical diagnosis and monitor the effectiveness of therapy and novel vaccine candidates. Three hundred and eighty-seven adult patients [nonulcer dyspepsia (NUD) 295, peptic ulcer disease (PUD) 77, gastric cancer (GC) 15] were enrolled for gastrointestinal endoscopies. Three biopsy samples from gastric antrum were collected for the following tests: culture, rapid urease test (RUT), histopathology, conventional polymerase chain reaction (PCR), and Multiple Genetic Analysis System (MGAS). The diagnostic capability of H. pylori for all methods was evaluated through the receiver operating characteristic (ROC) curves. Based on the gold standard, the sensitivity and specificity of MGAS were 92.9 and 92.4%, and positive predict value (PPV) and negative predict value (NPV) were 96.0 and 87.1%, respectively. All the above parameters of MGAS were higher than that of culture (except its specificity), RUT and histopathology, and nearly closed to that of conventional PCR. The area under curve (AUC) was 0.7575 (Culture), 0.8870 (RUT), 0.9000 (Histopathology), 0.9496 (Conventional PCR), and 0.9277 (MGAS). No significant statistical difference was observed for the H. pylori DNA load in different disease groups (p = .067). In contrast, a statistically significant difference in the H. pylori DNA copy number was observed based on age (p = .043) and gender (p = .021). The data showed that MGAS performed well in detecting H. pylori infection. Furthermore, the quantitative analysis showed that the load of H. pylori was significantly different within both age and gender groups. These results suggested that MGAS could be a potential alternative method for clinical detection and monitoring of the effectiveness of H. pylori therapy. © 2015 John Wiley & Sons Ltd.

  8. Clarifying CLARITY: Quantitative Optimization of the Diffusion Based Delipidation Protocol for Genetically Labeled Tissue.

    Science.gov (United States)

    Magliaro, Chiara; Callara, Alejandro L; Mattei, Giorgio; Morcinelli, Marco; Viaggi, Cristina; Vaglini, Francesca; Ahluwalia, Arti

    2016-01-01

    Tissue clarification has been recently proposed to allow deep tissue imaging without light scattering. The clarification parameters are somewhat arbitrary and dependent on tissue type, source and dimension: every laboratory has its own protocol, but a quantitative approach to determine the optimum clearing time is still lacking. Since the use of transgenic mouse lines that express fluorescent proteins to visualize specific cell populations is widespread, a quantitative approach to determine the optimum clearing time for genetically labeled neurons from thick murine brain slices using CLARITY2 is described. In particular, as the main objective of the delipidation treatment is to clarify tissues, while limiting loss of fluorescent signal, the "goodness" of clarification was evaluated by considering the bulk tissue clarification index (BTCi) and the fraction of the fluorescent marker retained in the slice as easily quantifiable macroscale parameters. Here we describe the approach, illustrating an example of how it can be used to determine the optimum clearing time for 1 mm-thick cerebellar slice from transgenic L7GFP mice, in which Purkinje neurons express the GFP (green fluorescent protein) tag. To validate the method, we evaluated confocal stacks of our samples using standard image processing indices (i.e., the mean pixel intensity of neurons and the contrast-to-noise ratio) as figures of merit for image quality. The results show that detergent-based delipidation for more than 5 days does not increase tissue clarity but the fraction of GFP in the tissue continues to diminish. The optimum clearing time for 1 mm-thick slices was thus identified as 5 days, which is the best compromise between the increase in light penetration depth due to removal of lipids and a decrease in fluorescent signal as a consequence of protein loss: further clearing does not improve tissue transparency, but only leads to more protein removal or degradation. The rigorous quantitative approach

  9. Quantitative genetics of disease traits.

    Science.gov (United States)

    Wray, N R; Visscher, P M

    2015-04-01

    John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics.

  10. PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

    Science.gov (United States)

    Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

    2008-05-15

    A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

  11. Simulation of collaborative studies for real-time PCR-based quantitation methods for genetically modified crops.

    Science.gov (United States)

    Watanabe, Satoshi; Sawada, Hiroshi; Naito, Shigehiro; Akiyama, Hiroshi; Teshima, Reiko; Furui, Satoshi; Kitta, Kazumi; Hino, Akihiro

    2013-01-01

    To study impacts of various random effects and parameters of collaborative studies on the precision of quantitation methods of genetically modified (GM) crops, we developed a set of random effects models for cycle time values of a standard curve-based relative real-time PCR that makes use of an endogenous gene sequence as the internal standard. The models and data from a published collaborative study for six GM lines at four concentration levels were used to simulate collaborative studies under various conditions. Results suggested that by reducing the numbers of well replications from three to two, and standard levels of endogenous sequence from five to three, the number of unknown samples analyzable on a 96-well PCR plate in routine analyses could be almost doubled, and still the acceptable repeatability RSD (RSDr crops by real-time PCR and their collaborative studies.

  12. The quantitative genetics of phenotypic robustness.

    Directory of Open Access Journals (Sweden)

    Hunter B Fraser

    Full Text Available Phenotypic robustness, or canalization, has been extensively investigated both experimentally and theoretically. However, it remains unknown to what extent robustness varies between individuals, and whether factors buffering environmental variation also buffer genetic variation. Here we introduce a quantitative genetic approach to these issues, and apply this approach to data from three species. In mice, we find suggestive evidence that for hundreds of gene expression traits, robustness is polymorphic and can be genetically mapped to discrete genomic loci. Moreover, we find that the polymorphisms buffering genetic variation are distinct from those buffering environmental variation. In fact, these two classes have quite distinct mechanistic bases: environmental buffers of gene expression are predominantly sex-specific and trans-acting, whereas genetic buffers are not sex-specific and often cis-acting. Data from studies of morphological and life-history traits in plants and yeast support the distinction between polymorphisms buffering genetic and environmental variation, and further suggest that loci buffering different types of environmental variation do overlap with one another. These preliminary results suggest that naturally occurring polymorphisms affecting phenotypic robustness could be abundant, and that these polymorphisms may generally buffer either genetic or environmental variation, but not both.

  13. Genetic diversity of upland rice germplasm in Malaysia based on quantitative traits.

    Science.gov (United States)

    Sohrabi, M; Rafii, M Y; Hanafi, M M; Siti Nor Akmar, A; Latif, M A

    2012-01-01

    Genetic diversity is prerequisite for any crop improvement program as it helps in the development of superior recombinants. Fifty Malaysian upland rice accessions were evaluated for 12 growth traits, yield and yield components. All of the traits were significant and highly significant among the accessions. The higher magnitudes of genotypic and phenotypic coefficients of variation were recorded for flag leaf length-to-width ratio, spikelet fertility, and days to flowering. High heritability along with high genetic advance was registered for yield of plant, days to flowering, and flag leaf length-to-width ratio suggesting preponderance of additive gene action in the gene expression of these characters. Plant height showed highly significant positive correlation with most of the traits. According to UPGMA cluster analysis all accessions were clustered into six groups. Twelve morphological traits provided around 77% of total variation among the accessions.

  14. Genetic Diversity of Upland Rice Germplasm in Malaysia Based on Quantitative Traits

    Directory of Open Access Journals (Sweden)

    M. Sohrabi

    2012-01-01

    Full Text Available Genetic diversity is prerequisite for any crop improvement program as it helps in the development of superior recombinants. Fifty Malaysian upland rice accessions were evaluated for 12 growth traits, yield and yield components. All of the traits were significant and highly significant among the accessions. The higher magnitudes of genotypic and phenotypic coefficients of variation were recorded for flag leaf length-to-width ratio, spikelet fertility, and days to flowering. High heritability along with high genetic advance was registered for yield of plant, days to flowering, and flag leaf length-to-width ratio suggesting preponderance of additive gene action in the gene expression of these characters. Plant height showed highly significant positive correlation with most of the traits. According to UPGMA cluster analysis all accessions were clustered into six groups. Twelve morphological traits provided around 77% of total variation among the accessions.

  15. Theory and Practice in Quantitative Genetics

    DEFF Research Database (Denmark)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

    2003-01-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

  16. Quantitative genetic studies of antisocial behaviour.

    Science.gov (United States)

    Viding, Essi; Larsson, Henrik; Jones, Alice P

    2008-08-12

    This paper will broadly review the currently available twin and adoption data on antisocial behaviour (AB). It is argued that quantitative genetic research can make a significant contribution to further the understanding of how AB develops. Genetically informative study designs are particularly useful for investigating several important questions such as whether: the heritability estimates vary as a function of assessment method or gender; the relative importance of genetic and environmental influences varies for different types of AB; the environmental risk factors are truly environmental; and genetic vulnerability influences susceptibility to environmental risk. While the current data are not yet directly translatable for prevention and treatment programmes, quantitative genetic research has concrete translational potential. Quantitative genetic research can supplement neuroscience research in informing about different subtypes of AB, such as AB coupled with callous-unemotional traits. Quantitative genetic research is also important in advancing the understanding of the mechanisms by which environmental risk operates.

  17. Strategies for MCMC computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez, N.; Sorensen, Daniel

    2006-01-01

    Given observations of a trait and a pedigree for a group of animals, the basic model in quantitative genetics is a linear mixed model with genetic random effects. The correlation matrix of the genetic random effects is determined by the pedigree and is typically very highdimensional...

  18. Construction of measurement uncertainty profiles for quantitative analysis of genetically modified organisms based on interlaboratory validation data.

    Science.gov (United States)

    Macarthur, Roy; Feinberg, Max; Bertheau, Yves

    2010-01-01

    A method is presented for estimating the size of uncertainty associated with the measurement of products derived from genetically modified organisms (GMOs). The method is based on the uncertainty profile, which is an extension, for the estimation of uncertainty, of a recent graphical statistical tool called an accuracy profile that was developed for the validation of quantitative analytical methods. The application of uncertainty profiles as an aid to decision making and assessment of fitness for purpose is also presented. Results of the measurement of the quantity of GMOs in flour by PCR-based methods collected through a number of interlaboratory studies followed the log-normal distribution. Uncertainty profiles built using the results generally give an expected range for measurement results of 50-200% of reference concentrations for materials that contain at least 1% GMO. This range is consistent with European Network of GM Laboratories and the European Union (EU) Community Reference Laboratory validation criteria and can be used as a fitness for purpose criterion for measurement methods. The effect on the enforcement of EU labeling regulations is that, in general, an individual analytical result needs to be 1.8% to demonstrate noncompliance with a labeling threshold of 0.9%.

  19. Theory and practice in quantitative genetics.

    Science.gov (United States)

    Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C; van Baal, G Caroline M; von Hjelmborg, Jacob B; Iachine, Ivan; Boomsma, Dorret I

    2003-10-01

    With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each, we show how the theoretical biometrical model can be translated into algebraic equations that may be used to generate scripts for statistical genetic software packages, such as Mx, Lisrel, SOLAR, or MERLIN. For using the former program a web-library (available from http://www.psy.vu.nl/mxbib) has been developed of freely available scripts that can be used to conduct all genetic analyses described in this paper.

  20. Quantitative genetic studies of antisocial behaviour

    OpenAIRE

    Viding, Essi; Larsson, Henrik; Jones, Alice P.

    2008-01-01

    This paper will broadly review the currently available twin and adoption data on antisocial behaviour (AB). It is argued that quantitative genetic research can make a significant contribution to further the understanding of how AB develops. Genetically informative study designs are particularly useful for investigating several important questions such as whether: the heritability estimates vary as a function of assessment method or gender; the relative importance of genetic and environmental ...

  1. Evolutionary quantitative genetics of nonlinear developmental systems.

    Science.gov (United States)

    Morrissey, Michael B

    2015-08-01

    In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium-term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time-steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances.

  2. Receptor-based modeling and 3D-QSAR for a quantitative production of the butyrylcholinesterase inhibitors based on genetic algorithm.

    Science.gov (United States)

    Zaheer-ul, Haq; Uddin, Reaz; Yuan, Hongbin; Petukhov, Pavel A; Choudhary, M Iqbal; Madura, Jeffry D

    2008-05-01

    Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of structurally related steroidal alkaloids as butyrylcholinesterase (BuChE) inhibitors. Docking studies were employed to position the inhibitors into the BuChE active site to determine the most probable binding mode. The strategy was to explore multiple inhibitor conformations in producing a more reliable 3D-QSAR model. These multiple conformations were derived using the FlexS program. The conformation selection step for CoMFA was done by genetic algorithm. The genetic algorithm based CoMFA approach was found to be the best. Both CoMFA and CoMSIA yielded significant cross-validated q(2) values of 0.701 and 0.627 and the r(2) values of 0.979 and 0.982, respectively. These statistically significant models were validated by a test set of five compounds. Comparison of CoMFA and CoMSIA contour maps helped to identify structural requirements for the inhibitors and serves as a basis for the design of the next generation of the inhibitor analogues. The results demonstrate that the combination of ligand-based and receptor-based modeling with use of a genetic algorithm is a powerful approach to build 3D-QSAR models. These data can be used for the lead optimization process with respect to inhibition enhancement which is important for the drug discovery and development for Alzheimer's disease.

  3. Whole genome approaches to quantitative genetics.

    Science.gov (United States)

    Visscher, Peter M

    2009-06-01

    Apart from parent-offspring pairs and clones, relative pairs vary in the proportion of the genome that they share identical by descent. In the past, quantitative geneticists have used the expected value of sharing genes by descent to estimate genetic parameters and predict breeding values. With the possibility to genotype individuals for many markers across the genome it is now possible to empirically estimate the actual relationship between relatives. We review some of the theory underlying the variation in genetic identity, show applications to estimating genetic variance for height in humans and discuss other applications.

  4. Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

    Science.gov (United States)

    Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

    2011-11-11

    Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

  5. Next generation quantitative genetics in plants.

    Science.gov (United States)

    Jiménez-Gómez, José M

    2011-01-01

    Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.

  6. Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea

    Science.gov (United States)

    Bajaj, Deepak; Saxena, Maneesha S.; Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Tripathi, Shailesh; Upadhyaya, Hari D.; Gowda, C. L. L.; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K.; Parida, Swarup K.

    2015-01-01

    Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5′-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea. PMID:25504138

  7. Genetic variability, heritability and genetic advance of quantitative ...

    African Journals Online (AJOL)

    ONOS

    2010-05-10

    May 10, 2010 ... clusters/plant, number of pods/plant, number of seeds/pod, yield/plant and 100 seed weight of black gram in M2 ... Key words: Genetic variability, gamma rays, quantitative traits, black gram. ... MATERIALS AND METHODS.

  8. Segregation Analysis on Genetic System of Quantitative Traits in Plants

    Institute of Scientific and Technical Information of China (English)

    Gai Junyi

    2006-01-01

    Based on the traditional polygene inheritance model of quantitative traits,the author suggests the major gene and polygene mixed inheritance model.The model was considered as a general one,while the pure major gene and pure polygene inheritance model was a specific case of the general model.Based on the proposed theory,the author established the segregation analysis procedure to study the genetic system of quantitative traits of plants.At present,this procedure can be used to evaluate the genetic effect of individual major genes (up to two to three major genes),the collective genetic effect of polygene,and their heritability value.This paper introduces how to establish the procedure,its main achievements,and its applications.An example is given to illustrate the steps,methods,and effectiveness of the procedure.

  9. Event History Analysis in Quantitative Genetics

    DEFF Research Database (Denmark)

    Maia, Rafael Pimentel

    Event history analysis is a clas of statistical methods specially designed to analyze time-to-event characteristics, e.g. the time until death. The aim of the thesis was to present adequate multivariate versions of mixed survival models that properly represent the genetic aspects related to a given...... time-to-event characteristic of interest. Real genetic longevity studies based on female animals of different species (sows, dairy cows, and sheep) exemplifies the use of the methods. Moreover these studies allow to understand som genetic mechanisms related to the lenght of the productive life...

  10. Genetic Variation, Heritability, and Diversity Analysis of Upland Rice (Oryza sativa L. Genotypes Based on Quantitative Traits

    Directory of Open Access Journals (Sweden)

    Mst. Tuhina-Khatun

    2015-01-01

    Full Text Available Upland rice is important for sustainable crop production to meet future food demands. The expansion in area of irrigated rice faces limitations due to water scarcity resulting from climate change. Therefore, this research aimed to identify potential genotypes and suitable traits of upland rice germplasm for breeding programmes. Forty-three genotypes were evaluated in a randomised complete block design with three replications. All genotypes exhibited a wide and significant variation for 22 traits. The highest phenotypic and genotypic coefficient of variation was recorded for the number of filled grains/panicle and yields/plant (g. The highest heritability was found for photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO2, and number of filled grains/panicle and yields/plant (g. Cluster analysis based on 22 traits grouped the 43 rice genotypes into five clusters. Cluster II was the largest and consisted of 20 genotypes mostly originating from the Philippines. The first four principle components of 22 traits accounted for about 72% of the total variation and indicated a wide variation among the genotypes. The selected best trait of the number of filled grains/panicle and yields/plant (g, which showed high heritability and high genetic advance, could be used as a selection criterion for hybridisation programmes in the future.

  11. Genetic Variation, Heritability, and Diversity Analysis of Upland Rice (Oryza sativa L.) Genotypes Based on Quantitative Traits.

    Science.gov (United States)

    Tuhina-Khatun, Mst; Hanafi, Mohamed M; Rafii Yusop, Mohd; Wong, M Y; Salleh, Faezah M; Ferdous, Jannatul

    2015-01-01

    Upland rice is important for sustainable crop production to meet future food demands. The expansion in area of irrigated rice faces limitations due to water scarcity resulting from climate change. Therefore, this research aimed to identify potential genotypes and suitable traits of upland rice germplasm for breeding programmes. Forty-three genotypes were evaluated in a randomised complete block design with three replications. All genotypes exhibited a wide and significant variation for 22 traits. The highest phenotypic and genotypic coefficient of variation was recorded for the number of filled grains/panicle and yields/plant (g). The highest heritability was found for photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO₂, and number of filled grains/panicle and yields/plant (g). Cluster analysis based on 22 traits grouped the 43 rice genotypes into five clusters. Cluster II was the largest and consisted of 20 genotypes mostly originating from the Philippines. The first four principle components of 22 traits accounted for about 72% of the total variation and indicated a wide variation among the genotypes. The selected best trait of the number of filled grains/panicle and yields/plant (g), which showed high heritability and high genetic advance, could be used as a selection criterion for hybridisation programmes in the future.

  12. An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus).

    Science.gov (United States)

    Ren, Yi; McGregor, Cecilia; Zhang, Yan; Gong, Guoyi; Zhang, Haiying; Guo, Shaogui; Sun, Honghe; Cai, Wantao; Zhang, Jie; Xu, Yong

    2014-01-20

    Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A

  13. Integration of molecular genetic technology with quantitative genetic technology for maximizing the speed of genetic improvement

    Institute of Scientific and Technical Information of China (English)

    Jack; C.M.; DEKKERS

    2005-01-01

    To date,most genetic progress for quantita-tive traits in livestock has been made by selec-tion on phenotype or on estimates of breedingvalues(BBV)derived from phenotype,withoutknowledge of the number of genes that affect thetrait or the effects of each gene.In this quantita-tive genetic approach to genetic improvement,the genetic architecture of traits of interest hasessentially been treated as a‘black box’.De-spite this,the substantial rates of genetic im-provement that have been and continue to be a-chie...

  14. Interacting personalities: behavioural ecology meets quantitative genetics.

    Science.gov (United States)

    Dingemanse, Niels J; Araya-Ajoy, Yimen G

    2015-02-01

    Behavioural ecologists increasingly study behavioural variation within and among individuals in conjunction, thereby integrating research on phenotypic plasticity and animal personality within a single adaptive framework. Interactions between individuals (cf. social environments) constitute a major causative factor of behavioural variation at both of these hierarchical levels. Social interactions give rise to complex 'interactive phenotypes' and group-level emergent properties. This type of phenotype has intriguing evolutionary implications, warranting a cohesive framework for its study. We detail here how a reaction-norm framework might be applied to usefully integrate social environment theory developed in behavioural ecology and quantitative genetics. The proposed emergent framework facilitates firm integration of social environments in adaptive research on phenotypic characters that vary within and among individuals.

  15. A wheat intervarietal genetic linkage map based on microsatellite and target region amplified polymorphism markers and its utility for detecting quantitative trait loci.

    Science.gov (United States)

    Liu, Z H; Anderson, J A; Hu, J; Friesen, T L; Rasmussen, J B; Faris, J D

    2005-08-01

    Efficient user-friendly methods for mapping plant genomes are highly desirable for the identification of quantitative trait loci (QTLs), genotypic profiling, genomic studies, and marker-assisted selection. SSR (microsatellite) markers are user-friendly and efficient in detecting polymorphism, but they detect few loci. Target region amplification polymorphism (TRAP) is a relatively new PCR-based technique that detects a large number of loci from a single reaction without extensive pre-PCR processing of samples. In the investigation reported here, we used both SSRs and TRAPs to generate over 700 markers for the construction of a genetic linkage map in a hard red spring wheat intervarietal recombinant inbred population. A framework map consisting of 352 markers accounted for 3,045 cM with an average density of one marker per 8.7 cM. On average, SSRs detected 1.9 polymorphic loci per reaction, while TRAPs detected 24. Both marker systems were suitable for assigning linkage groups to chromosomes using wheat aneuploid stocks. We demonstrated the utility of the maps by identifying major QTLs for days to heading and reduced plant height on chromosomes 5A and 4B, respectively. Our results indicate that TRAPs are highly efficient for genetic mapping in wheat. The maps developed will be useful for the identification of quality and disease resistance QTLs that segregate in this population.

  16. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

    2008-01-01

    In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...... in quantitative genetics is to obtain efficient updates of the high-dimensional vectors of genetic random effects and the associated covariance parameters. We discuss various strategies to approach this problem including reparameterization, Langevin-Hastings updates, and updates based on normal approximations....... The methods are compared in applications to Bayesian inference for three data sets using a model with genetically structured variance heterogeneity...

  17. Genetic Architectures of Quantitative Variation in RNA Editing Pathways.

    Science.gov (United States)

    Gu, Tongjun; Gatti, Daniel M; Srivastava, Anuj; Snyder, Elizabeth M; Raghupathy, Narayanan; Simecek, Petr; Svenson, Karen L; Dotu, Ivan; Chuang, Jeffrey H; Keller, Mark P; Attie, Alan D; Braun, Robert E; Churchill, Gary A

    2016-02-01

    RNA editing refers to post-transcriptional processes that alter the base sequence of RNA. Recently, hundreds of new RNA editing targets have been reported. However, the mechanisms that determine the specificity and degree of editing are not well understood. We examined quantitative variation of site-specific editing in a genetically diverse multiparent population, Diversity Outbred mice, and mapped polymorphic loci that alter editing ratios globally for C-to-U editing and at specific sites for A-to-I editing. An allelic series in the C-to-U editing enzyme Apobec1 influences the editing efficiency of Apob and 58 additional C-to-U editing targets. We identified 49 A-to-I editing sites with polymorphisms in the edited transcript that alter editing efficiency. In contrast to the shared genetic control of C-to-U editing, most of the variable A-to-I editing sites were determined by local nucleotide polymorphisms in proximity to the editing site in the RNA secondary structure. Our results indicate that RNA editing is a quantitative trait subject to genetic variation and that evolutionary constraints have given rise to distinct genetic architectures in the two canonical types of RNA editing.

  18. Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

    Science.gov (United States)

    Albert, Réka; Collins, James J.; Glass, Leon

    2013-06-01

    All cells of living organisms contain similar genetic instructions encoded in the organism's DNA. In any particular cell, the control of the expression of each different gene is regulated, in part, by binding of molecular complexes to specific regions of the DNA. The molecular complexes are composed of protein molecules, called transcription factors, combined with various other molecules such as hormones and drugs. Since transcription factors are coded by genes, cellular function is partially determined by genetic networks. Recent research is making large strides to understand both the structure and the function of these networks. Further, the emerging discipline of synthetic biology is engineering novel gene circuits with specific dynamic properties to advance both basic science and potential practical applications. Although there is not yet a universally accepted mathematical framework for studying the properties of genetic networks, the strong analogies between the activation and inhibition of gene expression and electric circuits suggest frameworks based on logical switching circuits. This focus issue provides a selection of papers reflecting current research directions in the quantitative analysis of genetic networks. The work extends from molecular models for the binding of proteins, to realistic detailed models of cellular metabolism. Between these extremes are simplified models in which genetic dynamics are modeled using classical methods of systems engineering, Boolean switching networks, differential equations that are continuous analogues of Boolean switching networks, and differential equations in which control is based on power law functions. The mathematical techniques are applied to study: (i) naturally occurring gene networks in living organisms including: cyanobacteria, Mycoplasma genitalium, fruit flies, immune cells in mammals; (ii) synthetic gene circuits in Escherichia coli and yeast; and (iii) electronic circuits modeling genetic networks

  19. Development and application of absolute quantitative detection by duplex chamber-based digital PCR of genetically modified maize events without pretreatment steps.

    Science.gov (United States)

    Zhu, Pengyu; Fu, Wei; Wang, Chenguang; Du, Zhixin; Huang, Kunlun; Zhu, Shuifang; Xu, Wentao

    2016-04-15

    The possibility of the absolute quantitation of GMO events by digital PCR was recently reported. However, most absolute quantitation methods based on the digital PCR required pretreatment steps. Meanwhile, singleplex detection could not meet the demand of the absolute quantitation of GMO events that is based on the ratio of foreign fragments and reference genes. Thus, to promote the absolute quantitative detection of different GMO events by digital PCR, we developed a quantitative detection method based on duplex digital PCR without pretreatment. Moreover, we tested 7 GMO events in our study to evaluate the fitness of our method. The optimized combination of foreign and reference primers, limit of quantitation (LOQ), limit of detection (LOD) and specificity were validated. The results showed that the LOQ of our method for different GMO events was 0.5%, while the LOD is 0.1%. Additionally, we found that duplex digital PCR could achieve the detection results with lower RSD compared with singleplex digital PCR. In summary, the duplex digital PCR detection system is a simple and stable way to achieve the absolute quantitation of different GMO events. Moreover, the LOQ and LOD indicated that this method is suitable for the daily detection and quantitation of GMO events. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Developments in statistical analysis in quantitative genetics

    DEFF Research Database (Denmark)

    Sorensen, Daniel

    2009-01-01

    A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap and ...

  1. The quantitative genetics of disgust sensitivity.

    Science.gov (United States)

    Sherlock, James M; Zietsch, Brendan P; Tybur, Joshua M; Jern, Patrick

    2016-02-01

    [Correction Notice: An Erratum for this article was reported in Vol 16(1) of Emotion (see record 2015-57029-001). In the article, the name of author Joshua M. Tybur was misspelled as Joshua M. Tyber. All versions of this article have been corrected.] Response sensitivity to common disgust elicitors varies considerably among individuals. The sources of these individual differences are largely unknown. In the current study, we use a large sample of female identical and nonidentical twins (N = 1,041 individuals) and their siblings (N = 170) to estimate the proportion of variation due to genetic effects, the shared environment, and other (residual) sources across multiple domains of disgust sensitivity. We also investigate the genetic and environmental influences on the covariation between the different disgust domains. Twin modeling revealed that approximately half of the variation in pathogen, sexual, and moral disgust is due to genetic effects. An independent pathways twin model also revealed that sexual and pathogen disgust sensitivity were influenced by unique sources of genetic variation, while also being significantly affected by a general genetic factor underlying all 3 disgust domains. Moral disgust sensitivity, in contrast, did not exhibit domain-specific genetic variation. These findings are discussed in light of contemporary evolutionary approaches to disgust sensitivity.

  2. Integration of gene-based markers in a pearl millet genetic map for identification of candidate genes underlying drought tolerance quantitative trait loci

    Directory of Open Access Journals (Sweden)

    Sehgal Deepmala

    2012-01-01

    Full Text Available Abstract Background Identification of genes underlying drought tolerance (DT quantitative trait loci (QTLs will facilitate understanding of molecular mechanisms of drought tolerance, and also will accelerate genetic improvement of pearl millet through marker-assisted selection. We report a map based on genes with assigned functional roles in plant adaptation to drought and other abiotic stresses and demonstrate its use in identifying candidate genes underlying a major DT-QTL. Results Seventy five single nucleotide polymorphism (SNP and conserved intron spanning primer (CISP markers were developed from available expressed sequence tags (ESTs using four genotypes, H 77/833-2, PRLT 2/89-33, ICMR 01029 and ICMR 01004, representing parents of two mapping populations. A total of 228 SNPs were obtained from 30.5 kb sequenced region resulting in a SNP frequency of 1/134 bp. The positions of major pearl millet linkage group (LG 2 DT-QTLs (reported from crosses H 77/833-2 × PRLT 2/89-33 and 841B × 863B were added to the present consensus function map which identified 18 genes, coding for PSI reaction center subunit III, PHYC, actin, alanine glyoxylate aminotransferase, uridylate kinase, acyl-CoA oxidase, dipeptidyl peptidase IV, MADS-box, serine/threonine protein kinase, ubiquitin conjugating enzyme, zinc finger C- × 8-C × 5-C × 3-H type, Hd3, acetyl CoA carboxylase, chlorophyll a/b binding protein, photolyase, protein phosphatase1 regulatory subunit SDS22 and two hypothetical proteins, co-mapping in this DT-QTL interval. Many of these candidate genes were found to have significant association with QTLs of grain yield, flowering time and leaf rolling under drought stress conditions. Conclusions We have exploited available pearl millet EST sequences to generate a mapped resource of seventy five new gene-based markers for pearl millet and demonstrated its use in identifying candidate genes underlying a major DT-QTL in this species. The reported gene-based

  3. Genetic mapping and quantitative trait loci analysis for disease resistance using F2 and F5 generation-based genetic maps derived from 'Tifrunner' x'GT-C20' in peanut

    Science.gov (United States)

    One mapping population derived from Tifrunner × GT-C20 has shown great potential in developing a high dense genetic map and identification of QTLs for important disease resistance, Tomato spotted wilt virus (TSWV) and leaf spot (LS). Both F2 and F5 generation-based genetic maps were constructed prev...

  4. Data-driven encoding for quantitative genetic trait prediction.

    Science.gov (United States)

    He, Dan; Wang, Zhanyong; Parida, Laxmi

    2015-01-01

    Given a set of biallelic molecular markers, such as SNPs, with genotype values on a collection of plant, animal or human samples, the goal of quantitative genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Quantitative genetic trait prediction is usually represented as linear regression models which require quantitative encodings for the genotypes: the three distinct genotype values, corresponding to one heterozygous and two homozygous alleles, are usually coded as integers, and manipulated algebraically in the model. Further, epistasis between multiple markers is modeled as multiplication between the markers: it is unclear that the regression model continues to be effective under this. In this work we investigate the effects of encodings to the quantitative genetic trait prediction problem. We first showed that different encodings lead to different prediction accuracies, in many test cases. We then proposed a data-driven encoding strategy, where we encode the genotypes according to their distribution in the phenotypes and we allow each marker to have different encodings. We show in our experiments that this encoding strategy is able to improve the performance of the genetic trait prediction method and it is more helpful for the oligogenic traits, whose values rely on a relatively small set of markers. To the best of our knowledge, this is the first paper that discusses the effects of encodings to the genetic trait prediction problem.

  5. Genetic diversity analysis based on molecular marker and quantitative traits of the response of different tomato (Lycopersicon esculentum Mill. cultivars to drought stress

    Directory of Open Access Journals (Sweden)

    Metwali Ehab M.R.

    2016-01-01

    Full Text Available The drought tolerance of tomato (Lycopersicon esculentum Mill. is a trait needing urgent improvement due to recent climate changes and limited water availability. We therefore conducted a greenhouse screening experiment to identify tomato cultivars with improved drought tolerance. Several sensitivity and tolerance indices were computed based on morphological markers. With the aim of establishing a correlation to these markers, a total of 16 inter-simple sequence repeat (ISSR primers were used, the genetic diversity among cultivars was elucidated and clustering the cultivars into groups based on their molecular profiles was performed. The obtained results indicated that selection indices, such as geometric mean productivity (GMP, mean productivity (MP, tolerance index (TOL,and stress tolerance index (STI, represented suitable indices for screening the drought tolerance of tomato cultivars. An interesting correlation of the ISSR analyses to these morphological findings was established according to 83 detectable fragments derived from 10 primers. The highest value of the effective multiplex ratio (EMR and marker index (MI was detected for primer INC7 followed by INC1. Based on Jaccard's similarity coefficients, the genetic distance of the genotypes varied from 0.702 to 0.942 with a mean value of 0.882. The results showed a clear-cut separation of the 15 tomato cultivars due to their genetic variability, making them a valuable genetic source for their incorporation into potential breeding programs. Molecular data were in good agreement with the results as regards selection indices, and both of them will be useful tools for improvement of the tomato germplasm.

  6. Genetic architecture of quantitative traits and complex diseases.

    Science.gov (United States)

    Fu, Wenqing; O'Connor, Timothy D; Akey, Joshua M

    2013-12-01

    More than 150 years after Mendel discovered the laws of heredity, the genetic architecture of phenotypic variation remains elusive. Here, we discuss recent progress in deciphering how genotypes map onto phenotypes, sources of genetic complexity, and how model organisms are illuminating general principles about the relationship between genetic and phenotypic variation. Moreover, we highlight insights gleaned from large-scale sequencing studies in humans, and how this knowledge informs outstanding questions about the genetic architecture of quantitative traits and complex diseases. Finally, we articulate how the confluence of technologies enabling whole-genome sequencing, comprehensive phenotyping, and high-throughput functional assays of polymorphisms will facilitate a more principled and mechanistic understanding of the genetic architecture of phenotypic variation.

  7. Complex genetic interactions in a quantitative trait locus.

    Directory of Open Access Journals (Sweden)

    Himanshu Sinha

    2006-02-01

    Full Text Available Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs, characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg QTGs (MKT1, END3, and RHO2. We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3'UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.

  8. Genetic mapping of quantitative phenotypic traits in Saccharomyces cerevisiae.

    Science.gov (United States)

    Swinnen, Steve; Thevelein, Johan M; Nevoigt, Elke

    2012-03-01

    Saccharomyces cerevisiae has become a favorite production organism in industrial biotechnology presenting new challenges to yeast engineers in terms of introducing advantageous traits such as stress tolerances. Exploring subspecies diversity of S. cerevisiae has identified strains that bear industrially relevant phenotypic traits. Provided that the genetic basis of such phenotypic traits can be identified inverse engineering allows the targeted modification of production strains. Most phenotypic traits of interest in S. cerevisiae strains are quantitative, meaning that they are controlled by multiple genetic loci referred to as quantitative trait loci (QTL). A straightforward approach to identify the genetic basis of quantitative traits is QTL mapping which aims at the allocation of the genetic determinants to regions in the genome. The application of high-density oligonucleotide arrays and whole-genome re-sequencing to detect genetic variations between strains has facilitated the detection of large numbers of molecular markers thus allowing high-resolution QTL mapping over the entire genome. This review focuses on the basic principle and state of the art of QTL mapping in S. cerevisiae. Furthermore we discuss several approaches developed during the last decade that allow down-scaling of the regions identified by QTL mapping to the gene level. We also emphasize the particular challenges of QTL mapping in nonlaboratory strains of S. cerevisiae.

  9. Quantitative Genetics in the Era of Molecular Genetics: Learning Abilities and Disabilities as an Example

    Science.gov (United States)

    Haworth, Claire M. A.; Plomin, Robert

    2010-01-01

    Objective: To consider recent findings from quantitative genetic research in the context of molecular genetic research, especially genome-wide association studies. We focus on findings that go beyond merely estimating heritability. We use learning abilities and disabilities as examples. Method: Recent twin research in the area of learning…

  10. Classification of cassava genotypes based on qualitative and quantitative data.

    Science.gov (United States)

    Oliveira, E J; Oliveira Filho, O S; Santos, V S

    2015-02-02

    We evaluated the genetic variation of cassava accessions based on qualitative (binomial and multicategorical) and quantitative traits (continuous). We characterized 95 accessions obtained from the Cassava Germplasm Bank of Embrapa Mandioca e Fruticultura; we evaluated these accessions for 13 continuous, 10 binary, and 25 multicategorical traits. First, we analyzed the accessions based only on quantitative traits; next, we conducted joint analysis (qualitative and quantitative traits) based on the Ward-MLM method, which performs clustering in two stages. According to the pseudo-F, pseudo-t2, and maximum likelihood criteria, we identified five and four groups based on quantitative trait and joint analysis, respectively. The smaller number of groups identified based on joint analysis may be related to the nature of the data. On the other hand, quantitative data are more subject to environmental effects in the phenotype expression; this results in the absence of genetic differences, thereby contributing to greater differentiation among accessions. For most of the accessions, the maximum probability of classification was >0.90, independent of the trait analyzed, indicating a good fit of the clustering method. Differences in clustering according to the type of data implied that analysis of quantitative and qualitative traits in cassava germplasm might explore different genomic regions. On the other hand, when joint analysis was used, the means and ranges of genetic distances were high, indicating that the Ward-MLM method is very useful for clustering genotypes when there are several phenotypic traits, such as in the case of genetic resources and breeding programs.

  11. The nature of quantitative genetic variation for Drosophila longevity.

    Science.gov (United States)

    Mackay, Trudy F C

    2002-01-01

    Longevity is a typical quantitative trait: the continuous variation in life span observed in natural populations is attributable to genetic variation at multiple quantitative trait loci (QTL), environmental sensitivity of QTL alleles, and truly continuous environmental variation. To begin to understand the genetic architecture of longevity at the level of individual QTL, we have mapped QTL for Drosophila life span that segregate between two inbred strains that were not selected for longevity. A mapping population of 98 recombinant inbred lines (RIL) was derived from these strains, and life span of virgin male and female flies measured under control culture conditions, chronic heat and cold stress, heat shock and starvation stress, and high and low density larval environments. The genotypes of the RIL were determined for polymorphic roo transposable element insertion sites, and life span QTL were mapped using composite interval mapping methods. A minimum of 19 life span QTL were detected by recombination mapping. The life span QTL exhibited strong genotype by sex, genotype by environment, and genotype by genotype (epistatic) interactions. These interactions complicate mapping efforts, but evolutionary theory predicts such properties of segregating QTL alleles. Quantitative deficiency mapping of four longevity QTL detected in the control environment by recombination mapping revealed a minimum of 11 QTL in these regions. Clearly, longevity is a complex quantitative trait. In the future, linkage disequilibrium mapping can be used to determine which candidate genes in a QTL region correspond to the genetic loci affecting variation in life span, and define the QTL alleles at the molecular level.

  12. Quantitative genetic analysis of injury liability in infants and toddlers

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, K.; Matheny, A.P. Jr. [Univ. of Louisville Medical School, KY (United States)

    1995-02-27

    A threshold model of latent liability was applied to infant and toddler twin data on total count of injuries sustained during the interval from birth to 36 months of age. A quantitative genetic analysis of estimated twin correlations in injury liability indicated strong genetic dominance effects, but no additive genetic variance was detected. Because interpretations involving overdominance have little research support, the results may be due to low order epistasis or other interaction effects. Boys had more injuries than girls, but this effect was found only for groups whose parents were prompted and questioned in detail about their children`s injuries. Activity and impulsivity are two behavioral predictors of childhood injury, and the results are discussed in relation to animal research on infant and adult activity levels, and impulsivity in adult humans. Genetic epidemiological approaches to childhood injury should aid in targeting higher risk children for preventive intervention. 30 refs., 4 figs., 3 tabs.

  13. Quantitative genetic activity graphical profiles for use in chemical evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Waters, M.D. [Environmental Protection Agency, Washington, DC (United States); Stack, H.F.; Garrett, N.E.; Jackson, M.A. [Environmental Health Research and Testing, Inc., Research Triangle Park, NC (United States)

    1990-12-31

    A graphic approach, terms a Genetic Activity Profile (GAP), was developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose or highest ineffective dose is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for producing and evaluating genetic activity profile was developed in collaboration with the International Agency for Research on Cancer (IARC). Data on individual chemicals were compiles by IARC and by the US Environmental Protection Agency (EPA). Data are available on 343 compounds selected from volumes 1-53 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar profiles of genetic activity. Through examination of the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluation of chemical analogs. GAPs provided useful data for development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from an assessment of the genetic activity profiles of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines. 36 refs., 2 figs.

  14. Multiple mating but not recombination causes quantitative increase in offspring genetic diversity for varying genetic architectures.

    Directory of Open Access Journals (Sweden)

    Olav Rueppell

    Full Text Available Explaining the evolution of sex and recombination is particularly intriguing for some species of eusocial insects because they display exceptionally high mating frequencies and genomic recombination rates. Explanations for both phenomena are based on the notion that both increase colony genetic diversity, with demonstrated benefits for colony disease resistance and division of labor. However, the relative contributions of mating number and recombination rate to colony genetic diversity have never been simultaneously assessed. Our study simulates colonies, assuming different mating numbers, recombination rates, and genetic architectures, to assess their worker genotypic diversity. The number of loci has a strong negative effect on genotypic diversity when the allelic effects are inversely scaled to locus number. In contrast, dominance, epistasis, lethal effects, or limiting the allelic diversity at each locus does not significantly affect the model outcomes. Mating number increases colony genotypic variance and lowers variation among colonies with quickly diminishing returns. Genomic recombination rate does not affect intra- and inter-colonial genotypic variance, regardless of mating frequency and genetic architecture. Recombination slightly increases the genotypic range of colonies and more strongly the number of workers with unique allele combinations across all loci. Overall, our study contradicts the argument that the exceptionally high recombination rates cause a quantitative increase in offspring genotypic diversity across one generation. Alternative explanations for the evolution of high recombination rates in social insects are therefore needed. Short-term benefits are central to most explanations of the evolution of multiple mating and high recombination rates in social insects but our results also apply to other species.

  15. Developmental quantitative genetic analysis of body weights and morphological traits in the turbot, Scophthalmusmaximus

    Institute of Scientific and Technical Information of China (English)

    WANG Xinan; MA Aijun; MA Deyou

    2015-01-01

    In order to elucidate the genetic mechanism of growth traits in turbot during ontogeny, developmental genetic analysis of the body weights, total lengths, standard lengths and body heights of turbots was conducted by mixed genetic models with additive-dominance effects, based on complete diallel crosses with four different strains of Scophthalmus maximus from Denmark, Norway, Britain, and France. Unconditional genetic analysis revealed that the unconditional additive effects for the four traits were more significant than unconditional dominance effects, meanwhile, the alternative expressions were also observed between the additive and dominant effects for body weights, total lengths and standard lengths. Conditional analysis showed that the developmental periods with active gene expression for body weights, total lengths, standard lengths and body heights were 15–18, 15 and 21–24, 15 and 24, and 21 and 27 months of age, respectively. The proportions of unconditional/conditional variances indicated that the narrow-sense heritabilities of body weights, total lengths and standard lengths were all increased systematically. The accumulative effects of genes controlling the four quantitative traits were mainly additive effects, suggesting that the selection is more efficient for the genetic improvement of turbots. The conditional genetic procedure is a useful tool to understand the expression of genes controlling developmental quantitative traits at a specific developmental period (t-1→t) during ontogeny. It is also important to determine the appropriate developmental period (t-1→t) for trait measurement in developmental quantitative genetic analysis in fish.

  16. Parent-offspring conflict and co-adaptation: behavioural ecology meets quantitative genetics.

    Science.gov (United States)

    Smiseth, Per T; Wright, Jonathan; Kölliker, Mathias

    2008-08-22

    The evolution of the complex and dynamic behavioural interactions between caring parents and their dependent offspring is a major area of research in behavioural ecology and quantitative genetics. While behavioural ecologists examine the evolution of interactions between parents and offspring in the light of parent-offspring conflict and its resolution, quantitative geneticists explore the evolution of such interactions in the light of parent-offspring co-adaptation due to combined effects of parental and offspring behaviours on fitness. To date, there is little interaction or integration between these two fields. Here, we first review the merits and limitations of each of these two approaches and show that they provide important complementary insights into the evolution of strategies for offspring begging and parental resource provisioning. We then outline how central ideas from behavioural ecology and quantitative genetics can be combined within a framework based on the concept of behavioural reaction norms, which provides a common basis for behavioural ecologists and quantitative geneticists to study the evolution of parent-offspring interactions. Finally, we discuss how the behavioural reaction norm approach can be used to advance our understanding of parent-offspring conflict by combining information about the genetic basis of traits from quantitative genetics with key insights regarding the adaptive function and dynamic nature of parental and offspring behaviours from behavioural ecology.

  17. A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus; Ibánez-Escriche, Noelia; Sorensen, Daniel

    2008-01-01

    In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications...

  18. Genetic Basis of Differential Heat Resistance between Two Species of Congeneric Freshwater Snails: Insights from Quantitative Proteomics and Base Substitution Rate Analysis.

    Science.gov (United States)

    Mu, Huawei; Sun, Jin; Fang, Ling; Luan, Tiangang; Williams, Gray A; Cheung, Siu Gin; Wong, Chris K C; Qiu, Jian-Wen

    2015-10-02

    We compared the heat tolerance, proteomic responses to heat stress, and adaptive sequence divergence in the invasive snail Pomacea canaliculata and its noninvasive congener Pomacea diffusa. The LT50 of P. canaliculata was significantly higher than that of P. diffusa. More than 3350 proteins were identified from the hepatopancreas of the snails exposed to acute and chronic thermal stress using iTRAQ-coupled mass spectrometry. Acute exposure (3 h exposure at 37 °C with 25 °C as control) resulted in similar numbers (27 in P. canaliculata and 23 in P. diffusa) of differentially expressed proteins in the two species. Chronic exposure (3 weeks of exposure at 35 °C with 25 °C as control) caused differential expression of more proteins (58 in P. canaliculata and 118 in P. diffusa), with many of them related to restoration of damaged molecules, ubiquitinating dysfunctional molecules, and utilization of energy reserves in both species; but only in P. diffusa was there a shift from carbohydrate to lipid catabolism. Analysis of orthologous genes encoding the differentially expressed proteins revealed two genes having clear evidence of positive selection (Ka/Ks > 1) and seven candidates for more detailed analysis of positive selection (Ka/Ks between 0.5 and 1). These nine genes are related to energy metabolism, cellular oxidative homeostasis, signaling, and binding processes. Overall, the proteomic and base substitution rate analyses indicate genetic basis of differential resistance to heat stress between the two species, and such differences could affect their further range expansion in a warming climate.

  19. Automated identification of pathways from quantitative genetic interaction data

    Science.gov (United States)

    Battle, Alexis; Jonikas, Martin C; Walter, Peter; Weissman, Jonathan S; Koller, Daphne

    2010-01-01

    High-throughput quantitative genetic interaction (GI) measurements provide detailed information regarding the structure of the underlying biological pathways by reporting on functional dependencies between genes. However, the analytical tools for fully exploiting such information lag behind the ability to collect these data. We present a novel Bayesian learning method that uses quantitative phenotypes of double knockout organisms to automatically reconstruct detailed pathway structures. We applied our method to a recent data set that measures GIs for endoplasmic reticulum (ER) genes, using the unfolded protein response as a quantitative phenotype. The results provided reconstructions of known functional pathways including N-linked glycosylation and ER-associated protein degradation. It also contained novel relationships, such as the placement of SGT2 in the tail-anchored biogenesis pathway, a finding that we experimentally validated. Our approach should be readily applicable to the next generation of quantitative GI data sets, as assays become available for additional phenotypes and eventually higher-level organisms. PMID:20531408

  20. Quantitative genetic-interaction mapping in mammalian cells

    Science.gov (United States)

    Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

    2013-01-01

    Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

  1. Quantitative Genetic Interactions Reveal Layers of Biological Modularity

    Science.gov (United States)

    Beltrao, Pedro; Cagney, Gerard; Krogan, Nevan J.

    2010-01-01

    In the past, biomedical research has embraced a reductionist approach, primarily focused on characterizing the individual components that comprise a system of interest. Recent technical developments have significantly increased the size and scope of data describing biological systems. At the same time, advances in the field of systems biology have evoked a broader view of how the underlying components are interconnected. In this essay, we discuss how quantitative genetic interaction mapping has enhanced our view of biological systems, allowing a deeper functional interrogation at different biological scales. PMID:20510918

  2. Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches.

    Science.gov (United States)

    Bérénos, Camillo; Ellis, Philip A; Pilkington, Jill G; Pemberton, Josephine M

    2014-07-01

    The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long-term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation-derived maternal links and microsatellite-derived paternal links; (ii) Pedigree 2, using SNP-derived assignment of both maternity and paternity; and (iii) whole-genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics

  3. Quantitative Genetic Analysis of Biomass and Wood Chemistry of Populus under Different Nitrogen Levels

    Energy Technology Data Exchange (ETDEWEB)

    Novaes, E.; Osorio, L.; Drost, D. R.; Miles, B. L.; Boaventura-Novaes, C. R. D.; Benedict, C.; Dervinis, C.; Yu, Q.; Sykes, R.; Davis, M.; Martin, T. A.; Peter, G. F.; Kirst, M.

    2009-01-01

    The genetic control of carbon allocation and partitioning in woody perennial plants is poorly understood despite its importance for carbon sequestration, biofuels and other wood-based industries. It is also unclear how environmental cues, such as nitrogen availability, impact the genes that regulate growth, biomass allocation and wood composition in trees. We phenotyped 396 clonally replicated genotypes of an interspecific pseudo-backcross pedigree of Populus for wood composition and biomass traits in above- and below-ground organs. The loci that regulate growth, carbon allocation and partitioning under two nitrogen conditions were identified, defining the contribution of environmental cues to their genetic control. Sixty-three quantitative trait loci were identified for the 20 traits analyzed. The majority of quantitative trait loci are specific to one of the two nitrogen treatments, demonstrating significant nitrogen-dependent genetic control. A highly significant genetic correlation was observed between plant growth and lignin/cellulose composition, and quantitative trait loci co-localization identified the genomic position of potential pleiotropic regulators. Pleiotropic loci linking higher growth rates to wood with less lignin are excellent targets to engineer tree germplasm improved for pulp, paper and cellulosic ethanol production. The causative genes are being identified with a genetical genomics approach.

  4. Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici.

    Science.gov (United States)

    Stewart, Ethan L; Croll, Daniel; Lendenmann, Mark H; Sanchez-Vallet, Andrea; Hartmann, Fanny E; Palma-Guerrero, Javier; Ma, Xin; McDonald, Bruce A

    2016-11-21

    We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High-throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site-associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large- and small-effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large-effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.

  5. From classical genetics to quantitative genetics to systems biology: modeling epistasis.

    Directory of Open Access Journals (Sweden)

    David L Aylor

    2008-03-01

    Full Text Available Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which is the interaction between alleles at different loci. We propose a framework for estimating and interpreting epistasis from a classical experiment that combines the strengths of each approach. A regression analysis step accommodates the quantitative nature of expression measurements by estimating the effect of gene deletions plus any interaction. Effects are selected by significance such that a reduced model describes each expression trait. We show how the resulting models correspond to specific hierarchical relationships between two regulator genes and a target gene. These relationships are the basic units of genetic pathways and genomic system diagrams. Our approach can be extended to analyze data from a variety of experiments, multiple loci, and multiple environments.

  6. Genetic diversity among exotic cotton accessions as for qualitative and quantitative traits.

    Science.gov (United States)

    de Carvalho, L P; Farias, F J C; Rodrigues, J I S; Suassuna, N D; Teodoro, P E

    2017-02-08

    Studying genetic diversity among a group of genotypes is important in genetic breeding because identifying hybrid combinations of greater heterotic effect also increases the chance of obtaining plants with favorable allele combinations in an intra-population selection program. The objective of this study was to compare different types of long and extra-long staple cotton and their genetic diversity in relation to the fiber traits and some agronomic traits in order to grant breeding programs. Diversity analysis among 29 cotton accessions based on qualitative and quantitative traits and joint including qualitative and quantitative traits was performed. Analysis based on qualitative and quantitative traits and joint met the accessions in three, two, and three groups, respectively. The cross between genotypes Giza 59 and Pima unknown was the most promising to generate segregating populations, comprising simultaneously resistance (based on molecular markers) to blue disease and bacterial blight, partial resistance to root-knot nematode, smaller size, in addition to good fiber characteristics. These populations can be used in recurrent selection programs as donors of alleles for development of long-staple cotton genotypes.

  7. Genetic bases for glaucoma.

    Science.gov (United States)

    Fuse, Nobuo

    2010-05-01

    Glaucoma is the leading cause of visual impairment and blindness throughout the world. Primary open angle glaucoma (POAG; MIM 137760) is the main type of glaucoma in most populations, and more than 20 genetic loci for POAG have been reported. Only three causative genes have been identified in these loci, viz. myocilin (MYOC), optineurin (OPTN), and WD repeat domain 36 (WDR36). However, mutations in these genes account for only a small percentage of the patients with POAG. Some of these glaucoma cases have a Mendelian inheritance pattern, and a considerable fraction of the cases result from a large number of variants in several genes each contributing small effects. Glaucoma is considered to be a common disease such as diabetes mellitus, coronary disease, Crohn disease, and several( )common cancers. The main technological approaches used to identify the genes associated with glaucoma are the candidate gene approach, linkage analysis, case-control association study, and genome-wide association study. Association studies have found about 27 genes related to POAG, but the glaucoma-causing effects of these genes need to be investigated in more detail. The current trend is to use case-control association studies or genome-wide association studies to map the genes associated with glaucoma. Such studies are expected to greatly advance our understanding of the genetic basis of glaucoma, and to provide information on the effectiveness of glaucoma therapy. This review gives an overview on the genetic aspects of glaucoma.

  8. A census of cells in time: quantitative genetics meets developmental biology.

    Science.gov (United States)

    Chitwood, Daniel H; Sinha, Neelima R

    2013-02-01

    Quantitative genetics has become a popular method for determining the genetic basis of natural variation. Combined with genomic methods, it provides a tool for discerning the genetic basis of gene expression. So-called genetical genomics approaches yield a wealth of genomic information, but by necessity, because of cost and time, fail to resolve the differences between organs, tissues, and/or cell types. Similarly, quantitative approaches in development that might potentially address these issues are seldom applied to quantitative genetics. We discuss recent advances in cell type-specific isolation methods, the quantitative analysis of phenotype, and developmental modeling that are compatible with quantitative genetics and, with time, promise to bridge the gap between these two powerful disciplines yielding unprecedented biological insight.

  9. Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

    Directory of Open Access Journals (Sweden)

    Jaeyong Yee

    2015-01-01

    Full Text Available A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait.

  10. Entering the second century of maize quantitative genetics

    Science.gov (United States)

    Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architectur...

  11. A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Saad M. Darwish

    2016-10-01

    Full Text Available Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions. The problem of expanding procedures to handle quantitative data has been attracting the attention of many researchers. The algorithms regularly discretize the attribute fields into sharp intervals, and then implement uncomplicated algorithms established for Boolean attributes. Fuzzy association rules mining approaches are intended to defeat such shortcomings based on the fuzzy set theory. Furthermore, most of the current algorithms in the direction of this topic are based on very tiring search methods to govern the ideal support and confidence thresholds that agonize from risky computational cost in searching association rules. To accelerate quantitative multilevel association rules searching and escape the extreme computation, in this paper, we propose a new genetic-based method with significant innovation to determine threshold values for frequent item sets. In this approach, a sophisticated coding method is settled, and the qualified confidence is employed as the fitness function. With the genetic algorithm, a comprehensive search can be achieved and system automation is applied, because our model does not need the user-specified threshold of minimum support. Experiment results indicate that the recommended algorithm can powerfully generate non-redundant fuzzy multilevel association rules.

  12. Advancing genetic theory and application by metabolic quantitative trait loci analysis.

    Science.gov (United States)

    Kliebenstein, Danielj

    2009-06-01

    This review describes recent advances in the analysis of metabolism using quantitative genetics. It focuses on how recent metabolic quantitative trait loci (QTL) studies enhance our understanding of the genetic architecture underlying naturally variable phenotypes and the impact of this fundamental research on agriculture, specifically crop breeding. In particular, the role of whole-genome duplications in generating quantitative genetic variation within a species is highlighted and the potential uses of this phenomenon presented. Additionally, the review describes how new observations from metabolic QTL mapping analyses are helping to shape and expand the concepts of genetic epistasis.

  13. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis

    Science.gov (United States)

    Huang, Wen; Mackay, Trudy F. C.

    2016-01-01

    Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs). Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA), providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits. PMID:27812106

  14. The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis.

    Directory of Open Access Journals (Sweden)

    Wen Huang

    2016-11-01

    Full Text Available Classical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals without knowing the identities of quantitative trait loci (QTLs. Many studies have found a large proportion of quantitative trait variation can be attributed to the additive genetic variance (VA, providing the basis for claims that non-additive gene actions are unimportant. In this study, we show that arbitrarily defined parameterizations of genetic effects seemingly consistent with non-additive gene actions can also capture the majority of genetic variation. This reveals a logical flaw in using the relative magnitudes of variance components to indicate the relative importance of additive and non-additive gene actions. We discuss the implications and propose that variance component analyses should not be used to infer the genetic architecture of quantitative traits.

  15. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2015-01-01

    Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  16. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics.

    Science.gov (United States)

    de Vlaming, Ronald; Groenen, Patrick J F

    2015-01-01

    In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to commonly used methods in animal breeding, (iii) the computational feasibility, and (iv) the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis). Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N < 10,000) the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP). However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  17. Functional genomics bridges the gap between quantitative genetics and molecular biology.

    Science.gov (United States)

    Lappalainen, Tuuli

    2015-10-01

    Deep characterization of molecular function of genetic variants in the human genome is becoming increasingly important for understanding genetic associations to disease and for learning to read the regulatory code of the genome. In this paper, I discuss how recent advances in both quantitative genetics and molecular biology have contributed to understanding functional effects of genetic variants, lessons learned from eQTL studies, and future challenges in this field.

  18. [The study of tomato fruit weight quantitative trait locus and its application in genetics teaching].

    Science.gov (United States)

    Wang, Haiyan

    2015-08-01

    The classical research cases, which have greatly promoted the development of genetics in history, can be combined with the content of courses in genetics teaching to train students' ability of scientific thinking and genetic analysis. The localization and clone of gene controlling tomato fruit weight is a pioneer work in quantitative trait locus (QTL) studies and represents a complete process of QTL research in plants. Application of this integrated case in genetics teaching, which showed a wonderful process of scientific discovery and the fascination of genetic research, has inspired students' interest in genetics and achieved a good teaching effect.

  19. A quantitative genetic analysis of intermediate asthma phenotypes

    DEFF Research Database (Denmark)

    Thomsen, S.F.; Ferreira, M.A.R.; Kyvik, K.O.

    2009-01-01

    to the observed data using maximum likelihood methods. RESULTS: Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most...

  20. A century after Fisher: time for a new paradigm in quantitative genetics.

    Science.gov (United States)

    Nelson, Ronald M; Pettersson, Mats E; Carlborg, Örjan

    2013-12-01

    Quantitative genetics traces its roots back through more than a century of theory, largely formed in the absence of directly observable genotype data, and has remained essentially unchanged for decades. By contrast, molecular genetics arose from direct observations and is currently undergoing rapid changes, making the amount of available data ever greater. Thus, the two disciplines are disparate both in their origins and their current states, yet they address the same fundamental question: how does the genotype affect the phenotype? The rapidly accumulating genomic data necessitate sophisticated analysis, but many of the current tools are adaptations of methods designed during the early days of quantitative genetics. We argue here that the present analysis paradigm in quantitative genetics is at its limits in regards to unraveling complex traits and it is necessary to re-evaluate the direction that genetic research is taking for the field to realize its full potential.

  1. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci

    NARCIS (Netherlands)

    Jansen, R.C.; Ooijen, J.W. van; Stam, P.; Lister, C.; Dean, C.

    1995-01-01

    The interval mapping method is widely used for the genetic mapping of quantitative trait loci (QTLs), though true resolution of quantitative variation into QTLs is hampered with this method. Separation of QTLs is troublesome, because single-QTL is models are fitted. Further, genotype-by-environment

  2. Genetic mapping of quantitative trait loci in plants - a novel statistical approach.

    NARCIS (Netherlands)

    Jansen, R.C.

    1995-01-01

    Quantitative variation is a feature of many important traits such as yield, quality and disease resistance in crop plants and farm animals, and diseases in humans. The genetic mapping, understanding and manipulation of quantitative trait loci (QTLs) are therefore of prime importance. Only by using g

  3. Integrating Quantitative Genetics and Practical Aspects in a Fish Breeding Network in Denmark

    DEFF Research Database (Denmark)

    Meier, Kristian; Sørensen, Anders Christian; Norberg, Elise;

    simulations are given to show how different practical aspects of a breeding plan can be optimized. By combining quantitative genetic theory with current breeding practice we are able to optimize different breeding plans increasing genetic gain while controlling the level of inbreeding and building up...

  4. [Genetic Bases of Human Comorbidity].

    Science.gov (United States)

    Puzyrev, V P

    2015-04-01

    In this review, the development of ideas focused on the phenomenon of disease combination (comorbidity) in humans is discussed. The genetic bases of the three forms of the phenomenon, comorbidity (syntropias), inverse comorbidity (dystropias), and comorbidity of Mendelian and multifactorial diseases, are analyzed. The results of personal genome-wide association studies of the genetic risk profile that may predispose an individual to cardiovascular disease continuum (CDC), including coronary heart disease, type 2 diabetes, hypertension, and hypercholesterolemia (CDC syntropy), as well as the results of bioinformatic analysis of common genes and the networks of molecular interactions for two (bronchial asthma and pulmonary tuberculosis) diseases rarely found in one patient (dystropy), are presented. The importance of the diseasome and network medicine concepts in the study of comorbidity is emphasized. Promising areas in genomic studies of comorbidities for disease classification and the development of personalized medicine are designated.

  5. Determination of Mycotoxin Production of Fusarium Species in Genetically Modified Maize Varieties by Quantitative Flow Immunocytometry

    Science.gov (United States)

    Bánáti, Hajnalka; Darvas, Béla; Fehér-Tóth, Szilvia; Czéh, Árpád; Székács, András

    2017-01-01

    Levels of mycotoxins produced by Fusarium species in genetically modified (GM) and near-isogenic maize, were determined using multi-analyte, microbead-based flow immunocytometry with fluorescence detection, for the parallel quantitative determination of fumonisin B1, deoxynivalenol, zearalenone, T-2, ochratoxin A, and aflatoxin B1. Maize varieties included the genetic events MON 810 and DAS-59122-7, and their isogenic counterparts. Cobs were artificially infested by F. verticillioides and F. proliferatum conidia, and contained F. graminearum and F. sporotrichoides natural infestation. The production of fumonisin B1 and deoxynivalenol was substantially affected in GM maize lines: F. verticillioides, with the addition of F. graminearum and F. sporotrichoides, produced significantly lower levels of fumonisin B1 (~300 mg·kg−1) in DAS-59122-7 than in its isogenic line (~580 mg·kg−1), while F. proliferatum, in addition to F. graminearum and F. sporotrichoides, produced significantly higher levels of deoxynivalenol (~18 mg·kg−1) in MON 810 than in its isogenic line (~5 mg·kg−1). Fusarium verticillioides, with F. graminearum and F. sporotrichoides, produced lower amounts of deoxynivalenol and zearalenone than F. proliferatum, with F. graminearum and F. sporotrichoides. T-2 toxin production remained unchanged when considering the maize variety. The results demonstrate the utility of the Fungi-Plex™ quantitative flow immunocytometry method, applied for the high throughput parallel determination of the target mycotoxins. PMID:28241411

  6. Contribution and perspectives of quantitative genetics to plant breeding in Brazil

    Directory of Open Access Journals (Sweden)

    Fernando Henrique Ribeiro Barrozo Toledo

    2012-12-01

    Full Text Available The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained inplant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breedersthe possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybridcultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selectionprograms, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improverecommendations.

  7. Genetic mapping of quantitative trait loci (QTLs) with effects on ...

    African Journals Online (AJOL)

    SERVER

    2008-02-05

    Feb 5, 2008 ... 2Department of Crop Protection and Environmental Biology, ... identify genetic loci associated with the expression of resistance to FTh. ... indicated that resistance to FTh may be controlled by ... population or to pyramid resistance into new populations. .... environment and human health (Eigenbrode and.

  8. Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships.

    Science.gov (United States)

    Hasegawa, K; Funatsu, K

    2000-01-01

    Quantitative structure-activity relationship (QSAR) studies based on chemometric techniques are reviewed. Partial least squares (PLS) is introduced as a novel robust method to replace classical methods such as multiple linear regression (MLR). Advantages of PLS compared to MLR are illustrated with typical applications. Genetic algorithm (GA) is a novel optimization technique which can be used as a search engine in variable selection. A novel hybrid approach comprising GA and PLS for variable selection developed in our group (GAPLS) is described. The more advanced method for comparative molecular field analysis (CoMFA) modeling called GA-based region selection (GARGS) is described as well. Applications of GAPLS and GARGS to QSAR and 3D-QSAR problems are shown with some representative examples. GA can be hybridized with nonlinear modeling methods such as artificial neural networks (ANN) for providing useful tools in chemometric and QSAR.

  9. Quantitative Recognizing Dissolved Hydrocarbons with Genetic Algorithm-Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Qu Zhou

    2013-09-01

    Full Text Available Online monitoring of dissolved fault characteristic hydrocarbon gases, such as methane, ethane, ethylene and acetylene in power transformer oil has significant meaning for condition assessment of transformer. Recently, semiconductor tin oxide based gas sensor array has been widely applied in online monitoring apparatus, while cross sensitivity of the gas sensor array is inevitable due to same compositions and similar structures among the four hydrocarbon gases. Based on support vector regression (SVR with genetic algorithm (GA, a new pattern recognition method was proposed to reduce the cross sensitivity of the gas sensor array and further quantitatively recognize the concentration of dissolved hydrocarbon gases. The experimental data from a certain online monitoring device in China is used to illustrate the performance of the proposed GA-SVR model. Experimental results indicate that the GA-SVR method can effectively decrease the cross sensitivity and the regressed data is much more closed to the real values.

  10. Genetic toxicology at the crossroads-from qualitative hazard evaluation to quantitative risk assessment.

    Science.gov (United States)

    White, Paul A; Johnson, George E

    2016-05-01

    Applied genetic toxicology is undergoing a transition from qualitative hazard identification to quantitative dose-response analysis and risk assessment. To facilitate this change, the Health and Environmental Sciences Institute (HESI) Genetic Toxicology Technical Committee (GTTC) sponsored a workshop held in Lancaster, UK on July 10-11, 2014. The event included invited speakers from several institutions and the contents was divided into three themes-1: Point-of-departure Metrics for Quantitative Dose-Response Analysis in Genetic Toxicology; 2: Measurement and Estimation of Exposures for Better Extrapolation to Humans and 3: The Use of Quantitative Approaches in Genetic Toxicology for human health risk assessment (HHRA). A host of pertinent issues were discussed relating to the use of in vitro and in vivo dose-response data, the development of methods for in vitro to in vivo extrapolation and approaches to use in vivo dose-response data to determine human exposure limits for regulatory evaluations and decision-making. This Special Issue, which was inspired by the workshop, contains a series of papers that collectively address topics related to the aforementioned themes. The Issue includes contributions that collectively evaluate, describe and discuss in silico, in vitro, in vivo and statistical approaches that are facilitating the shift from qualitative hazard evaluation to quantitative risk assessment. The use and application of the benchmark dose approach was a central theme in many of the workshop presentations and discussions, and the Special Issue includes several contributions that outline novel applications for the analysis and interpretation of genetic toxicity data. Although the contents of the Special Issue constitutes an important step towards the adoption of quantitative methods for regulatory assessment of genetic toxicity, formal acceptance of quantitative methods for HHRA and regulatory decision-making will require consensus regarding the

  11. Quantitative resistance against Bemisia tabaci in Solanum pennellii:Genetics and metabolomics

    Institute of Scientific and Technical Information of China (English)

    Alejandro F Lucatti; Sjaak van Heusden; Colette Broekgaarden; Roland Mumm; Marcel Dicke; Ben Vosman

    2016-01-01

    The whitefly Bemisia tabaci is a serious threat in tomato cultivation worldwide as all varieties grown today are highly susceptible to this devastating herbivorous insect. Many accessions of the tomato wild relative Solanum pennellii show a high resistance towards B. tabaci. A mapping approach was used to elucidate the genetic background of whitefly-resistance related traits and associated biochemical traits in this species. Minor quantitative trait loci (QTLs) for whitefly adult survival (AS) and oviposition rate (OR) were identified and some were confirmed in an F2BC1 population, where they showed increased percentages of explained variance (more than 30%). Bulked segregant analyses on pools of whitefly-resistant and-susceptible F2 plants enabled the identification of metabolites that correlate either with resistance or susceptibility. Genetic mapping of these metabolites showed that a large number of them co-localize with whitefly-resistance QTLs. Some of these whitefly-resistance QTLs are hotspots for metabolite QTLs. Although a large number of metabolite QTLs correlated to whitefly resistance or suscepti-bility, most of them are yet unknown compounds and further studies are needed to identify the metabolic pathways and genes involved. The results indicate a direct genetic correla-tion between biochemical-based resistance characteristics and reduced whitefly incidence in S. pennellii.

  12. Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

    OpenAIRE

    Sourav Bandyopadhyay; Ryan Kelley; Krogan, Nevan J.; Trey Ideker

    2008-01-01

    Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relat...

  13. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

    Science.gov (United States)

    Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

  14. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in "Brassica rapa" Fast Plants

    Science.gov (United States)

    Batzli, Janet M.; Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dosa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory…

  15. Parameter estimation using the genetic algorithm and its impact on quantitative precipitation forecast

    Directory of Open Access Journals (Sweden)

    Y. H. Lee

    2006-12-01

    Full Text Available In this study, optimal parameter estimations are performed for both physical and computational parameters in a mesoscale meteorological model, and their impacts on the quantitative precipitation forecasting (QPF are assessed for a heavy rainfall case occurred at the Korean Peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when the two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

  16. Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk

    DEFF Research Database (Denmark)

    Buitenhuis, Albert Johannes; Sundekilde, Ulrik; Poulsen, Nina Aagaard;

    2013-01-01

    Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk....... For this purpose, milk samples were collected in mid lactation from 371 Danish Holstein cows in first to third parity. A total of 31 metabolites were detected and identified in bovine milk by using 1H nuclear magnetic resonance (NMR) spectroscopy. Cows were genotyped using a bovine high-density single nucleotide...... polymorphism (SNP) chip. Based on the SNP data, a genomic relationship matrix was calculated and used as a random factor in a model together with 2 fixed factors (herd and lactation stage) to estimate the heritability and breeding value for individual metabolites in the milk. Heritability was in the range of 0...

  17. Genetic influences on attention deficit hyperactivity disorder symptoms from age 2 to 3: A quantitative and molecular genetic investigation

    Directory of Open Access Journals (Sweden)

    Saudino Kimberly J

    2010-12-01

    Full Text Available Abstract Background A twin study design was used to assess the degree to which additive genetic variance influences ADHD symptom scores across two ages during infancy. A further objective in the study was to observe whether genetic association with a number of candidate markers reflects results from the quantitative genetic analysis. Method We have studied 312 twin pairs at two time-points, age 2 and age 3. A composite measure of ADHD symptoms from two parent-rating scales: The Child Behavior Checklist/1.5 - 5 years (CBCL hyperactivity scale and the Revised Rutter Parent Scale for Preschool Children (RRPSPC was used for both quantitative and molecular genetic analyses. Results At ages 2 and 3 ADHD symptoms are highly heritable (h2 = 0.79 and 0.78, respectively with a high level of genetic stability across these ages. However, we also observe a significant level of genetic change from age 2 to age 3. There are modest influences of non-shared environment at each age independently (e2 = 0.22 and 0.21, respectively, with these influences being largely age-specific. In addition, we find modest association signals in DAT1 and NET1 at both ages, along with suggestive specific effects of 5-HTT and DRD4 at age 3. Conclusions ADHD symptoms are heritable at ages 2 and 3. Additive genetic variance is largely shared across these ages, although there are significant new effects emerging at age 3. Results from our genetic association analysis reflect these levels of stability and change and, more generally, suggest a requirement for consideration of age-specific genotypic effects in future molecular studies.

  18. The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

    Directory of Open Access Journals (Sweden)

    Jason A Corwin

    2016-02-01

    Full Text Available The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs and nucleotide-binding site leucine-rich repeat proteins (NLRs, were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60% when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen

  19. Genetic Studies of Quantitative MCI and AD Phenotypes in ADNI: Progress, Opportunities, and Plans

    Science.gov (United States)

    Saykin, Andrew J.; Shen, Li; Yao, Xiaohui; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L.; Ramanan, Vijay K.; Foroud, Tatiana M.; Faber, Kelly M.; Sarwar, Nadeem; Munsie, Leanne M.; Hu, Xiaolan; Soares, Holly D.; Potkin, Steven G.; Thompson, Paul M.; Kauwe, John S.K.; Kaddurah-Daouk, Rima; Green, Robert C.; Toga, Arthur W.; Weiner, Michael W.

    2015-01-01

    INTRODUCTION Genetic data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) has been crucial in advancing the understanding of AD pathophysiology. Here we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing (WES, WGS) data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times and over 300 publications have resulted, including reports of large scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies employed ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first WES and WGS data sets and reports in healthy controls, MCI, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data, and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multi-omics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological

  20. Quantitative genetic analysis of retinal degeneration in the blind cavefish Astyanax mexicanus.

    Directory of Open Access Journals (Sweden)

    Kelly E O'Quin

    Full Text Available The retina is the light-sensitive tissue of the eye that facilitates vision. Mutations within genes affecting eye development and retinal function cause a host of degenerative visual diseases, including retinitis pigmentosa and anophthalmia/microphthalmia. The characin fish Astyanax mexicanus includes both eyed (surface fish and eyeless (cavefish morphs that initially develop eyes with normal retina; however, early in development, the eyes of cavefish degenerate. Since both surface and cave morphs are members of the same species, they serve as excellent evolutionary mutant models with which to identify genes causing retinal degeneration. In this study, we crossed the eyed and eyeless forms of A. mexicanus and quantified the thickness of individual retinal layers among 115 F(2 hybrid progeny. We used next generation sequencing (RAD-seq and microsatellite mapping to construct a dense genetic map of the Astyanax genome, scan for quantitative trait loci (QTL affecting retinal thickness, and identify candidate genes within these QTL regions. The map we constructed for Astyanax includes nearly 700 markers assembled into 25 linkage groups. Based on our scans with this map, we identified four QTL, one each associated with the thickness of the ganglion, inner nuclear, outer plexiform, and outer nuclear layers of the retina. For all but one QTL, cavefish alleles resulted in a clear reduction in the thickness of the affected layer. Comparative mapping of genetic markers within each QTL revealed that each QTL corresponds to an approximately 35 Mb region of the zebrafish genome. Within each region, we identified several candidate genes associated with the function of each affected retinal layer. Our study is the first to examine Astyanax retinal degeneration in the context of QTL mapping. The regions we identify serve as a starting point for future studies on the genetics of retinal degeneration and eye disease using the evolutionary mutant model Astyanax.

  1. The current and future use of ridge regression for prediction in quantitative genetics

    NARCIS (Netherlands)

    R. de Vlaming (Ronald); P.J.F. Groenen (Patrick)

    2015-01-01

    textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge

  2. Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

    Science.gov (United States)

    Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described cow feces-spec...

  3. Multilevel selection 1: Quantitative genetics of inheritance and response to selection

    NARCIS (Netherlands)

    Bijma, P.; Muir, W.M.; Arendonk, van J.A.M.

    2007-01-01

    Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theor

  4. Investigation of the genetic association between quantitative measures of psychosis and schizophrenia

    DEFF Research Database (Denmark)

    Derks, Eske M; Vorstman, Jacob A S; Ripke, Stephan

    2012-01-01

    The presence of subclinical levels of psychosis in the general population may imply that schizophrenia is the extreme expression of more or less continuously distributed traits in the population. In a previous study, we identified five quantitative measures of schizophrenia (positive, negative......, disorganisation, mania, and depression scores). The aim of this study is to examine the association between a direct measure of genetic risk of schizophrenia and the five quantitative measures of psychosis. Estimates of the log of the odds ratios of case/control allelic association tests were obtained from...... the Psychiatric GWAS Consortium (PGC) (minus our sample) which included genome-wide genotype data of 8,690 schizophrenia cases and 11,831 controls. These data were used to calculate genetic risk scores in 314 schizophrenia cases and 148 controls from the Netherlands for whom genotype data and quantitative symptom...

  5. Slow erosion of a quantitative apple resistance to Venturia inaequalis based on an isolate-specific Quantitative Trait Locus.

    Science.gov (United States)

    Caffier, Valérie; Le Cam, Bruno; Al Rifaï, Mehdi; Bellanger, Marie-Noëlle; Comby, Morgane; Denancé, Caroline; Didelot, Frédérique; Expert, Pascale; Kerdraon, Tifenn; Lemarquand, Arnaud; Ravon, Elisa; Durel, Charles-Eric

    2016-10-01

    Quantitative plant resistance affects the aggressiveness of pathogens and is usually considered more durable than qualitative resistance. However, the efficiency of a quantitative resistance based on an isolate-specific Quantitative Trait Locus (QTL) is expected to decrease over time due to the selection of isolates with a high level of aggressiveness on resistant plants. To test this hypothesis, we surveyed scab incidence over an eight-year period in an orchard planted with susceptible and quantitatively resistant apple genotypes. We sampled 79 Venturia inaequalis isolates from this orchard at three dates and we tested their level of aggressiveness under controlled conditions. Isolates sampled on resistant genotypes triggered higher lesion density and exhibited a higher sporulation rate on apple carrying the resistance allele of the QTL T1 compared to isolates sampled on susceptible genotypes. Due to this ability to select aggressive isolates, we expected the QTL T1 to be non-durable. However, our results showed that the quantitative resistance based on the QTL T1 remained efficient in orchard over an eight-year period, with only a slow decrease in efficiency and no detectable increase of the aggressiveness of fungal isolates over time. We conclude that knowledge on the specificity of a QTL is not sufficient to evaluate its durability. Deciphering molecular mechanisms associated with resistance QTLs, genetic determinants of aggressiveness and putative trade-offs within pathogen populations is needed to help in understanding the erosion processes.

  6. Spontaneous mutations and the origin and maintenance of quantitative genetic variation.

    Science.gov (United States)

    Huang, Wen; Lyman, Richard F; Lyman, Rachel A; Carbone, Mary Anna; Harbison, Susan T; Magwire, Michael M; Mackay, Trudy Fc

    2016-05-23

    Mutation and natural selection shape the genetic variation in natural populations. Here, we directly estimated the spontaneous mutation rate by sequencing new Drosophila mutation accumulation lines maintained with minimal natural selection. We inferred strong stabilizing natural selection on quantitative traits because genetic variation among wild-derived inbred lines was much lower than predicted from a neutral model and the mutational effects were much larger than allelic effects of standing polymorphisms. Stabilizing selection could act directly on the traits, or indirectly from pleiotropic effects on fitness. However, our data are not consistent with simple models of mutation-stabilizing selection balance; therefore, further empirical work is needed to assess the balance of evolutionary forces responsible for quantitative genetic variation.

  7. The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

    DEFF Research Database (Denmark)

    Corwin, Jason A; Copeland, Daniel; Feusier, Julie

    2016-01-01

    the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B...... of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total......, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study...

  8. The quantitative genetic basis of polyandry in the parasitoid wasp, Nasonia vitripennis.

    Science.gov (United States)

    Shuker, D M; Phillimore, A J; Burton-Chellew, M N; Hodge, S E; West, S A

    2007-02-01

    Understanding the evolution of female multiple mating (polyandry) is crucial for understanding sexual selection and sexual conflict. Despite this interest, little is known about its genetic basis or whether genetics influences the evolutionary origin or maintenance of polyandry. Here, we explore the quantitative genetic basis of polyandry in the parasitoid wasp Nasonia vitripennis, a species in which female re-mating has been observed to evolve in the laboratory. We performed a quantitative genetic experiment on a recently collected population of wasps. We found low heritabilities of female polyandry (re-mating frequency after 18 h), low heritability of courtship duration and a slightly higher heritability of copulation duration. However, the coefficients of additive genetic variance for these traits were all reasonably large (CV(A)>7.0). We also found considerable dam effects for all traits after controlling for common environment, suggesting either dominance or maternal effects. Our work adds to the evidence that nonadditive genetic effects may influence the evolution of mating behaviour in Nasonia vitripennis, and the evolution of polyandry more generally.

  9. Genetic base of Brazilian irrigated rice cultivars

    Directory of Open Access Journals (Sweden)

    Hudson de Oliveira Rabelo

    2015-08-01

    Full Text Available The aim of this study was to estimate the genetic base of Brazilian irrigated rice cultivars released in the period from 1965 to 2012. The genealogies of the cultivars were obtained based on information from marketing folders, websites, crossings records, and scientific articles. The following factors were calculated: relative genetic contribution (RGC, accumulated genetic contribution (AGC, frequency (in percentage of each ancestor in the genealogy (FAG, number of ancestors that constitute each cultivar (NAC,number of ancestors responsible for 60%, 70%, 80% and 90% of the genetic base (NAGB, and average number of ancestor per cultivar (ANAC. The cultivars were also grouped based on the period of release (1965-1980, 1981-1990, 1991-2000 and 2001-2012. For each grouping, the previously described factors were also estimated. A total of 110 cultivars were studied and it was concluded that the genetic base of Brazilian irrigated rice cultivars is narrow.

  10. Quantitative genetics of shape in cricket wings: developmental integration in a functional structure.

    Science.gov (United States)

    Klingenberg, Christian Peter; Debat, Vincent; Roff, Derek A

    2010-10-01

    The role of developmental and genetic integration for evolution is contentious. One hypothesis states that integration acts as a constraint on evolution, whereas an alternative is that developmental and genetic systems evolve to match the functional modularity of organisms. This study examined a morphological structure, the cricket wing, where developmental and functional modules are discordant, making it possible to distinguish the two alternatives. Wing shape was characterized with geometric morphometrics, quantitative genetic information was extracted using a full-sibling breeding design, and patterns of developmental integration were inferred from fluctuating asymmetry of wing shape. The patterns of genetic, phenotypic, and developmental integration were clearly similar, but not identical. Heritabilities for different shape variables varied widely, but no shape variables were devoid of genetic variation. Simulated selection for specific shape changes produced predicted responses with marked deflections due to the genetic covariance structure. Three hypotheses of modularity according to the wing structures involved in sound production were inconsistent with the genetic, phenotypic, or developmental covariance structure. Instead, there appears to be strong integration throughout the wing. The hypothesis that genetic and developmental integration evolve to match functional modularity can therefore be rejected for this example.

  11. The quantitative basis of the Arabidopsis innate immune system to endemic pathogens depends on pathogen genetics

    DEFF Research Database (Denmark)

    Corwin, Jason A; Copeland, Daniel; Feusier, Julie;

    2016-01-01

    The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used...... the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B....... cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence...

  12. Are Genetically Informed Designs Genetically Informative?: Comment on McGue, Elkins, Walden, and Iacono (2005) and Quantitative Behavioral Genetics

    Science.gov (United States)

    Partridge, Ty

    2005-01-01

    M. McGue, I. Elkins, B. Walden, and W. G. Iacono (see record 2005-14938-011) presented the findings from a twin study examining the relative contributions of genetic and environmental factors to the developmental trajectories of parent-adolescent relationships. From a behavioral genetics perspective, this study is well conceptualized, is well…

  13. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development

    NARCIS (Netherlands)

    Pires, Nuno D.; Bemer, Marian; Müller, Lena M.; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

    2016-01-01

    Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can

  14. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Science.gov (United States)

    Pires, Nuno D; Bemer, Marian; Müller, Lena M; Baroux, Célia; Spillane, Charles; Grossniklaus, Ueli

    2016-01-01

    Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship) theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  15. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Directory of Open Access Journals (Sweden)

    Nuno D Pires

    2016-01-01

    Full Text Available Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  16. Quantitative Genetics Identifies Cryptic Genetic Variation Involved in the Paternal Regulation of Seed Development.

    Directory of Open Access Journals (Sweden)

    Nuno D Pires

    2016-01-01

    Full Text Available Embryonic development requires a correct balancing of maternal and paternal genetic information. This balance is mediated by genomic imprinting, an epigenetic mechanism that leads to parent-of-origin-dependent gene expression. The parental conflict (or kinship theory proposes that imprinting can evolve due to a conflict between maternal and paternal alleles over resource allocation during seed development. One assumption of this theory is that paternal alleles can regulate seed growth; however, paternal effects on seed size are often very low or non-existent. We demonstrate that there is a pool of cryptic genetic variation in the paternal control of Arabidopsis thaliana seed development. Such cryptic variation can be exposed in seeds that maternally inherit a medea mutation, suggesting that MEA acts as a maternal buffer of paternal effects. Genetic mapping using recombinant inbred lines, and a novel method for the mapping of parent-of-origin effects using whole-genome sequencing of segregant bulks, indicate that there are at least six loci with small, paternal effects on seed development. Together, our analyses reveal the existence of a pool of hidden genetic variation on the paternal control of seed development that is likely shaped by parental conflict.

  17. The quantitative genetics of indirect genetic effects: a selective review of modelling issues : Review

    NARCIS (Netherlands)

    Bijma, P.

    2014-01-01

    Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits sub

  18. The quantitative genetic architecture of the bold-shy continuum in zebrafish, Danio rerio.

    Directory of Open Access Journals (Sweden)

    Mary E Oswald

    Full Text Available In studies of consistent individual differences (personality along the bold-shy continuum, a pattern of behavioral correlations frequently emerges: individuals towards the bold end of the continuum are more likely to utilize risky habitat, approach potential predators, and feed under risky conditions. Here, we address the hypothesis that observed phenotypic correlations among component behaviors of the bold-shy continuum are a result of underlying genetic correlations (quantitative genetic architecture. We used a replicated three-generation pedigree of zebrafish (Danio rerio to study three putative components of the bold-shy continuum: horizontal position, swim level, and feeding latency. We detected significant narrow-sense heritabilities as well as significant genetic and phenotypic correlations among all three behaviors, such that fish selected for swimming at the front of the tank swam closer to the observer, swam higher in the water column, and fed more quickly than fish selected for swimming at the back of the tank. Further, the lines varied in their initial open field behavior (swim level and activity level. The quantitative genetic architecture of the bold-shy continuum indicates that the multivariate behavioral phenotype characteristic of a "bold" personality type may be a result of correlated evolution via underlying genetic correlations.

  19. Quantitative genetics theory for genomic selection and efficiency of breeding value prediction in open-pollinated populations

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2016-06-01

    Full Text Available ABSTRACT To date, the quantitative genetics theory for genomic selection has focused mainly on the relationship between marker and additive variances assuming one marker and one quantitative trait locus (QTL. This study extends the quantitative genetics theory to genomic selection in order to prove that prediction of breeding values based on thousands of single nucleotide polymorphisms (SNPs depends on linkage disequilibrium (LD between markers and QTLs, assuming dominance. We also assessed the efficiency of genomic selection in relation to phenotypic selection, assuming mass selection in an open-pollinated population, all QTLs of lower effect, and reduced sample size, based on simulated data. We show that the average effect of a SNP substitution is proportional to LD measure and to average effect of a gene substitution for each QTL that is in LD with the marker. Weighted (by SNP frequencies and unweighted breeding value predictors have the same accuracy. Efficiency of genomic selection in relation to phenotypic selection is inversely proportional to heritability. Accuracy of breeding value prediction is not affected by the dominance degree and the method of analysis, however, it is influenced by LD extent and magnitude of additive variance. The increase in the number of markers asymptotically improved accuracy of breeding value prediction. The decrease in the sample size from 500 to 200 did not reduce considerably accuracy of breeding value prediction.

  20. Study of quantitative genetics of gum arabic production complicated by variability in ploidy level of Acacia senegal (L.) Willd

    DEFF Research Database (Denmark)

    Diallo, Adja Madjiguene; Nielsen, Lene Rostgaard; Hansen, Jon Kehlet;

    2015-01-01

    sibs, while the open-pollinated families of polyploids showed low variation within families. The difference in sibling relationship observed between ploidy levels complicated estimation of genetic parameters. However, based on the diploid trees, we conclude that heritability in gum arabic production......Gum arabic is an important international commodity produced by trees of Acacia senegal across Sahelian Africa, but documented results of breeding activities are limited. The objective of this study was to provide reliable estimates of quantitative genetic parameters in order to shed light...... on the breeding potential for improvement of gum yield and quality. For this purpose, we measured growth on 617 offspring from 60 open-pollinated trees after 18 years, and gum yield and quality based on two seasons, 18 and 19 years after establishment. Genotyping with eight microsatellite markers revealed...

  1. The first genetic map of the American cranberry: exploration of synteny conservation and quantitative trait loci.

    Science.gov (United States)

    Georgi, Laura; Johnson-Cicalese, Jennifer; Honig, Josh; Das, Sushma Parankush; Rajah, Veeran D; Bhattacharya, Debashish; Bassil, Nahla; Rowland, Lisa J; Polashock, James; Vorsa, Nicholi

    2013-03-01

    The first genetic map of cranberry (Vaccinium macrocarpon) has been constructed, comprising 14 linkage groups totaling 879.9 cM with an estimated coverage of 82.2 %. This map, based on four mapping populations segregating for field fruit-rot resistance, contains 136 distinct loci. Mapped markers include blueberry-derived simple sequence repeat (SSR) and cranberry-derived sequence-characterized amplified region markers previously used for fingerprinting cranberry cultivars. In addition, SSR markers were developed near cranberry sequences resembling genes involved in flavonoid biosynthesis or defense against necrotrophic pathogens, or conserved orthologous set (COS) sequences. The cranberry SSRs were developed from next-generation cranberry genomic sequence assemblies; thus, the positions of these SSRs on the genomic map provide information about the genomic location of the sequence scaffold from which they were derived. The use of SSR markers near COS and other functional sequences, plus 33 SSR markers from blueberry, facilitates comparisons of this map with maps of other plant species. Regions of the cranberry map were identified that showed conservation of synteny with Vitis vinifera and Arabidopsis thaliana. Positioned on this map are quantitative trait loci (QTL) for field fruit-rot resistance (FFRR), fruit weight, titratable acidity, and sound fruit yield (SFY). The SFY QTL is adjacent to one of the fruit weight QTL and may reflect pleiotropy. Two of the FFRR QTL are in regions of conserved synteny with grape and span defense gene markers, and the third FFRR QTL spans a flavonoid biosynthetic gene.

  2. Quantitative genetics model as the unifying model for defining genomic relationship and inbreeding coefficient.

    Science.gov (United States)

    Wang, Chunkao; Da, Yang

    2014-01-01

    The traditional quantitative genetics model was used as the unifying approach to derive six existing and new definitions of genomic additive and dominance relationships. The theoretical differences of these definitions were in the assumptions of equal SNP effects (equivalent to across-SNP standardization), equal SNP variances (equivalent to within-SNP standardization), and expected or sample SNP additive and dominance variances. The six definitions of genomic additive and dominance relationships on average were consistent with the pedigree relationships, but had individual genomic specificity and large variations not observed from pedigree relationships. These large variations may allow finding least related genomes even within the same family for minimizing genomic relatedness among breeding individuals. The six definitions of genomic relationships generally had similar numerical results in genomic best linear unbiased predictions of additive effects (GBLUP) and similar genomic REML (GREML) estimates of additive heritability. Predicted SNP dominance effects and GREML estimates of dominance heritability were similar within definitions assuming equal SNP effects or within definitions assuming equal SNP variance, but had differences between these two groups of definitions. We proposed a new measure of genomic inbreeding coefficient based on parental genomic co-ancestry coefficient and genomic additive correlation as a genomic approach for predicting offspring inbreeding level. This genomic inbreeding coefficient had the highest correlation with pedigree inbreeding coefficient among the four methods evaluated for calculating genomic inbreeding coefficient in a Holstein sample and a swine sample.

  3. Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

    Science.gov (United States)

    Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

    2016-01-01

    Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

  4. Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

    Science.gov (United States)

    In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

  5. Uncovering the genetic signature of quantitative trait evolution with replicated time series data.

    Science.gov (United States)

    Franssen, S U; Kofler, R; Schlötterer, C

    2017-01-01

    The genetic architecture of adaptation in natural populations has not yet been resolved: it is not clear to what extent the spread of beneficial mutations (selective sweeps) or the response of many quantitative trait loci drive adaptation to environmental changes. Although much attention has been given to the genomic footprint of selective sweeps, the importance of selection on quantitative traits is still not well studied, as the associated genomic signature is extremely difficult to detect. We propose 'Evolve and Resequence' as a promising tool, to study polygenic adaptation of quantitative traits in evolving populations. Simulating replicated time series data we show that adaptation to a new intermediate trait optimum has three characteristic phases that are reflected on the genomic level: (1) directional frequency changes towards the new trait optimum, (2) plateauing of allele frequencies when the new trait optimum has been reached and (3) subsequent divergence between replicated trajectories ultimately leading to the loss or fixation of alleles while the trait value does not change. We explore these 3 phase characteristics for relevant population genetic parameters to provide expectations for various experimental evolution designs. Remarkably, over a broad range of parameters the trajectories of selected alleles display a pattern across replicates, which differs both from neutrality and directional selection. We conclude that replicated time series data from experimental evolution studies provide a promising framework to study polygenic adaptation from whole-genome population genetics data.

  6. Multilevel selection 1: Quantitative genetics of inheritance and response to selection.

    Science.gov (United States)

    Bijma, Piter; Muir, William M; Van Arendonk, Johan A M

    2007-01-01

    Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theory accounting for interaction among individuals and selection acting on multiple levels. Consequently, current quantitative genetic theory fails to explain why some traits do not respond to selection among individuals, but respond greatly to selection among groups. Understanding the full impacts of heritable interactions on the outcomes of selection requires a quantitative genetic framework including all levels of selection and relatedness. Here we present such a framework and provide expressions for the response to selection. Results show that interaction among individuals may create substantial heritable variation, which is hidden to classical analyses. Selection acting on higher levels of organization captures this hidden variation and therefore always yields positive response, whereas individual selection may yield response in the opposite direction. Our work provides testable predictions of response to multilevel selection and reduces to classical theory in the absence of interaction. Statistical methodology provided elsewhere enables empirical application of our work to both natural and domestic populations.

  7. EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS.

    Science.gov (United States)

    Bürger, Reinhard; Lynch, Michael

    1995-02-01

    Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation. © 1995 The Society for the Study of Evolution.

  8. Inheritance of 18 quantitative dermatoglyphic traits based on factors in MZ and DZ twins.

    Science.gov (United States)

    Karmakar, Bibha; Malkin, Ida; Kobyliansky, Eugene

    2010-01-01

    18 quantitative finger and palmar dermatoglyphic traits were analyzed with the aim of determining genetic effects and common familial environmental influences on a large (358 nuclear pedigrees) number of twins (MZ and DZ). Genetic analysis based on principal factors includes variance and bivariate variance decomposition analysis. Especially, Factor 1 (digital pattern size) is remarkable, due to its degree of universality. The results of genetic analysis revealed all three extracted factors have significant proportion of additive genetic variance (93.5% to 72.9%). The main results of bivariate variance decomposition analysis appears significant correlation in residual variance between digital pattern size factor (Factor 1) versus finger pattern intensity factor (Factor 4), and palmar main lines factor (Factor 2) verses a-b ridge count (Factor 3), but there was no significant correlation in the genetic variance of factors.

  9. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2005-12-01

    Full Text Available Abstract With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The twoWeibull baseline parameters were updated jointly using a Metropolis-Hastingstep. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  10. A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The two Weibull baseline parameters were updated jointly using a Metropolis-Hasting step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.

  11. Modeling development and quantitative trait mapping reveal independent genetic modules for leaf size and shape.

    Science.gov (United States)

    Baker, Robert L; Leong, Wen Fung; Brock, Marcus T; Markelz, R J Cody; Covington, Michael F; Devisetty, Upendra K; Edwards, Christine E; Maloof, Julin; Welch, Stephen; Weinig, Cynthia

    2015-10-01

    Improved predictions of fitness and yield may be obtained by characterizing the genetic controls and environmental dependencies of organismal ontogeny. Elucidating the shape of growth curves may reveal novel genetic controls that single-time-point (STP) analyses do not because, in theory, infinite numbers of growth curves can result in the same final measurement. We measured leaf lengths and widths in Brassica rapa recombinant inbred lines (RILs) throughout ontogeny. We modeled leaf growth and allometry as function valued traits (FVT), and examined genetic correlations between these traits and aspects of phenology, physiology, circadian rhythms and fitness. We used RNA-seq to construct a SNP linkage map and mapped trait quantitative trait loci (QTL). We found genetic trade-offs between leaf size and growth rate FVT and uncovered differences in genotypic and QTL correlations involving FVT vs STPs. We identified leaf shape (allometry) as a genetic module independent of length and width and identified selection on FVT parameters of development. Leaf shape is associated with venation features that affect desiccation resistance. The genetic independence of leaf shape from other leaf traits may therefore enable crop optimization in leaf shape without negative effects on traits such as size, growth rate, duration or gas exchange.

  12. WOMBAT: a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).

    Science.gov (United States)

    Meyer, Karin

    2007-11-01

    WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses. Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from (http://agbu. une.edu.au/~kmeyer/wombat.html).

  13. Validation of PCR methods for quantitation of genetically modified plants in food.

    Science.gov (United States)

    Hübner, P; Waiblinger, H U; Pietsch, K; Brodmann, P

    2001-01-01

    For enforcement of the recently introduced labeling threshold for genetically modified organisms (GMOs) in food ingredients, quantitative detection methods such as quantitative competitive (QC-PCR) and real-time PCR are applied by official food control laboratories. The experiences of 3 European food control laboratories in validating such methods were compared to describe realistic performance characteristics of quantitative PCR detection methods. The limit of quantitation (LOQ) of GMO-specific, real-time PCR was experimentally determined to reach 30-50 target molecules, which is close to theoretical prediction. Starting PCR with 200 ng genomic plant DNA, the LOQ depends primarily on the genome size of the target plant and ranges from 0.02% for rice to 0.7% for wheat. The precision of quantitative PCR detection methods, expressed as relative standard deviation (RSD), varied from 10 to 30%. Using Bt176 corn containing test samples and applying Bt176 specific QC-PCR, mean values deviated from true values by -7to 18%, with an average of 2+/-10%. Ruggedness of real-time PCR detection methods was assessed in an interlaboratory study analyzing commercial, homogeneous food samples. Roundup Ready soybean DNA contents were determined in the range of 0.3 to 36%, relative to soybean DNA, with RSDs of about 25%. Taking the precision of quantitative PCR detection methods into account, suitable sample plans and sample sizes for GMO analysis are suggested. Because quantitative GMO detection methods measure GMO contents of samples in relation to reference material (calibrants), high priority must be given to international agreements and standardization on certified reference materials.

  14. The quantitative genetics of incipient speciation: heritability and genetic correlations of skeletal traits in populations of diverging Favia fragum ecomorphs.

    Science.gov (United States)

    Carlon, David B; Budd, Ann F; Lippé, Catherine; Andrew, Rose L

    2011-12-01

    Recent speciation events provide potential opportunities to understand the microevolution of reproductive isolation. We used a marker-based approach and a common garden to estimate the additive genetic variation in skeletal traits in a system of two ecomorphs within the coral species Favia fragum: a Tall ecomorph that is a seagrass specialist, and a Short ecomorph that is most abundant on coral reefs. Considering both ecomorphs, we found significant narrow-sense heritability (h(2) ) in a suite of measurements that define corallite architecture, and could partition additive and nonadditive variation for some traits. We found positive genetic correlations for homologous height and length measurements among different types of vertical plates (costosepta) within corallites, but negative correlations between height and length within, as well as between costosepta. Within ecomorphs, h(2) estimates were generally lower, compared to the combined ecomorph analysis. Marker-based estimates of h(2) were comparable to broad-sense heritability (H) obtained from parent-offspring regressions in a common garden for most traits, and similar genetic co-variance matrices for common garden and wild populations may indicate relatively small G × E interactions. The patterns of additive genetic variation in this system invite hypotheses of divergent selection or genetic drift as potential evolutionary drivers of reproductive isolation.

  15. 59. Cold Spring Harbor symposium on quantitative biology: Molecular genetics of cancer

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    Investigation of the mechanistic aspects of cancer has its roots in the studies on tumor viruses and their effects on cell proliferation, function, and growth. This outstanding progress was well documented in previous Cold Spring Harbor Symposia on Quantitative Biology. In the early to mid 1980s, progress on the development of chromosome mapping strategies and the accumulation of DNA probes that identified polymorphisms, encouraged by the international Human Genome Project, enabled the identification of other genes that contributed to familial inheritance of high susceptibility to specific cancers. This approach was very successful and led to a degree of optimism that one aspect of cancer, the multistep genetic process from early neoplasia to metastatic tumors, was beginning to be understood. It therefore seemed appropriate that the 59th Symposium on Quantitative Biology focus attention on the Molecular Genetics of Cancer. The concept was to combine the exciting progress on the identification of new genetic alterations in human tumor cells with studies on the function of the cancer gene products and how they go awry in tumor cells.

  16. Quantitative genetic analysis indicates natural selection on leaf phenotypes across wild tomato species (Solanum sect. Lycopersicon; Solanaceae).

    Science.gov (United States)

    Muir, Christopher D; Pease, James B; Moyle, Leonie C

    2014-12-01

    Adaptive evolution requires both raw genetic material and an accessible path of high fitness from one fitness peak to another. In this study, we used an introgression line (IL) population to map quantitative trait loci (QTL) for leaf traits thought to be associated with adaptation to precipitation in wild tomatoes (Solanum sect. Lycopersicon; Solanaceae). A QTL sign test showed that several traits likely evolved under directional natural selection. Leaf traits correlated across species do not share a common genetic basis, consistent with a scenario in which selection maintains trait covariation unconstrained by pleiotropy or linkage disequilibrium. Two large effect QTL for stomatal distribution colocalized with key genes in the stomatal development pathway, suggesting promising candidates for the molecular bases of adaptation in these species. Furthermore, macroevolutionary transitions between vastly different stomatal distributions may not be constrained when such large-effect mutations are available. Finally, genetic correlations between stomatal traits measured in this study and data on carbon isotope discrimination from the same ILs support a functional hypothesis that the distribution of stomata affects the resistance to CO2 diffusion inside the leaf, a trait implicated in climatic adaptation in wild tomatoes. Along with evidence from previous comparative and experimental studies, this analysis indicates that leaf traits are an important component of climatic niche adaptation in wild tomatoes and demonstrates that some trait transitions between species could have involved few, large-effect genetic changes, allowing rapid responses to new environmental conditions.

  17. Characterization of sweet cassava accessions based on molecular, quantitative and qualitative data

    Directory of Open Access Journals (Sweden)

    Eduardo Alano Vieira

    2011-01-01

    Full Text Available The purpose of this study was to estimate the genetic divergence in sweet cassava accessions by molecular markersand quantitative and qualitative characters, as well as determine the correlation between these estimates. Sixteen sweet cassavaaccessions of the Regional Cassava Germplasm Bank of the Cerrado were evaluated under field conditions, for 13 quantitative and33 qualitative characters. In the laboratory, the accessions were evaluated with RAPD markers. Subsequently, matrixes of geneticdissimilarity/distance among the accessions were estimated based on molecular markers and quantitative and qualitative characters.Besides, the significance of the correlation between the matrixes was estimated. The RAPD, qualitative and quantitative dataindicated the existence of high divergence among the accessions. The divergences estimated by molecular markers and by quantitativetraits were weakly associated with each other and moderately with the divergence estimated by qualitative characters.

  18. Establishment of Quantitative Analysis Method for Genetically Modified Maize Using a Reference Plasmid and Novel Primers

    Science.gov (United States)

    Moon, Gi-Seong; Shin, Weon-Sun

    2012-01-01

    For the quantitative analysis of genetically modified (GM) maize in processed foods, primer sets and probes based on the 35S promoter (p35S), nopaline synthase terminator (tNOS), p35S-hsp70 intron, and zSSIIb gene encoding starch synthase II for intrinsic control were designed. Polymerase chain reaction (PCR) products (80~101 bp) were specifically amplified and the primer sets targeting the smaller regions (80 or 81 bp) were more sensitive than those targeting the larger regions (94 or 101 bp). Particularly, the primer set 35F1-R1 for p35S targeting 81 bp of sequence was even more sensitive than that targeting 101 bp of sequence by a 3-log scale. The target DNA fragments were also specifically amplified from all GM labeled food samples except for one item we tested when 35F1-R1 primer set was applied. A reference plasmid pGMmaize (3 kb) including the smaller PCR products for p35S, tNOS, p35S-hsp70 intron, and the zSSIIb gene was constructed for real-time PCR (RT-PCR). The linearity of standard curves was confirmed by using diluents ranging from 2×101~105 copies of pGMmaize and the R2 values ranged from 0.999~1.000. In the RT-PCR, the detection limit using the novel primer/probe sets was 5 pg of genomic DNA from MON810 line indicating that the primer sets targeting the smaller regions (80 or 81 bp) could be used for highly sensitive detection of foreign DNA fragments from GM maize in processed foods. PMID:24471096

  19. Quantitative analysis of terahertz spectra for illicit drugs using adaptive-range micro-genetic algorithm

    Science.gov (United States)

    Chen, Yi; Ma, Yong; Lu, Zheng; Peng, Bei; Chen, Qin

    2011-08-01

    In the field of anti-illicit drug applications, many suspicious mixture samples might consist of various drug components—for example, a mixture of methamphetamine, heroin, and amoxicillin—which makes spectral identification very difficult. A terahertz spectroscopic quantitative analysis method using an adaptive range micro-genetic algorithm with a variable internal population (ARVIPɛμGA) has been proposed. Five mixture cases are discussed using ARVIPɛμGA driven quantitative terahertz spectroscopic analysis in this paper. The devised simulation results show agreement with the previous experimental results, which suggested that the proposed technique has potential applications for terahertz spectral identifications of drug mixture components. The results show agreement with the results obtained using other experimental and numerical techniques.

  20. Quantitative estimation of activity and quality for collections of functional genetic elements.

    Science.gov (United States)

    Mutalik, Vivek K; Guimaraes, Joao C; Cambray, Guillaume; Mai, Quynh-Anh; Christoffersen, Marc Juul; Martin, Lance; Yu, Ayumi; Lam, Colin; Rodriguez, Cesar; Bennett, Gaymon; Keasling, Jay D; Endy, Drew; Arkin, Adam P

    2013-04-01

    The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

  1. A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Amir Jamshidnezhad

    2011-01-01

    Full Text Available In recent decades computer technology has considerable developed in use of intelligent systems for classification. The development of HCI systems is highly depended on accurate understanding of emotions. However, facial expressions are difficult to classify by a mathematical models because of natural quality. In this paper, quantitative analysis is used in order to find the most effective features movements between the selected facial feature points. Therefore, the features are extracted not only based on the psychological studies, but also based on the quantitative methods to arise the accuracy of recognitions. Also in this model, fuzzy logic and genetic algorithm are used to classify facial expressions. Genetic algorithm is an exclusive attribute of proposed model which is used for tuning membership functions and increasing the accuracy.

  2. Genes and quantitative genetic variation involved with senescence in cells, organs and the whole plant

    Directory of Open Access Journals (Sweden)

    Benoit ePujol

    2015-02-01

    Full Text Available Senescence, the deterioration of morphological, physiological and reproductive functions with age that ends with the death of the organism, was widely studied in plants. Genes were identified that are linked to the deterioration of cells, organs and the whole plant. It is however unclear whether those genes are the source of age dependent deterioration or get activated to regulate such deterioration. Furthermore, it is also unclear whether such genes are active as a direct consequence of age or because they are specifically involved in some developmental stages. At the individual level, it is the relationship between quantitative genetic variation and age that can be used to detect the genetic signature of senescence. Surprisingly, the latter approach was only scarcely applied to plants. This may be the consequence of the demanding requirements for such approaches and/or the fact that most research interest was directed towards plants that avoid senescence. Here, I review those aspects in turn and call for an integrative genetic theory of senescence in plants. Such conceptual development would have implications for the management of plant genetic resources and generate progress on fundamental questions raised by ageing research.

  3. Quantitative genetics of functional characters in Drosophila melanogaster populations subjected to laboratory selection

    Indian Academy of Sciences (India)

    Henrique Teotónio; Margarida Matos; Michael R. Rose

    2004-12-01

    What are the genetics of phenotypes other than fitness, in outbred populations? To answer this question, the quantitative-genetic basis of divergence was characterized for outbred Drosophila melanogaster populations that had previously undergone selection to enhance characters related to fitness. Line-cross analysis using first-generation and second-generation hybrids from reciprocal crosses was conducted for two types of cross, each replicated fivefold. One type of cross was between representatives of the ancestral population, a set of five populations maintained for several hundred generations on a two-week discrete-generation life cycle and a set of five populations adapted to starvation stress. The other type of cross was between the same set of ancestral-representative populations and another set of five populations selected for accelerated development from egg to egg. Developmental time from egg to eclosion, starvation resistance, dry body weight and fecundity at day 14 from egg were fit to regression models estimating single-locus additive and dominant effects, maternal and paternal effects, and digenic additive and dominance epistatic effects. Additive genetic variation explained most of the differences between populations, with additive maternal and cytoplasmic effects also commonly found. Both within-locus and between-locus dominance effects were inferred in some cases, as well as one instance of additive epistasis. Some of these effects may have been caused by linkage disequilibrium. We conclude with a brief discussion concerning the relationship of the genetics of population differentiation to adaptation.

  4. Developments in quantitative genetics methodology as applied to national genetic improvement programs for swine

    Institute of Scientific and Technical Information of China (English)

    Ignacy; MISZTAL

    2005-01-01

    For a long time,purebred pigs were evalua-ted in a nucleus for several growth,meat qualityand reproduction traits including growth,backfatand number of piglets alive[1].The evaluationwas using BLUP with all traits treated as linearand also assuming a normal distribution.Ani-mals down the pyramid were not evaluated;itwas assumed that most if not all of the gains ofselection at the nucleus level transferred to thecommercial level.The selection based on the e-valuations seemed to be successful as all thetraits...

  5. Function Optimization Based on Quantum Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Ying Sun

    2014-01-01

    Full Text Available Optimization method is important in engineering design and application. Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on. It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed, which is called Variable-boundary-coded Quantum Genetic Algorithm (vbQGA in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded chromosomes. Therefore much shorter chromosome strings can be gained. The method of encoding and decoding of chromosome is first described before a new adaptive selection scheme for angle parameters used for rotation gate is put forward based on the core ideas and principles of quantum computation. Eight typical functions are selected to optimize to evaluate the effectiveness and performance of vbQGA against standard Genetic Algorithm (sGA and Genetic Quantum Algorithm (GQA. The simulation results show that vbQGA is significantly superior to sGA in all aspects and outperforms GQA in robustness and solving velocity, especially for multidimensional and complicated functions.

  6. The genetic architecture of heterochronsy as a quantitative trait: lessons from a computational model.

    Science.gov (United States)

    Sun, Lidan; Sang, Mengmeng; Zheng, Chenfei; Wang, Dongyang; Shi, Hexin; Liu, Kaiyue; Guo, Yanfang; Cheng, Tangren; Zhang, Qixiang; Wu, Rongling

    2017-05-30

    Heterochrony is known as a developmental change in the timing or rate of ontogenetic events across phylogenetic lineages. It is a key concept synthesizing development into ecology and evolution to explore the mechanisms of how developmental processes impact on phenotypic novelties. A number of molecular experiments using contrasting organisms in developmental timing have identified specific genes involved in heterochronic variation. Beyond these classic approaches that can only identify single genes or pathways, quantitative models derived from current next-generation sequencing data serve as a more powerful tool to precisely capture heterochronic variation and systematically map a complete set of genes that contribute to heterochronic processes. In this opinion note, we discuss a computational framework of genetic mapping that can characterize heterochronic quantitative trait loci that determine the pattern and process of development. We propose a unifying model that charts the genetic architecture of heterochrony that perceives and responds to environmental perturbations and evolves over geologic time. The new model may potentially enhance our understanding of the adaptive value of heterochrony and its evolutionary origins, providing a useful context for designing new organisms that can best use future resources. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  7. Gene set analyses of genome-wide association studies on 49 quantitative traits measured in a single genetic epidemiology dataset.

    Science.gov (United States)

    Kim, Jihye; Kwon, Ji-Sun; Kim, Sangsoo

    2013-09-01

    Gene set analysis is a powerful tool for interpreting a genome-wide association study result and is gaining popularity these days. Comparison of the gene sets obtained for a variety of traits measured from a single genetic epidemiology dataset may give insights into the biological mechanisms underlying these traits. Based on the previously published single nucleotide polymorphism (SNP) genotype data on 8,842 individuals enrolled in the Korea Association Resource project, we performed a series of systematic genome-wide association analyses for 49 quantitative traits of basic epidemiological, anthropometric, or blood chemistry parameters. Each analysis result was subjected to subsequent gene set analyses based on Gene Ontology (GO) terms using gene set analysis software, GSA-SNP, identifying a set of GO terms significantly associated to each trait (pcorr neuronal or nerve systems.

  8. Quantitative genetics theory for non-inbred populations in linkage disequilibrium

    Directory of Open Access Journals (Sweden)

    José Marcelo Soriano Viana

    2004-01-01

    Full Text Available Although linkage disequilibrium, epistasis and inbreeding are common phenomena in genetic systems that control quantitative traits, theory development and analysis are very complex, especially when they are considered together. The objective of this study is to offer additional quantitative genetics theory to define and analyze, in relation to non-inbred cross pollinating populations, components of genotypic variance, heritabilities and predicted gains, assuming linkage disequilibrium and absence of epistasis. The genotypic variance and its components, additive and due to dominance genetic variances, are invariant over the generations only in regard to completely linked genes and to those in equilibrium. When the population is structured in half-sib families, the additive variance in the parents' generation and the genotypic variance in the population can be estimated. When the population is structured in full-sib families, none of the components of genotypic variance can be estimated. The narrow sense heritability level at plant level can be estimated from the parent-offspring or mid parent-offspring regression. When there is dominance, the narrow sense heritability estimate in the in F2 is biased due to linkage disequilibrium when estimated by the Warner method, but not when estimated by means of the plant F2-family F3 regression. The bias is proportional to the number of pairs of linked genes, without independent assortment, and to the degree of dominance, and tends to be positive when genes in the coupling phase predominate or negative and of higher value when genes in the repulsion phase predominate. Linkage disequilibrium is also cause of bias in estimates of the narrow sense heritabilities at full-sib family mean and at plant within half-sib and full-sib families levels. Generally, the magnitude of the bias is proportional to the number of pairs of genes in disequilibrium and to the frequency of recombining gametes.

  9. Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Mohan Babu

    2014-02-01

    Full Text Available Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI screens can provide insights into the biological role(s of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

  10. Development and evaluation of event-specific quantitative PCR method for genetically modified soybean A2704-12.

    Science.gov (United States)

    Takabatake, Reona; Akiyama, Hiroshi; Sakata, Kozue; Onishi, Mari; Koiwa, Tomohiro; Futo, Satoshi; Minegishi, Yasutaka; Teshima, Reiko; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

    2011-01-01

    A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) soybean event; A2704-12. During the plant transformation, DNA fragments derived from pUC19 plasmid were integrated in A2704-12, and the region was found to be A2704-12 specific. The pUC19-derived DNA sequences were used as primers for the specific detection of A2704-12. We first tried to construct a standard plasmid for A2704-12 quantification using pUC19. However, non-specific signals appeared with both qualitative and quantitative PCR analyses using the specific primers with pUC19 as a template, and we then constructed a plasmid using pBR322. The conversion factor (C(f)), which is required to calculate the amount of the genetically modified organism (GMO), was experimentally determined with two real-time PCR instruments, the Applied Biosystems 7900HT and the Applied Biosystems 7500. The determined C(f) values were both 0.98. The quantitative method was evaluated by means of blind tests in multi-laboratory trials using the two real-time PCR instruments. The limit of quantitation for the method was estimated to be 0.1%. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSD(R)), and the determined bias and RSD(R) values for the method were each less than 20%. These results suggest that the developed method would be suitable for practical analyses for the detection and quantification of A2704-12.

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

    Science.gov (United States)

    Iyer, Janani; Wang, Qingyu; Le, Thanh; Pizzo, Lucilla; Grönke, Sebastian; Ambegaokar, Surendra S.; Imai, Yuzuru; Srivastava, Ashutosh; Troisí, Beatriz Llamusí; Mardon, Graeme; Artero, Ruben; Jackson, George R.; Isaacs, Adrian M.; Partridge, Linda; Lu, Bingwei; Kumar, Justin P.; Girirajan, Santhosh

    2016-01-01

    About two-thirds of the vital genes in the Drosophila genome are involved in eye development, making the fly eye an excellent genetic system to study cellular function and development, neurodevelopment/degeneration, and complex diseases such as cancer and diabetes. We developed a novel computational method, implemented as Flynotyper software (http://flynotyper.sourceforge.net), to quantitatively assess the morphological defects in the Drosophila eye resulting from genetic alterations affecting basic cellular and developmental processes. Flynotyper utilizes a series of image processing operations to automatically detect the fly eye and the individual ommatidium, and calculates a phenotypic score as a measure of the disorderliness of ommatidial arrangement in the fly eye. As a proof of principle, we tested our method by analyzing the defects due to eye-specific knockdown of Drosophila orthologs of 12 neurodevelopmental genes to accurately document differential sensitivities of these genes to dosage alteration. We also evaluated eye images from six independent studies assessing the effect of overexpression of repeats, candidates from peptide library screens, and modifiers of neurotoxicity and developmental processes on eye morphology, and show strong concordance with the original assessment. We further demonstrate the utility of this method by analyzing 16 modifiers of sine oculis obtained from two genome-wide deficiency screens of Drosophila and accurately quantifying the effect of its enhancers and suppressors during eye development. Our method will complement existing assays for eye phenotypes, and increase the accuracy of studies that use fly eyes for functional evaluation of genes and genetic interactions. PMID:26994292

  12. Toward genetics-based virus taxonomy: comparative analysis of a genetics-based classification and the taxonomy of picornaviruses.

    Science.gov (United States)

    Lauber, Chris; Gorbalenya, Alexander E

    2012-04-01

    Virus taxonomy has received little attention from the research community despite its broad relevance. In an accompanying paper (C. Lauber and A. E. Gorbalenya, J. Virol. 86:3890-3904, 2012), we have introduced a quantitative approach to hierarchically classify viruses of a family using pairwise evolutionary distances (PEDs) as a measure of genetic divergence. When applied to the six most conserved proteins of the Picornaviridae, it clustered 1,234 genome sequences in groups at three hierarchical levels (to which we refer as the "GENETIC classification"). In this study, we compare the GENETIC classification with the expert-based picornavirus taxonomy and outline differences in the underlying frameworks regarding the relation of virus groups and genetic diversity that represent, respectively, the structure and content of a classification. To facilitate the analysis, we introduce two novel diagrams. The first connects the genetic diversity of taxa to both the PED distribution and the phylogeny of picornaviruses. The second depicts a classification and the accommodated genetic diversity in a standardized manner. Generally, we found striking agreement between the two classifications on species and genus taxa. A few disagreements concern the species Human rhinovirus A and Human rhinovirus C and the genus Aphthovirus, which were split in the GENETIC classification. Furthermore, we propose a new supergenus level and universal, level-specific PED thresholds, not reached yet by many taxa. Since the species threshold is approached mostly by taxa with large sampling sizes and those infecting multiple hosts, it may represent an upper limit on divergence, beyond which homologous recombination in the six most conserved genes between two picornaviruses might not give viable progeny.

  13. Web Based Genetic Algorithm Using Data Mining

    OpenAIRE

    Ashiqur Rahman; Asaduzzaman Noman; Md. Ashraful Islam; Al-Amin Gaji

    2016-01-01

    This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. Through weighting the feature vectors using a Genetic Algorithm we can optimize the prediction accuracy and get a marked improvement over raw classification. It further shows that when the number of features is few; fea...

  14. Construction of a genetic linkage map of Thlaspi caerulescens and quantitative trait loci analysis of zinc accumulation.

    Science.gov (United States)

    Assunção, Ana G L; Pieper, Bjorn; Vromans, Jaap; Lindhout, Pim; Aarts, Mark G M; Schat, Henk

    2006-01-01

    Zinc (Zn) hyperaccumulation seems to be a constitutive species-level trait in Thlaspi caerulescens. When compared under conditions of equal Zn availability, considerable variation in the degree of hyperaccumulation is observed among accessions originating from different soil types. This variation offers an excellent opportunity for further dissection of the genetics of this trait. A T. caerulescens intraspecific cross was made between a plant from a nonmetallicolous accession [Lellingen (LE)], characterized by relatively high Zn accumulation, and a plant from a calamine accession [La Calamine (LC)], characterized by relatively low Zn accumulation. Zinc accumulation in roots and shoots segregated in the F3 population. This population was used to construct an LE/LC amplified fragment length polymorphism (AFLP)-based genetic linkage map and to map quantitative trait loci (QTL) for Zn accumulation. Two QTL were identified for root Zn accumulation, with the trait-enhancing alleles being derived from each of the parents, and explaining 21.7 and 16.6% of the phenotypic variation observed in the mapping population. Future development of more markers, based on Arabidopsis orthologous genes localized in the QTL regions, will allow fine-mapping and map-based cloning of the genes underlying the QTL.

  15. Quantitative Genetic Analysis for Yield and Yield Components in Boro Rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-03-01

    Full Text Available Twenty-nine genotypes of boro rice (Oryza sativa L. were grown in a randomized block design with three replications in plots of 4m x 1m with a crop geometry of 20 cm x 20 cm between November-April, in Regional Agricultural Research Station, Nagaon, India. Quantitative data were collected on five randomly selected plants of each genotype per replication for yield/plant, and six other yield components, namely plant height, panicles/plant, panicle length, effective grains/panicle, 100 grain weight and harvest index. Mean values of the characters for each genotype were used for analysis of variance and covariance to obtain information on genotypic and phenotypic correlation along with coheritability between two characters. Path analyses were carried out to estimate the direct and indirect effects of boro rice�s yield components. The objective of the study was to identify the characters that mostly influence the yield for increasing boro rice productivity through breeding program. Correlation analysis revealed significant positive genotypic correlation of yield/plant with plant height (0.21, panicles/plant (0.53, panicle length (0.53, effective grains/panicle (0.57 and harvest index (0.86. Path analysis based on genotypic correlation coefficients elucidated high positive direct effect of harvest index (0.8631, panicle length (0.2560 and 100 grain weight (0.1632 on yield/plant with a residual effect of 0.33. Plant height and panicles/plant recorded high positive indirect effect on yield/plant via harvest index whereas effective grains/panicle on yield/plant via harvest index and panicle length. Results of the present study suggested that five component characters, namely harvest index, effective grains/plant, panicle length, panicles/plant and plant height influenced the yield of boro rice. A genotype with higher magnitude of these component characters could be either selected from the existing genotypes or evolved by breeding program for genetic

  16. Impact of measurement error on testing genetic association with quantitative traits.

    Directory of Open Access Journals (Sweden)

    Jiemin Liao

    Full Text Available Measurement error of a phenotypic trait reduces the power to detect genetic associations. We examined the impact of sample size, allele frequency and effect size in presence of measurement error for quantitative traits. The statistical power to detect genetic association with phenotype mean and variability was investigated analytically. The non-centrality parameter for a non-central F distribution was derived and verified using computer simulations. We obtained equivalent formulas for the cost of phenotype measurement error. Effects of differences in measurements were examined in a genome-wide association study (GWAS of two grading scales for cataract and a replication study of genetic variants influencing blood pressure. The mean absolute difference between the analytic power and simulation power for comparison of phenotypic means and variances was less than 0.005, and the absolute difference did not exceed 0.02. To maintain the same power, a one standard deviation (SD in measurement error of a standard normal distributed trait required a one-fold increase in sample size for comparison of means, and a three-fold increase in sample size for comparison of variances. GWAS results revealed almost no overlap in the significant SNPs (p<10(-5 for the two cataract grading scales while replication results in genetic variants of blood pressure displayed no significant differences between averaged blood pressure measurements and single blood pressure measurements. We have developed a framework for researchers to quantify power in the presence of measurement error, which will be applicable to studies of phenotypes in which the measurement is highly variable.

  17. A bivariate quantitative genetic model for a threshold trait and a survival trait

    Directory of Open Access Journals (Sweden)

    Damgaard Lars

    2006-11-01

    Full Text Available Abstract Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  18. A bivariate quantitative genetic model for a threshold trait and a survival trait.

    Science.gov (United States)

    Damgaard, Lars Holm; Korsgaard, Inge Riis

    2006-01-01

    Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.

  19. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M. You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design (MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  20. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Institute of Scientific and Technical Information of China (English)

    Frank M.You; Qijian Song; Gaofeng Jia; Yanzhao Cheng; Scott Duguid; Helen Booker; Sylvie Cloutier

    2016-01-01

    The type 2 modified augmented design(MAD2) is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters.Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline(http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html).

  1. Estimation of genetic parameters and their sampling variances for quantitative traits in the type 2 modified augmented design

    Directory of Open Access Journals (Sweden)

    Frank M. You

    2016-04-01

    Full Text Available The type 2 modified augmented design (MAD2 is an efficient unreplicated experimental design used for evaluating large numbers of lines in plant breeding and for assessing genetic variation in a population. Statistical methods and data adjustment for soil heterogeneity have been previously described for this design. In the absence of replicated test genotypes in MAD2, their total variance cannot be partitioned into genetic and error components as required to estimate heritability and genetic correlation of quantitative traits, the two conventional genetic parameters used for breeding selection. We propose a method of estimating the error variance of unreplicated genotypes that uses replicated controls, and then of estimating the genetic parameters. Using the Delta method, we also derived formulas for estimating the sampling variances of the genetic parameters. Computer simulations indicated that the proposed method for estimating genetic parameters and their sampling variances was feasible and the reliability of the estimates was positively associated with the level of heritability of the trait. A case study of estimating the genetic parameters of three quantitative traits, iodine value, oil content, and linolenic acid content, in a biparental recombinant inbred line population of flax with 243 individuals, was conducted using our statistical models. A joint analysis of data over multiple years and sites was suggested for genetic parameter estimation. A pipeline module using SAS and Perl was developed to facilitate data analysis and appended to the previously developed MAD data analysis pipeline (http://probes.pw.usda.gov/bioinformatics_ tools/MADPipeline/index.html.

  2. Identification of quantitative genetic components of fitness variation in farmed, hybrid and native salmon in the wild.

    Science.gov (United States)

    Besnier, F; Glover, K A; Lien, S; Kent, M; Hansen, M M; Shen, X; Skaala, Ø

    2015-07-01

    Feral animals represent an important problem in many ecosystems due to interbreeding with wild conspecifics. Hybrid offspring from wild and domestic parents are often less adapted to local environment and ultimately, can reduce the fitness of the native population. This problem is an important concern in Norway, where each year, hundreds of thousands of farm Atlantic salmon escape from fish farms. Feral fish outnumber wild populations, leading to a possible loss of local adaptive genetic variation and erosion of genetic structure in wild populations. Studying the genetic factors underlying relative performance between wild and domesticated conspecific can help to better understand how domestication modifies the genetic background of populations, and how it may alter their ability to adapt to the natural environment. Here, based upon a large-scale release of wild, farm and wild x farm salmon crosses into a natural river system, a genome-wide quantitative trait locus (QTL) scan was performed on the offspring of 50 full-sib families, for traits related to fitness (length, weight, condition factor and survival). Six QTLs were detected as significant contributors to the phenotypic variation of the first three traits, explaining collectively between 9.8 and 14.8% of the phenotypic variation. The seventh QTL had a significant contribution to the variation in survival, and is regarded as a key factor to understand the fitness variability observed among salmon in the river. Interestingly, strong allelic correlation within one of the QTL regions in farmed salmon might reflect a recent selective sweep due to artificial selection.

  3. [Reconstituting evaluation methods based on both qualitative and quantitative paradigms].

    Science.gov (United States)

    Miyata, Hiroaki; Okubo, Suguru; Yoshie, Satoru; Kai, Ichiro

    2011-01-01

    Debate about the relationship between quantitative and qualitative paradigms is often muddled and confusing and the clutter of terms and arguments has resulted in the concepts becoming obscure and unrecognizable. In this study we conducted content analysis regarding evaluation methods of qualitative healthcare research. We extracted descriptions on four types of evaluation paradigm (validity/credibility, reliability/credibility, objectivity/confirmability, and generalizability/transferability), and classified them into subcategories. In quantitative research, there has been many evaluation methods based on qualitative paradigms, and vice versa. Thus, it might not be useful to consider evaluation methods of qualitative paradigm are isolated from those of quantitative methods. Choosing practical evaluation methods based on the situation and prior conditions of each study is an important approach for researchers.

  4. Genetic programming:  a novel method for the quantitative analysis of pyrolysis mass spectral data.

    Science.gov (United States)

    Gilbert, R J; Goodacre, R; Woodward, A M; Kell, D B

    1997-11-01

    A technique for the analysis of multivariate data by genetic programming (GP) is described, with particular reference to the quantitative analysis of orange juice adulteration data collected by pyrolysis mass spectrometry (PyMS). The dimensionality of the input space was reduced by ranking variables according to product moment correlation or mutual information with the outputs. The GP technique as described gives predictive errors equivalent to, if not better than, more widespread methods such as partial least squares and artificial neural networks but additionally can provide a means for easing the interpretation of the correlation between input and output variables. The described application demonstrates that by using the GP method for analyzing PyMS data the adulteration of orange juice with 10% sucrose solution can be quantified reliably over a 0-20% range with an RMS error in the estimate of ∼1%.

  5. Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype.

    Directory of Open Access Journals (Sweden)

    Claudia Kappen

    Full Text Available The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes.

  6. Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize.

    Science.gov (United States)

    Cankar, Katarina; Chauvensy-Ancel, Valérie; Fortabat, Marie-Noelle; Gruden, Kristina; Kobilinsky, André; Zel, Jana; Bertheau, Yves

    2008-05-15

    Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.

  7. Array-CGH and quantitative PCR genetic analysis in a case with bilateral hypoplasia of pulmonary arteries and lungs and simultaneous unilateral renal agenesis.

    Science.gov (United States)

    Hussein, Kais; Steinemann, Doris; Scholz, Henrike; Menkhaus, Ralf; Feist, Henning; Kreipe, Hans

    2010-08-18

    We describe the clinical course and have characterised anatomically and genetically a unique case of a newborn with bilateral hypoplasia of pulmonary arteries, consecutive extremely hypoplastic lung tissue and associated unilateral renal agenesis. Intrauterine oxygenation by the placenta seemed to have allowed normotrophic body maturity but immediately after delivery, in the third trimester, progressive hypoxemia developed and the newborn succumbed to acute respiratory failure. Genetic analysis by array-based comparative genomic hybridisation and quantitative PCR revealed duplication of 1p21, which, however, might not be the disease causing aberration. This case might represent an extreme form of previously reported, rare cases with simultaneous dysorganogenesis of lungs and kidneys.

  8. Quantitative genetic analysis of chlorophyll a fluorescence parameters in maize in the field environments

    Institute of Scientific and Technical Information of China (English)

    Domagojimi; Hrvoje Lepedu; Vlatka Jurkovi; Jasenka Antunovi; Vera Cesar

    2014-01-01

    Chlorophyl fluorescence transient from initial to maximum fluorescence (“P”step) throughout two intermedi-ate steps (“J”and“I”) (JIP-test) is considered a reliable early quantitative indicator of stress in plants. The JIP-test is particularly useful for crop plants when applied in variable field environments. The aim of the present study was to conduct a quantitative trait loci (QTL) analysis for nine JIP-test parameters in maize during flowering in four field environ-ments differing in weather conditions. QTL analysis and identification of putative candidate genes might help to explain the genetic relationship between photosynthesis and different field scenarios in maize plants. The JIP-test param-eters were analyzed in the intermated B73 ? Mo17 (IBM) maize population of 205 recombinant inbred lines. A set of 2,178 molecular markers across the whole maize genome was used for QTL analysis revealing 10 significant QTLs for seven JIP-test parameters, of which five were co-localized when combined over the four environments indicating polygenic inheritance and pleiotropy. Our results demonstrate that QTL analysis of chlorophyl fluorescence parameters was capable of detecting one pleiotropic locus on chromosome 7, coinciding with the gene gst23 that may be associated with efficient photosynthe-sis under different field scenarios.

  9. Genetic heterogeneity, modifier genes, and quantitative phenotypes in psychiatric illness: searching for a framework.

    Science.gov (United States)

    Fanous, A H; Kendler, K S

    2005-01-01

    Schizophrenia has long been thought to be clinically heterogeneous. A range of studies suggests that this is due to genetic heterogeneity. Some clinical features, such as negative symptoms, are associated with a greater risk of illness in relatives. Affected sibling pairs are correlated for clinical and course features as well as subforms of illness, and twin studies suggest that this is due to genetic factors. This is further supported by findings that subjects from families linked to some chromosomal regions may differ clinically from those from unlinked families. Moreover, some genes may affect clinical features without altering susceptibility (ie are modifier genes). High-risk genotypes may have quantitative, rather than categorical effects, and may influence milder or subclinical phenotypes. Another recent finding is that nonpsychotic relatives may have personality features that resemble those of their affected relatives. These findings taken together suggest that there may be several classes of gene action in schizophrenia: some genes may influence susceptibility only, others may influence clinical features only, and still others may have a mixed effect. Furthermore, subsets of these classes may affect personality and other traits in nonpsychotic relatives. Understanding these classes of gene action may help guide the design of linkage and association studies that have increased power. We describe five classes of genes and their predictions of the outcomes of family, twin, and several types of linkage studies. We go on to explore how these predictions can in turn be used to aid in the design of linkage studies.

  10. The Evaluation Criteria of Some Botanical Quantitative Characters of Peach Genetic Resources

    Institute of Scientific and Technical Information of China (English)

    WANG Li-rong; ZHU Geng-rui; FANG Wei-chao

    2006-01-01

    There were two peach descriptors systems: one from IPRGI in 1980 and the other from China in 1990. The former had only reference cultivars without quantity grades; the latter had only a list of some characteristics. This makes it difficult sharing of genetic resource information for breeders. To describe the main quantitative characteristics, a new system was established. Ten characteristics of 346-476 peach cultivars were investigated from 1986 to 2002 in the National Peach Genetic Collection in Zhengzhou City, China. These characteristics and their coefficients of variation were as follows: flower diameter 19.55%, vertical diameter of fruit 14.24%, cheek diameter of fruit 10.36%, suture diameter of fruit 11.44%, stone length 19.04%, stone width 10.86%, stone thickness 11.19%, leaf length 7.9%, leaf width 10.55%, and leaf stalk length 19.03%, respectively. Grade index and reference cultivars were given by statistical data for peach description.These grade indexes were recorded on 1-5 grades, and the third grade as a middle one occupied 39% or more of the distribution. In general, two reference cultivars for each grade were chosen, one is USA cultivar and the other is Chinese cultivar. This paper tried to use them as the reference cultivars, which are planted or used widely by Chinese breeders.

  11. EvolQG - An R package for evolutionary quantitative genetics [version 2; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Diogo Melo

    2016-06-01

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

  12. The quantitative genetic basis of adaptive divergence in the moor frog (Rana arvalis) and its implications for gene flow.

    Science.gov (United States)

    Hangartner, S; Laurila, A; Räsänen, K

    2012-08-01

    Knowledge on the relative contribution of direct genetic, maternal and environmental effects to adaptive divergence is important for understanding the drivers of biological diversification. The moor frog (Rana arvalis) shows adaptive divergence in embryonic and larval fitness traits along an acidification gradient in south-western Sweden. To understand the quantitative genetic basis of this divergence, we performed reciprocal crosses between three divergent population pairs and reared embryos and larvae at acid and neutral pH in the laboratory. Divergence in embryonic acid tolerance (survival) was mainly determined by maternal effects, whereas the relative contributions of maternal, additive and nonadditive genetic effects in larval life-history traits differed between traits, population pairs and rearing environments. These results emphasize the need to investigate the quantitative genetic basis of adaptive divergence in multiple populations and traits, as well as different environments. We discuss the implications of our findings for maintenance of local adaptation in the context of migrant and hybrid fitness.

  13. Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

    Science.gov (United States)

    Ragognetti, B N N; Stafuzza, N B; Silva, T B R; Chud, T C S; Grupioni, N V; Cruz, V A R; Peixoto, J O; Nones, K; Ledur, M C; Munari, D P

    2015-12-21

    Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

  14. [Development and validation of event-specific quantitative PCR method for genetically modified maize LY038].

    Science.gov (United States)

    Mano, Junichi; Masubuchi, Tomoko; Hatano, Shuko; Futo, Satoshi; Koiwa, Tomohiro; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Akiyama, Hiroshi; Teshima, Reiko; Kurashima, Takeyo; Takabatake, Reona; Kitta, Kazumi

    2013-01-01

    In this article, we report a novel real-time PCR-based analytical method for quantitation of the GM maize event LY038. We designed LY038-specific and maize endogenous reference DNA-specific PCR amplifications. After confirming the specificity and linearity of the LY038-specific PCR amplification, we determined the conversion factor required to calculate the weight-based content of GM organism (GMO) in a multilaboratory evaluation. Finally, in order to validate the developed method, an interlaboratory collaborative trial according to the internationally harmonized guidelines was performed with blind DNA samples containing LY038 at the mixing levels of 0, 0.5, 1.0, 5.0 and 10.0%. The precision of the method was evaluated as the RSD of reproducibility (RSDR), and the values obtained were all less than 25%. The limit of quantitation of the method was judged to be 0.5% based on the definition of ISO 24276 guideline. The results from the collaborative trial suggested that the developed quantitative method would be suitable for practical testing of LY038 maize.

  15. Statistical design of quantitative mass spectrometry-based proteomic experiments.

    Science.gov (United States)

    Oberg, Ann L; Vitek, Olga

    2009-05-01

    We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

  16. Development and validation of an event-specific quantitative PCR method for genetically modified maize MIR162.

    Science.gov (United States)

    Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

    2014-01-01

    A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize event, MIR162. We first prepared a standard plasmid for MIR162 quantification. The conversion factor (Cf) required to calculate the genetically modified organism (GMO) amount was empirically determined for two real-time PCR instruments, the Applied Biosystems 7900HT (ABI7900) and the Applied Biosystems 7500 (ABI7500) for which the determined Cf values were 0.697 and 0.635, respectively. To validate the developed method, a blind test was carried out in an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of relative standard deviation (RSDr). The determined biases were less than 25% and the RSDr values were less than 20% at all evaluated concentrations. These results suggested that the limit of quantitation of the method was 0.5%, and that the developed method would thus be suitable for practical analyses for the detection and quantification of MIR162.

  17. Systems genetics of liver fibrosis: identification of fibrogenic and expression quantitative trait loci in the BXD murine reference population.

    Directory of Open Access Journals (Sweden)

    Rabea A Hall

    Full Text Available The progression of liver fibrosis in response to chronic injury varies considerably among individual patients. The underlying genetics is highly complex due to large numbers of potential genes, environmental factors and cell types involved. Here, we provide the first toxicogenomic analysis of liver fibrosis induced by carbon tetrachloride in the murine 'genetic reference panel' of recombinant inbred BXD lines. Our aim was to define the core of risk genes and gene interaction networks that control fibrosis progression. Liver fibrosis phenotypes and gene expression profiles were determined in 35 BXD lines. Quantitative trait locus (QTL analysis identified seven genomic loci influencing fibrosis phenotypes (pQTLs with genome-wide significance on chromosomes 4, 5, 7, 12, and 17. Stepwise refinement was based on expression QTL mapping with stringent selection criteria, reducing the number of 1,351 candidate genes located in the pQTLs to a final list of 11 cis-regulated genes. Our findings demonstrate that the BXD reference population represents a powerful experimental resource for shortlisting the genes within a regulatory network that determine the liver's vulnerability to chronic injury.

  18. Quantitative Genetics and Functional-Structural Plant Growth Models: Simulation of Quantitative Trait Loci Detection for Model Parameters and Application to Potential Yield Optimization

    CERN Document Server

    Letort, Veronique; Cournède, Paul-Henry; De Reffye, Philippe; Courtois, Brigitte; 10.1093/aob/mcm197

    2010-01-01

    Background and Aims: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. Methods: The GreenLab model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings ...

  19. Beyond Punnett Squares: Student Word Association and Explanations of Phenotypic Variation through an Integrative Quantitative Genetics Unit Investigating Anthocyanin Inheritance and Expression in Brassica rapa Fast Plants

    Science.gov (United States)

    Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse

    2014-01-01

    Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225

  20. Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits.

    Science.gov (United States)

    Broadaway, K Alaine; Duncan, Richard; Conneely, Karen N; Almli, Lynn M; Bradley, Bekh; Ressler, Kerry J; Epstein, Michael P

    2015-07-01

    The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects. © 2015 WILEY PERIODICALS, INC.

  1. Quantitative genetics of plumage color: lifetime effects of early nest environment on a colorful sexual signal

    Science.gov (United States)

    Hubbard, Joanna K; Jenkins, Brittany R; Safran, Rebecca J

    2015-01-01

    Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color – a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) – is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought. PMID:26380676

  2. Quantitative genetics of plumage color: lifetime effects of early nest environment on a colorful sexual signal.

    Science.gov (United States)

    Hubbard, Joanna K; Jenkins, Brittany R; Safran, Rebecca J

    2015-08-01

    Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color - a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) - is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought.

  3. A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait.

    Science.gov (United States)

    Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner

    2010-10-01

    A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some "baseline" family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a

  4. Dissection of Genetic Effects of Quantitative Trait Loci (QTL) in Transgenic Cotton

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yong-shan

    2008-01-01

    @@ When alien DNA inserts into cotton genome in multi-copy manner,several QTL in cotton genome are disrupted,which are called dQTL in this study.Transgenic mutant line is near-isogenic to its recipient which is divergent for the dQTL from remaining QTL.So,a set of data from a transgenic QTL mutant line produced by Agrobacterium-mediated transformation,30074,its recipient,their F1 hybrids between them,and three elite lines were analyzed under a modified additive-dominance model with genotype by environment interactions in three different environments to dissect the genetic effects due to dQTL from the whole genome based genetic effects.

  5. Asian Option Pricing Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    YunzhongLiu; HuiyuXuan

    2004-01-01

    The cross-fertilization between artificial intelligence and computational finance has resulted in some of the most active research areas in financial engineering. One direction is the application of machine learning techniques to pricing financial products, which is certainly one of the most complex issues in finance. In the literature, when the interest rate,the mean rate of return and the volatility of the underlying asset follow general stochastic processes, the exact solution is usually not available. In this paper, we shall illustrate how genetic algorithms (GAs), as a numerical approach, can be potentially helpful in dealing with pricing. In particular, we test the performance of basic genetic algorithms by using it to the determination of prices of Asian options, whose exact solutions is known from Black-Scholesoption pricing theory. The solutions found by basic genetic algorithms are compared with the exact solution, and the performance of GAs is ewluated accordingly. Based on these ewluations, some limitations of GAs in option pricing are examined and possible extensions to future works are also proposed.

  6. GENETIC-BASED NUTRITION RECOMMENDATION MODEL

    Directory of Open Access Journals (Sweden)

    S. A.A. Fayoumi

    2014-01-01

    Full Text Available Evolutionary computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being widely applied to a variety of problems in many vital fields. Also, Evolutionary Algorithms (EA which applied the principles of Evolutionary computations, such as genetic algorithm, particle swarm, ant colony and bees algorithm and so on play an important role in decision making process. EAs serve a lot of fields which can affect our life directly, such as medicine, engineering, transportations, communications. One of these vital fields is Nutrition which can be viewed from several points of view as medical, physical, social, environmental and psychological point of view. This study, presents a proposed model that shows how evolutionary computing generally and genetic algorithm specifically-as a powerful algorithm of evolutionary algorithms-can be used to recommend an appropriate nutrition style in a medical and physical sides only to each person according to his/her personal and medical measurements.

  7. Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations

    NARCIS (Netherlands)

    S.K. Ganesh (Santhi); D.I. Chasman (Daniel); M.G. Larson (Martin); X. Guo (Xiuqing); G.C. Verwoert (Germaine); J.C. Bis (Joshua); X. Gu (Xiangjun); G.D. Smith; M.-L. Yang (Min-Lee); Y. Zhang (Yan); G.B. Ehret (Georg); L.M. Rose (Lynda); S.J. Hwang; G.J. Papanicolau (George); E.J.G. Sijbrands (Eric); K. Rice (Kenneth); G. Eiriksdottir (Gudny); V. Pihur (Vasyl); P.M. Ridker (Paul); R.S. Vasan (Ramachandran Srini); C. Newton-Cheh (Christopher); L.J. Raffel (Leslie); N. Amin (Najaf); J.I. Rotter (Jerome); K. Liu (Kiang); L.J. Launer (Lenore); M. Xu (Ming); M. Caulfield (Mark); A.C. Morrison (Alanna); A.D. Johnson (Andrew); D. Vaidya (Dhananjay); A. Dehghan (Abbas); G. Li (Guo); C. Bouchard (Claude); T.B. Harris (Tamara); H. Zhang (He); E.A. Boerwinkle (Eric); D.S. Siscovick (David); W. Gao (Wei); A.G. Uitterlinden (André); F. Rivadeneira Ramirez (Fernando); A. Hofman (Albert); E.M. Schmidt (Ellen); O.H. Franco (Oscar); Y. Huo (Yong); J.C.M. Witteman (Jacqueline); P. Munroe (Patricia); V. Gudnason (Vilmundur); W. Palmas (Walter); C.M. van Duijn (Cock); M. Fornage (Myriam); D. Levy (Daniel); B.M. Psaty (Bruce); A. Chakravarti (Aravinda)

    2014-01-01

    textabstractBlood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that ave

  8. Study of quantitative genetics of gum arabic production complicated by variability in ploidy level of Acacia senegal (L.) Willd

    DEFF Research Database (Denmark)

    Diallo, Adja Madjiguene; Nielsen, Lene Rostgaard; Hansen, Jon Kehlet

    2015-01-01

    Gum arabic is an important international commodity produced by trees of Acacia senegal across Sahelian Africa, but documented results of breeding activities are limited. The objective of this study was to provide reliable estimates of quantitative genetic parameters in order to shed light...

  9. Quantitative genetics approaches to study evolutionary processes in ecotoxicology; a perspective from research on the evolution of resistance.

    Science.gov (United States)

    Klerks, Paul L; Xie, Lingtian; Levinton, Jeffrey S

    2011-05-01

    Quantitative genetic approaches are often used to study evolutionary processes in ecotoxicology. This paper focuses on the evolution of resistance to environmental contaminants-an important evolutionary process in ecotoxicology. Three approaches are commonly employed to study the evolution of resistance: (1) Assessing whether a contaminant-exposed population has an increased resistance relative to a control population, using either spatial or temporal comparisons. (2) Estimating a population's heritability of resistance. (3) Investigating responses in a laboratory selection experiment. All three approaches provide valuable information on the potential for contaminants to affect a population's evolutionary trajectory via natural selection. However, all three approaches have inherent limitations, including difficulty in separating the various genetic and environmental variance components, responses being dependent on specific population and testing conditions, and inability to fully capture natural conditions in the laboratory. In order to maximize insights into the long-term consequences of adaptation, it is important to not just look at resistance itself, but also at the fitness consequences and at correlated responses in characteristics other than resistance. The rapid development of molecular genetics has yielded alternatives to the "black box" approach of quantitative genetics, but the presence of different limitations and strengths in the two fields means that they should be viewed as complementary rather than exchangeable. Quantitative genetics is benefiting from the incorporation of molecular tools and remains an important field for studying evolutionary toxicology.

  10. Quantitative Analysis of Polarimetric Model-Based Decomposition Methods

    Directory of Open Access Journals (Sweden)

    Qinghua Xie

    2016-11-01

    Full Text Available In this paper, we analyze the robustness of the parameter inversion provided by general polarimetric model-based decomposition methods from the perspective of a quantitative application. The general model and algorithm we have studied is the method proposed recently by Chen et al., which makes use of the complete polarimetric information and outperforms traditional decomposition methods in terms of feature extraction from land covers. Nevertheless, a quantitative analysis on the retrieved parameters from that approach suggests that further investigations are required in order to fully confirm the links between a physically-based model (i.e., approaches derived from the Freeman–Durden concept and its outputs as intermediate products before any biophysical parameter retrieval is addressed. To this aim, we propose some modifications on the optimization algorithm employed for model inversion, including redefined boundary conditions, transformation of variables, and a different strategy for values initialization. A number of Monte Carlo simulation tests for typical scenarios are carried out and show that the parameter estimation accuracy of the proposed method is significantly increased with respect to the original implementation. Fully polarimetric airborne datasets at L-band acquired by German Aerospace Center’s (DLR’s experimental synthetic aperture radar (E-SAR system were also used for testing purposes. The results show different qualitative descriptions of the same cover from six different model-based methods. According to the Bragg coefficient ratio (i.e., β , they are prone to provide wrong numerical inversion results, which could prevent any subsequent quantitative characterization of specific areas in the scene. Besides the particular improvements proposed over an existing polarimetric inversion method, this paper is aimed at pointing out the necessity of checking quantitatively the accuracy of model-based PolSAR techniques for a

  11. Genetic mapping of quantitative trait loci for milk production in sheep.

    Science.gov (United States)

    Mateescu, R G; Thonney, M L

    2010-10-01

    A backcross pedigree using dairy East Friesian rams and non-dairy Dorset ewes was established specifically to map quantitative trait loci (QTL) affecting milk production in sheep. Ninety nine microsatellite markers of an initial set of 120 were successfully genotyped and informative on 188 animals of this backcross pedigree. Test-day milk records on individual ewes were used to estimate several milk yield related traits, including peak milk yield and cumulative milk yield to 50 (MY50), 100 (MY100) and 250 days (MY250). These traits, as well as estimated breeding value of backcross ewes extracted from the genetic evaluation file of the entire flock, were used in interval mapping. Ovine chromosomes 2, 12, 18, 20 and 24 were identified to harbour putative QTL for different measures of milk production. The QTL on Ovis aries chromosomes (OAR) 2 and 20 mapped to locations where similar trait QTL have already been mapped in other studies, whereas QTL on OAR 12, 18 and 24 were unique to our backcross pedigree and have not been reported previously. In addition, all identified QTL regions were syntenic with bovine chromosomal segments revealed to harbour QTL affecting milk production traits, providing supporting evidence for the QTL identified here.

  12. Genetic modifier loci of mouse Mfrp(rd6) identified by quantitative trait locus analysis.

    Science.gov (United States)

    Won, Jungyeon; Charette, Jeremy R; Philip, Vivek M; Stearns, Timothy M; Zhang, Weidong; Naggert, Jürgen K; Krebs, Mark P; Nishina, Patsy M

    2014-01-01

    The identification of genes that modify pathological ocular phenotypes in mouse models may improve our understanding of disease mechanisms and lead to new treatment strategies. Here, we identify modifier loci affecting photoreceptor cell loss in homozygous Mfrp(rd6) mice, which exhibit a slowly progressive photoreceptor degeneration. A cohort of 63 F2 homozygous Mfrp(rd6) mice from a (B6.C3Ga-Mfrp(rd6)/J × CAST/EiJ) F1 intercross exhibited a variable number of cell bodies in the retinal outer nuclear layer at 20 weeks of age. Mice were genotyped with a panel of single nucleotide polymorphism markers, and genotypes were correlated with phenotype by quantitative trait locus (QTL) analysis to map modifier loci. A genome-wide scan revealed a statistically significant, protective candidate locus on CAST/EiJ Chromosome 1 and suggestive modifier loci on Chromosomes 6 and 11. Multiple regression analysis of a three-QTL model indicated that the modifier loci on Chromosomes 1 and 6 together account for 26% of the observed phenotypic variation, while the modifier locus on Chromosome 11 explains only an additional 4%. Our findings indicate that the severity of the Mfrp(rd6) retinal degenerative phenotype in mice depends on the strain genetic background and that a significant modifier locus on CAST/EiJ Chromosome 1 protects against Mfrp(rd6)-associated photoreceptor loss.

  13. Determinants of Neurotransmitters in Cerebrospinal Fluid and Plasma : from Seasonality to Quantitative Genetics

    NARCIS (Netherlands)

    Luykx, J.J.

    2013-01-01

    Most psychiatric conditions are complex genetic as the largest proportion of genetic variance is likely to derive from many genetic variants of small effect. Nonetheless, given the intricacies of the human brain and the heterogeneous nature of psychiatric disease entities, dissecting the genetic mec

  14. Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population.

    Science.gov (United States)

    Bonnet, Timothée; Wandeler, Peter; Camenisch, Glauco; Postma, Erik

    2017-01-01

    In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called "stasis paradox" highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is

  15. A Genetic Algorithm-Based Feature Selection

    Directory of Open Access Journals (Sweden)

    Babatunde Oluleye

    2014-07-01

    Full Text Available This article details the exploration and application of Genetic Algorithm (GA for feature selection. Particularly a binary GA was used for dimensionality reduction to enhance the performance of the concerned classifiers. In this work, hundred (100 features were extracted from set of images found in the Flavia dataset (a publicly available dataset. The extracted features are Zernike Moments (ZM, Fourier Descriptors (FD, Lengendre Moments (LM, Hu 7 Moments (Hu7M, Texture Properties (TP and Geometrical Properties (GP. The main contributions of this article are (1 detailed documentation of the GA Toolbox in MATLAB and (2 the development of a GA-based feature selector using a novel fitness function (kNN-based classification error which enabled the GA to obtain a combinatorial set of feature giving rise to optimal accuracy. The results obtained were compared with various feature selectors from WEKA software and obtained better results in many ways than WEKA feature selectors in terms of classification accuracy

  16. Multicast Routing Based on Hybrid Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    CAO Yuan-da; CAI Gui

    2005-01-01

    A new multicast routing algorithm based on the hybrid genetic algorithm (HGA) is proposed. The coding pattern based on the number of routing paths is used. A fitness function that is computed easily and makes algorithm quickly convergent is proposed. A new approach that defines the HGA's parameters is provided. The simulation shows that the approach can increase largely the convergent ratio, and the fitting values of the parameters of this algorithm are different from that of the original algorithms. The optimal mutation probability of HGA equals 0.50 in HGA in the experiment, but that equals 0.07 in SGA. It has been concluded that the population size has a significant influence on the HGA's convergent ratio when it's mutation probability is bigger. The algorithm with a small population size has a high average convergent rate. The population size has little influence on HGA with the lower mutation probability.

  17. Analysis of quantitative pore features based on mathematical morphology

    Institute of Scientific and Technical Information of China (English)

    QI Heng-nian; CHEN Feng-nong; WANG Hang-jun

    2008-01-01

    Wood identification is a basic technique of wood science and industry. Pore features are among the most important identification features for hardwoods. We have used a method based on an analysis of quantitative pore feature, which differs from traditional qualitative methods. We applies mathematical morphology methods such as dilation and erosion, open and close transformation of wood cross-sections, image repairing, noise filtering and edge detection to segment the pores from their background. Then the mean square errors (MSE) of pores were computed to describe the distribution of pores. Our experiment shows that it is easy to classift the pore features into three basic types, just as in traditional qualitative methods, but with the use of MSE of pores. This quantitative method improves wood identification considerably.

  18. Evolutionary genetic bases of longevity and senescence.

    Science.gov (United States)

    Govindaraju, Diddahally R

    2015-01-01

    Senescence, as a time-dependent developmental process, affects all organisms at every stage in their development and growth. During this process, genetic, epigenetic and environmental factors are known to introduce a wide range of variation for longevity among individuals. As an important life-history trait, longevity shows ontogenetic relationships with other complex traits, and hence may be viewed as a composite trait. Factors that influence the origin and maintenance of diversity of life are ultimately governed by Darwinian processes. Here we review evolutionary genetic mechanisms underlying longevity and senescence in humans from a life-history and genotype-epigenetic-phenotype (G-E-P) map prospective. We suggest that synergistic and cascading effects of cis-ruptive mechanisms in the genome, and epigenetic disruptive processes in relation to environmental factors may lead to sequential slippage in the G-E-P space. These mechanisms accompany age, stage and individual specific senescent processes, influenced by positive pleiotropy of certain genes, superior genome integrity, negative-frequency dependent selection and other factors that universally regulate rarity in nature. Finally we interpret life span as an inherent property of self-organizing systems that, accordingly, maintain species-specific limits for the entire complex of fitness traits. We conclude that Darwinian approaches provide unique opportunities to discover the biological bases of longevity as well as devise individual specific medical or other interventions toward improving health span.

  19. Function Optimization Based on Quantum Genetic Algorithm

    OpenAIRE

    Ying Sun; Hegen Xiong

    2014-01-01

    Optimization method is important in engineering design and application. Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on. It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed, which is called Variable-boundary-coded Quantum Genetic Algorithm (vbQGA) in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded c...

  20. Function Optimization Based on Quantum Genetic Algorithm

    OpenAIRE

    Ying Sun; Yuesheng Gu; Hegen Xiong

    2013-01-01

    Quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on.It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed ,which is called variable-boundary-coded quantum genetic algorithm (vbQGA) in which qubit chromosomes are collapsed into variableboundary- coded chromosomes instead of binary-coded chromosomes. Therefore much shorter chromosome strings can be gained.The m...

  1. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

    Science.gov (United States)

    Malvezzi, Alex J; Murray, Christopher S; Feldheim, Kevin A; DiBattista, Joseph D; Garant, Dany; Gobler, Christopher J; Chapman, Demian D; Baumann, Hannes

    2015-01-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (∼2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent–offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection. PMID:25926880

  2. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification.

    Science.gov (United States)

    Malvezzi, Alex J; Murray, Christopher S; Feldheim, Kevin A; DiBattista, Joseph D; Garant, Dany; Gobler, Christopher J; Chapman, Demian D; Baumann, Hannes

    2015-04-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (∼2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.

  3. A quantitative genetic approach to assess the evolutionary potential of a coastal marine fish to ocean acidification

    KAUST Repository

    Malvezzi, Alex J.

    2015-02-01

    Assessing the potential of marine organisms to adapt genetically to increasing oceanic CO2 levels requires proxies such as heritability of fitness-related traits under ocean acidification (OA). We applied a quantitative genetic method to derive the first heritability estimate of survival under elevated CO2 conditions in a metazoan. Specifically, we reared offspring, selected from a wild coastal fish population (Atlantic silverside, Menidia menidia), at high CO2 conditions (~2300 μatm) from fertilization to 15 days posthatch, which significantly reduced survival compared to controls. Perished and surviving offspring were quantitatively sampled and genotyped along with their parents, using eight polymorphic microsatellite loci, to reconstruct a parent-offspring pedigree and estimate variance components. Genetically related individuals were phenotypically more similar (i.e., survived similarly long at elevated CO2 conditions) than unrelated individuals, which translated into a significantly nonzero heritability (0.20 ± 0.07). The contribution of maternal effects was surprisingly small (0.05 ± 0.04) and nonsignificant. Survival among replicates was positively correlated with genetic diversity, particularly with observed heterozygosity. We conclude that early life survival of M. menidia under high CO2 levels has a significant additive genetic component that could elicit an evolutionary response to OA, depending on the strength and direction of future selection.

  4. Genetic influences on type 2 diabetes and metabolic syndrome related quantitative traits in Mauritius.

    Science.gov (United States)

    Jowett, Jeremy B; Diego, Vincent P; Kotea, Navaratnam; Kowlessur, Sudhir; Chitson, Pierrot; Dyer, Thomas D; Zimmet, Paul; Blangero, John

    2009-02-01

    Epidemiological studies report a high prevalence of type 2 diabetes and metabolic syndrome in the island nation of Mauritius. The Mauritius Family Study was initiated to examine heritable factors that contribute to these high rates of prevalence and consists of 400 individuals in 24 large extended multigenerational pedigrees. Anthropometric and biochemical measurements relating to the metabolic syndrome were undertaken in addition to family and lifestyle based information for each individual. Variance components methods were used to determine the heritability of the type 2 diabetes and metabolic syndrome related quantitative traits. The cohort was made up of 218 females (55%) and 182 males with 22% diagnosed with type 2 diabetes and a further 30% having impaired glucose tolerance or impaired fasting glucose. Notably BMI was not significantly increased in those with type 2 diabetes (P= .12), however a significant increase in waist circumference was observed in these groups (P= .02). The heritable proportion of trait variance was substantial and greater than values previously published for hip circumference, LDL and total cholesterol, diastolic and systolic blood pressure and serum creatinine. Height, weight and BMI heritabilities were all in the upper range of those previously reported. The phenotypic characteristics of the Mauritius family cohort are similar to those previously reported in the Mauritian population with a high observed prevalence rate of type 2 diabetes. A high heritability for key type 2 diabetes and metabolic syndrome related phenotypes (range 0.23 to 0.68), suggest the cohort will have utility in identifying genes that influence these quantitative traits.

  5. Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations.

    Science.gov (United States)

    Schielzeth, Holger; Husby, Arild

    2014-07-01

    A considerable challenge in evolutionary genetics is to understand the genetic mechanisms that facilitate or impede evolutionary adaptation in natural populations. For this, we must understand the genetic loci contributing to trait variation and the selective forces acting on them. The decreased costs and increased feasibility of obtaining genotypic data on a large number of individuals have greatly facilitated gene mapping in natural populations, particularly because organisms whose genetics have been historically difficult to study are now within reach. Here we review the methods available to evolutionary ecologists interested in dissecting the genetic basis of traits in natural populations. Our focus lies on standing genetic variation in outbred populations. We present an overview of the current state of research in the field, covering studies on both plants and animals. We also draw attention to particular challenges associated with the discovery of quantitative trait loci and discuss parallels to studies on crops, livestock, and humans. Finally, we point to some likely future developments in genetic mapping studies.

  6. Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum)

    Indian Academy of Sciences (India)

    Min Wang; Chengqi Li; Qinglian Wang

    2014-08-01

    Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5 /chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for marker-assisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.

  7. Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum).

    Science.gov (United States)

    Wang, Min; Li, Chengqi; Wang, Qinglian

    2014-08-01

    Lint percentage is an important character of cotton yield components and it is also correlated with cotton fibre development. In this study, we used a high lint percentage variety, Baimian1, and a low lint percentage, TM-1 genetic standard for Gossypium hirsutum, as parents to construct a mapping populations in upland cotton (G. hirsutum). A quantitative trait locus/loci (QTL) analysis of lint percentage was performed by using two mapping procedures; composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and the F2:3 populations in 2 years. Six main-effect QTL (M-QTL) for lint percentage (four significant and two suggestive) were detected in both years by CIM, and were located on chr. 3, chr. 19, chr. 26 and chr. 5/chr. 19. Of the six QTL, marker intervals and favourable gene sources of the significant M-QTL, qLP-3(2010) and qLP-3(2011) were consistent. These QTL were also detected by ICIM, and therefore, should preferentially be used for markerassisted selection (MAS) of lint percentage. Another M-QTL, qLP-19(2010), was detected by two mapping procedures, and it could also be a candidate for MAS. We detected the interaction between two M-QTL and environment, and 11 epistatic QTL (E-QTL) and their interaction with environment by using ICIM. The study also found two EST-SSRs, NAU1187 and NAU1255, linked to M-QTL for lint percentage that could be candidate markers affecting cotton fibre development.

  8. Cognitive radio resource allocation based on coupled chaotic genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Zu Yun-Xiao; Zhou Jie; Zeng Chang-Chang

    2010-01-01

    A coupled chaotic genetic algorithm for cognitive radio resource allocation which is based on genetic algorithm and coupled Logistic map is proposed. A fitness function for cognitive radio resource allocation is provided. Simulations are conducted for cognitive radio resource allocation by using the coupled chaotic genetic algorithm, simple genetic algorithm and dynamic allocation algorithm respectively. The simulation results show that, compared with simple genetic and dynamic allocation algorithm, coupled chaotic genetic algorithm reduces the total transmission power and bit error rate in cognitive radio system, and has faster convergence speed.

  9. Cognitive radio resource allocation based on coupled chaotic genetic algorithm

    Science.gov (United States)

    Zu, Yun-Xiao; Zhou, Jie; Zeng, Chang-Chang

    2010-11-01

    A coupled chaotic genetic algorithm for cognitive radio resource allocation which is based on genetic algorithm and coupled Logistic map is proposed. A fitness function for cognitive radio resource allocation is provided. Simulations are conducted for cognitive radio resource allocation by using the coupled chaotic genetic algorithm, simple genetic algorithm and dynamic allocation algorithm respectively. The simulation results show that, compared with simple genetic and dynamic allocation algorithm, coupled chaotic genetic algorithm reduces the total transmission power and bit error rate in cognitive radio system, and has faster convergence speed.

  10. Semiconductor defect metrology using laser-based quantitative phase imaging

    Science.gov (United States)

    Zhou, Renjie; Edwards, Chris; Popescu, Gabriel; Goddard, Lynford

    2015-03-01

    A highly sensitive laser-based quantitative phase imaging tool, using an epi-illumination diffraction phase microscope, has been developed for silicon wafer defect inspection. The first system used a 532 nm solid-state laser and detected 20 nm by 100 nm by 110 nm defects in a 22 nm node patterned silicon wafer. The second system, using a 405 nm diode laser, is more sensitive and has enabled detection of 15 nm by 90 nm by 35 nm defects in a 9 nm node densely patterned silicon wafer. In addition to imaging, wafer scanning and image-post processing are also crucial for defect detection.

  11. Quantitative design of regulatory elements based on high-precision strength prediction using artificial neural network.

    Science.gov (United States)

    Meng, Hailin; Wang, Jianfeng; Xiong, Zhiqiang; Xu, Feng; Zhao, Guoping; Wang, Yong

    2013-01-01

    Accurate and controllable regulatory elements such as promoters and ribosome binding sites (RBSs) are indispensable tools to quantitatively regulate gene expression for rational pathway engineering. Therefore, de novo designing regulatory elements is brought back to the forefront of synthetic biology research. Here we developed a quantitative design method for regulatory elements based on strength prediction using artificial neural network (ANN). One hundred mutated Trc promoter & RBS sequences, which were finely characterized with a strength distribution from 0 to 3.559 (relative to the strength of the original sequence which was defined as 1), were used for model training and test. A precise strength prediction model, NET90_19_576, was finally constructed with high regression correlation coefficients of 0.98 for both model training and test. Sixteen artificial elements were in silico designed using this model. All of them were proved to have good consistency between the measured strength and our desired strength. The functional reliability of the designed elements was validated in two different genetic contexts. The designed parts were successfully utilized to improve the expression of BmK1 peptide toxin and fine-tune deoxy-xylulose phosphate pathway in Escherichia coli. Our results demonstrate that the methodology based on ANN model can de novo and quantitatively design regulatory elements with desired strengths, which are of great importance for synthetic biology applications.

  12. Quantitative Trait Locus and Genetical Genomics Analysis Identifies Putatively Causal Genes for Fecundity and Brooding in the Chicken

    Directory of Open Access Journals (Sweden)

    Martin Johnsson

    2016-02-01

    Full Text Available Life history traits such as fecundity are important to evolution because they make up components of lifetime fitness. Due to their polygenic architectures, such traits are difficult to investigate with genetic mapping. Therefore, little is known about their molecular basis. One possible way toward finding the underlying genes is to map intermediary molecular phenotypes, such as gene expression traits. We set out to map candidate quantitative trait genes for egg fecundity in the chicken by combining quantitative trait locus mapping in an advanced intercross of wild by domestic chickens with expression quantitative trait locus mapping in the same birds. We measured individual egg fecundity in 232 intercross chickens in two consecutive trials, the second one aimed at measuring brooding. We found 12 loci for different aspects of egg fecundity. We then combined the genomic confidence intervals of these loci with expression quantitative trait loci from bone and hypothalamus in the same intercross. Overlaps between egg loci and expression loci, and trait–gene expression correlations identify 29 candidates from bone and five from hypothalamus. The candidate quantitative trait genes include fibroblast growth factor 1, and mitochondrial ribosomal proteins L42 and L32. In summary, we found putative quantitative trait genes for egg traits in the chicken that may have been affected by regulatory variants under chicken domestication. These represent, to the best of our knowledge, some of the first candidate genes identified by genome-wide mapping for life history traits in an avian species.

  13. Quantitative Trait Locus and Genetical Genomics Analysis Identifies Putatively Causal Genes for Fecundity and Brooding in the Chicken.

    Science.gov (United States)

    Johnsson, Martin; Jonsson, Kenneth B; Andersson, Leif; Jensen, Per; Wright, Dominic

    2015-12-04

    Life history traits such as fecundity are important to evolution because they make up components of lifetime fitness. Due to their polygenic architectures, such traits are difficult to investigate with genetic mapping. Therefore, little is known about their molecular basis. One possible way toward finding the underlying genes is to map intermediary molecular phenotypes, such as gene expression traits. We set out to map candidate quantitative trait genes for egg fecundity in the chicken by combining quantitative trait locus mapping in an advanced intercross of wild by domestic chickens with expression quantitative trait locus mapping in the same birds. We measured individual egg fecundity in 232 intercross chickens in two consecutive trials, the second one aimed at measuring brooding. We found 12 loci for different aspects of egg fecundity. We then combined the genomic confidence intervals of these loci with expression quantitative trait loci from bone and hypothalamus in the same intercross. Overlaps between egg loci and expression loci, and trait-gene expression correlations identify 29 candidates from bone and five from hypothalamus. The candidate quantitative trait genes include fibroblast growth factor 1, and mitochondrial ribosomal proteins L42 and L32. In summary, we found putative quantitative trait genes for egg traits in the chicken that may have been affected by regulatory variants under chicken domestication. These represent, to the best of our knowledge, some of the first candidate genes identified by genome-wide mapping for life history traits in an avian species.

  14. Smartphone based visual and quantitative assays on upconversional paper sensor.

    Science.gov (United States)

    Mei, Qingsong; Jing, Huarong; Li, You; Yisibashaer, Wuerzha; Chen, Jian; Nan Li, Bing; Zhang, Yong

    2016-01-15

    The integration of smartphone with paper sensors recently has been gain increasing attentions because of the achievement of quantitative and rapid analysis. However, smartphone based upconversional paper sensors have been restricted by the lack of effective methods to acquire luminescence signals on test paper. Herein, by the virtue of 3D printing technology, we exploited an auxiliary reusable device, which orderly assembled a 980nm mini-laser, optical filter and mini-cavity together, for digitally imaging the luminescence variations on test paper and quantitative analyzing pesticide thiram by smartphone. In detail, copper ions decorated NaYF4:Yb/Tm upconversion nanoparticles were fixed onto filter paper to form test paper, and the blue luminescence on it would be quenched after additions of thiram through luminescence resonance energy transfer mechanism. These variations could be monitored by the smartphone camera, and then the blue channel intensities of obtained colored images were calculated to quantify amounts of thiram through a self-written Android program installed on the smartphone, offering a reliable and accurate detection limit of 0.1μM for the system. This work provides an initial demonstration of integrating upconversion nanosensors with smartphone digital imaging for point-of-care analysis on a paper-based platform.

  15. Calculation of measurement uncertainty in quantitative analysis of genetically modified organisms using intermediate precision--a practical approach.

    Science.gov (United States)

    Zel, Jana; Gruden, Kristina; Cankar, Katarina; Stebih, Dejan; Blejec, Andrej

    2007-01-01

    Quantitative characterization of nucleic acids is becoming a frequently used method in routine analysis of biological samples, one use being the detection of genetically modified organisms (GMOs). Measurement uncertainty is an important factor to be considered in these analyses, especially where precise thresholds are set in regulations. Intermediate precision, defined as a measure between repeatability and reproducibility, is a parameter describing the real situation in laboratories dealing with quantitative aspects of molecular biology methods. In this paper, we describe the top-down approach to calculating measurement uncertainty, using intermediate precision, in routine GMO testing of food and feed samples. We illustrate its practicability in defining compliance of results with regulations. The method described is also applicable to other molecular methods for a variety of laboratory diagnostics where quantitative characterization of nucleic acids is needed.

  16. Web Based Genetic Algorithm Using Data Mining

    Directory of Open Access Journals (Sweden)

    Ashiqur Rahman

    2016-09-01

    Full Text Available This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. Through weighting the feature vectors using a Genetic Algorithm we can optimize the prediction accuracy and get a marked improvement over raw classification. It further shows that when the number of features is few; feature weighting is works better than just feature selection. Many leading educational institutions are working to establish an online teaching and learning presence. Several systems with different capabilities and approaches have been developed to deliver online education in an academic setting. In particular, Michigan State University (MSU has pioneered some of these systems to provide an infrastructure for online instruction. The research presented here was performed on a part of the latest online educational system developed at MSU, the Learning Online Network with Computer-Assisted Personalized Approach (LON-CAPA

  17. Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

    Science.gov (United States)

    Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven

    2006-01-01

    A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

  18. Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

    Science.gov (United States)

    Cornford, Steven L.; Feather, Martin S.; Heron, Vance A.; Jenkins, J. Steven

    2006-01-01

    A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

  19. WOMBAT——A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML)

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model;estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance structures, random regression models and reduced rank estimation are accommodated. WOMBAT employs up-to-date numerical and computational methods. Together with the use of efficient compilers, this generates fast executable programs, suitable for large scale analyses.Use of WOMBAT is illustrated for a bivariate analysis. The package consists of the executable program, available for LINUX and WINDOWS environments, manual and a set of worked example, and can be downloaded free of charge from http://agbu.une.edu.au/~kmeyer/wombat.html

  20. Development of an event-specific hydrolysis probe quantitative real-time polymerase chain reaction assay for Embrapa 5.1 genetically modified common bean (Phaseolus vulgaris).

    Science.gov (United States)

    Treml, Diana; Venturelli, Gustavo L; Brod, Fábio C A; Faria, Josias C; Arisi, Ana C M

    2014-12-10

    A genetically modified (GM) common bean event, namely Embrapa 5.1, resistant to the bean golden mosaic virus (BGMV), was approved for commercialization in Brazil. Brazilian regulation for genetically modified organism (GMO) labeling requires that any food containing more than 1% GMO be labeled. The event-specific polymerase chain reaction (PCR) method has been the primary trend for GMO identification and quantitation because of its high specificity based on the flanking sequence. This work reports the development of an event-specific assay, named FGM, for Embrapa 5.1 detection and quantitation by use of SYBR Green or hydrolysis probe. The FGM assay specificity was tested for Embrapa 2.3 event (a noncommercial GM common bean also resistant to BGMV), 46 non-GM common bean varieties, and other crop species including maize, GM maize, soybean, and GM soybean. The FGM assay showed high specificity to detect the Embrapa 5.1 event. Standard curves for the FGM assay presented a mean efficiency of 95% and a limit of detection (LOD) of 100 genome copies in the presence of background DNA. The primers and probe developed are suitable for the detection and quantitation of Embrapa 5.1.

  1. Qualitative and quantitative assessment of genetically modified soy in enteral nutrition formulas by polymerase chain reaction based methods Avaliação qualitativa e quantitativa de soja geneticamente modificada em fórmulas de nutrição enteral

    Directory of Open Access Journals (Sweden)

    Natália Eudes Fagundes de Barros

    2010-02-01

    Full Text Available OBJECTIVE: The aim of this work was to investigate the occurrence of Roundup Ready soybean in enteral nutrition formulas sold in Brazil. METHODS: A duplex Polymerase Chain Reaction based on the amplification of the lectin gene and the construction of the recombinant deoxyribonucleic acid of transgenic glyphosate-tolerant soybean (35S promoter and chloroplast transit peptide gene was performed in order to analyze the deoxyribonucleic acid obtained from nine soy protein isolate-containing formulas. RESULTS: Despite the highly processed nature of the food matrices, amplifiable deoxyribonucleic acid templates were obtained from all tested samples, as judged by the amplification of the lectin gene sequence. However, amplicons relative to the presence of Roundup Ready soybean were restricted to one of the nine enteral nutrition formulas analyzed as well as to the soybean reference powder, as expected. Quantitative analysis of the genetically modified formula by real-time Polymerase Chain Reaction showed a content of approximately 0.3% (w/w of recombinant deoxyribonucleic acid from the Roundup Ready soybean. CONCLUSION: The results show that one of the formulas contained genetically modified soy, pointing to the need of regulating the use of transgenic substances and of specific labeling in this product category.OBJETIVO: Investigar a ocorrência de soja transgênica em fórmulas de suporte nutricional comercializadas no Brasil. MÉTODOS: Foi desenvolvido o método da reação em cadeia da polimerase duplex, com base na amplificação do gene na lectina, e na construção do ácido desoxirribonucléico recombinante da soja transgênica tolerante a glifosato (promotor 35S e gene de peptídeo de trânsito de cloroplasto, a fim de avaliar o ácido desoxirribonucléico extraído a partir das nove fórmulas contendo isolado protéico de soja. RESULTADOS: Apesar do alto grau de processamento aos quais os produtos avaliados foram submetidos, foi poss

  2. A microfabrication-based approach to quantitative isothermal titration calorimetry.

    Science.gov (United States)

    Wang, Bin; Jia, Yuan; Lin, Qiao

    2016-04-15

    Isothermal titration calorimetry (ITC) directly measures heat evolved in a chemical reaction to determine equilibrium binding properties of biomolecular systems. Conventional ITC instruments are expensive, use complicated design and construction, and require long analysis times. Microfabricated calorimetric devices are promising, although they have yet to allow accurate, quantitative ITC measurements of biochemical reactions. This paper presents a microfabrication-based approach to integrated, quantitative ITC characterization of biomolecular interactions. The approach integrates microfabricated differential calorimetric sensors with microfluidic titration. Biomolecules and reagents are introduced at each of a series of molar ratios, mixed, and allowed to react. The reaction thermal power is differentially measured, and used to determine the thermodynamic profile of the biomolecular interactions. Implemented in a microdevice featuring thermally isolated, well-defined reaction volumes with minimized fluid evaporation as well as highly sensitive thermoelectric sensing, the approach enables accurate and quantitative ITC measurements of protein-ligand interactions under different isothermal conditions. Using the approach, we demonstrate ITC characterization of the binding of 18-Crown-6 with barium chloride, and the binding of ribonuclease A with cytidine 2'-monophosphate within reaction volumes of approximately 0.7 µL and at concentrations down to 2mM. For each binding system, the ITC measurements were completed with considerably reduced analysis times and material consumption, and yielded a complete thermodynamic profile of the molecular interaction in agreement with published data. This demonstrates the potential usefulness of our approach for biomolecular characterization in biomedical applications. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Image based quantitative reader for Lateral flow immunofluorescence assay.

    Science.gov (United States)

    Chowdhury, Kaushik Basak; Joseph, Jayaraj; Sivaprakasam, Mohanasankar

    2015-08-01

    Fluorescence Lateral flow immunoassays (LFIA) have wide range of applications in point-of-care testing (POCT). An integrated, motion-free, accurate, reliable reader that performs automated quantitative analysis of LFIA is essential for POCT diagnosis. We demonstrate an image based quantitative method to read the lateral flow immunofluorescence test strips. The developed reader uses line laser diode module to illuminate the LFIA test strip having fluorescent dye. Fluorescence light coming from the region of interest (ROI) of the LFIA test strip was filtered using an emission filter and imaged using a camera following which images were processed in computer. A dedicated control program was developed that automated the entire process including illumination of the test strip using laser diode, capturing the ROI of the test strip, processing and analyzing the images and displaying of results. Reproducibility of the reader has been evaluated using few reference cartridges and HbA1c (Glycated haemoglobin) test cartridges. The proposed system can be upgraded to a compact reader for widespread testing of LFIA test strips.

  4. Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

    Science.gov (United States)

    Crossa, José; Campos, Gustavo de los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P.; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

    2010-01-01

    The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed. PMID:20813882

  5. Quantitative criteria for improving performance of buccal DNA for high-throughput genetic analysis

    Directory of Open Access Journals (Sweden)

    Woo Jessica G

    2012-08-01

    Full Text Available Abstract Background DNA from buccal brush samples is being used for high-throughput analyses in a variety of applications, but the impact of sample type on genotyping success and downstream statistical analysis remains unclear. The objective of the current study was to determine laboratory predictors of genotyping failure among buccal DNA samples, and to evaluate the successfully genotyped results with respect to analytic quality control metrics. Sample and genotyping characteristics were compared between buccal and blood samples collected in the population-based Genetic and Environmental Risk Factors for Hemorrhagic Stroke (GERFHS study (https://gerfhs.phs.wfubmc.edu/public/index.cfm. Results Seven-hundred eight (708 buccal and 142 blood DNA samples were analyzed for laboratory-based and analysis metrics. Overall genotyping failure rates were not statistically different between buccal (11.3% and blood (7.0%, p = 0.18 samples; however, both the Contrast Quality Control (cQC rate and the dynamic model (DM call rates were lower among buccal DNA samples (p  Conclusions We identified a buccal sample characteristic, a ratio of ds/total DNA

  6. Soybean parent selection based on genetic diversity

    Directory of Open Access Journals (Sweden)

    Valéria Carpentieri-Pípolo

    2000-01-01

    Full Text Available Thirty-four soybean lines were assessed for twelve traits. The genetic distances were estimates using multivariate techniques, to identify parents to be included in breeding programs for hybridization. Grouping by the Tocher method, from generalized Mahalanobis distances, divided the 34 lines into four groups. The most important agronomic traits, weight of seeds per plot, plant height, height of first pod and days to maturity were considered when recommending for crossing. The following crosses were recommended based on the genetic divergence and the key agronomic traits: lines 23, 10, 2, 27 and 25 (group I with genotype 6 (group II and genotype 16 (group III. Thus only ten crosses would be made, representing only 2% of the total crosses which could be made in the partial diallel among the 34 lines assessed, which would allow up to 561 combinations.Trinta e quatro linhagens de soja foram avaliadas para doze características. As distâncias genéticas foram estimadas utilizando técnicas multivariadas com objetivo de identificar parentais a serem incluidos em um programa de melhoramento envolvendo hibridação. O agrupamento pelo método de Tocher, a partir das distâncias generalizadas de Mahalanobis, dividiu as 34 linhagens em 4 grupos. As caracterísiticas agronômicas mais importantes, peso de sementes por parcela, altura de planta, altura da primeira vagem e dias para maturação foram consideradas para a recomendação dos cruzamentos. Os seguintes cruzamentos foram recomendados baseado na divergência genética e nas características agronômicas chave: linhagens 23, 10, 2, 27 e 25 (grupo I com genótipo 6 (grupoII e com o genótipo 16 (grupo III. Portanto somente 10 cruzamentos poderiam ser realizados representando somente 2% do total de cruzamentos qu poderiam ser realizados em um dialelo parcial entre as 34 linhagens avaliadas as quais admitiriam até 561 combinações.

  7. Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

    Science.gov (United States)

    Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

    2015-12-01

    Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

  8. Quantitative Monte Carlo-based holmium-166 SPECT reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Elschot, Mattijs; Smits, Maarten L. J.; Nijsen, Johannes F. W.; Lam, Marnix G. E. H.; Zonnenberg, Bernard A.; Bosch, Maurice A. A. J. van den; Jong, Hugo W. A. M. de [Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands); Viergever, Max A. [Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands)

    2013-11-15

    Purpose: Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ({sup 166}Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative {sup 166}Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum.Methods: A fast Monte Carlo (MC) simulator was developed for simulation of {sup 166}Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full {sup 166}Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A{sup est}) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six {sup 166}Ho RE patients.Results: At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96–106.21 ml were improved from 32%–63% (SPECT-DSW) and 50%–80

  9. The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population.

    Science.gov (United States)

    Matsuda, H; Iwaisaki, H

    2002-01-01

    In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.

  10. Genetic selection of mice for quantitative responsiveness of lymphocytes to phytohemagglutinin.

    Science.gov (United States)

    Stiffel, C; Liacopoulos-Briot, M; Decreusefond, C; Lambert, F

    1977-05-01

    A two-way selection was performed in mice according to the quantitative in vitro response of lymph node lymphocytes to the mitogenic activity of phytohemagglutinin (PHA). The foundation population was composed of outbred mice produced by reciprocal mating of equal numbers of mice from four different colonies. The selective breeding was carried out by mating of mice at each generation giving the best or the lowest response, respectively. The progressive interline separation produced by 6 generations of selective breeding demonstrates that responsiveness to PHA is submitted to polygenic regulation. The heritability of the character investigated is 0.28 +/- 0.08. The interline separation is also found with another T mitogen, concanavalin A (Con A). In spleen cells PHA and Con A produce a similar interline difference. In contrast, the purified protein derivative of tuberculin (PPD) stimulated both lines equally, and E. coli lipopolysaccharide gave only a slightly higher response in high line. This finding implies that our selection based upon response to PHA did not influence B cell function.

  11. Genetic and Environmental Bases of Reading and Spelling: A Unified Genetic Dual Route Model

    Science.gov (United States)

    Bates, Timothy C.; Castles, Anne; Luciano, Michelle; Wright, Margaret J.; Coltheart, Max; Martin, Nicholas G.

    2007-01-01

    We develop and test a dual-route model of genetic effects on reading aloud and spelling, based on irregular and non-word reading and spelling performance assessed in 1382 monozygotic and dizygotic twins. As in earlier research, most of the variance in reading was due to genetic effects. However, there were three more specific conclusions: the…

  12. Family-based bivariate association tests for quantitative traits.

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    Full Text Available The availability of a large number of dense SNPs, high-throughput genotyping and computation methods promotes the application of family-based association tests. While most of the current family-based analyses focus only on individual traits, joint analyses of correlated traits can extract more information and potentially improve the statistical power. However, current TDT-based methods are low-powered. Here, we develop a method for tests of association for bivariate quantitative traits in families. In particular, we correct for population stratification by the use of an integration of principal component analysis and TDT. A score test statistic in the variance-components model is proposed. Extensive simulation studies indicate that the proposed method not only outperforms approaches limited to individual traits when pleiotropic effect is present, but also surpasses the power of two popular bivariate association tests termed FBAT-GEE and FBAT-PC, respectively, while correcting for population stratification. When applied to the GAW16 datasets, the proposed method successfully identifies at the genome-wide level the two SNPs that present pleiotropic effects to HDL and TG traits.

  13. PCA-based groupwise image registration for quantitative MRI.

    Science.gov (United States)

    Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

    2016-04-01

    Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as

  14. Quantitation of 35S promoter in maize DNA extracts from genetically modified organisms using real-time polymerase chain reaction, part 2: interlaboratory study.

    Science.gov (United States)

    Feinberg, Max; Fernandez, Sophie; Cassard, Sylvanie; Bertheau, Yves

    2005-01-01

    The European Committee for Standardization (CEN) and the European Network of GMO Working Laboratories have proposed development of a modular strategy for stepwise validation of complex analytical techniques. When applied to the quantitation of genetically modified organisms (GMOs) in food products, the instrumental quantitation step of the technique is separately validated from the DNA extraction step to better control the sources of uncertainty and facilitate the validation of GMO-specific polymerase chain reaction (PCR) tests. This paper presents the results of an interlaboratory study on the quantitation step of the method standardized by CEN for the detection of a regulatory element commonly inserted in GMO maize-based foods. This is focused on the quantitation of P35S promoter through using the quantitative real-time PCR (QRT-PCR). Fifteen French laboratories participated in the interlaboratory study of the P35S quantitation operating procedure on DNA extract samples using either the thermal cycler ABI Prism 7700 (Applied Biosystems, Foster City, CA) or Light Cycler (Roche Diagnostics, Indianapolis, IN). Attention was focused on DNA extract samples used to calibrate the method and unknown extract samples. Data were processed according to the recommendations of ISO 5725 standard. Performance criteria, obtained using the robust algorithm, were compared to the classic data processing after rejection of outliers by the Cochran and Grubbs tests. Two laboratories were detected as outliers by the Grubbs test. The robust precision criteria gave values between the classical values estimated before and after rejection of the outliers. Using the robust method, the relative expanded uncertainty by the quantitation method is about 20% for a 1% Bt176 content, whereas it can reach 40% for a 0.1% Bt176. The performances of the quantitation assay are relevant to the application of the European regulation, which has an accepted tolerance interval of about +/-50%. These data

  15. [The genetic bases of neurodevelopmental disorders].

    Science.gov (United States)

    Artigas-Pallarés, Josep; Guitart, Miriam; Gabau-Vila, Elisabeth

    2013-02-22

    In the last decade, progress made in genetics is questioning the current implicit nosological model in the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision (DSM-IV-TR) and the International Classification of Diseases, tenth revision. Both the categorical nature and the comorbidity detected on applying diagnostic criteria become unsustainable in the light of the genetic architecture that is emerging from studies being conducted on the genetics of mental disorders. The classical paradigms -one gene for one disease- or even a specific distinctive genetic pattern for each condition, are concepts restricted to specific cases. In this review the objective is to describe the current scenario that has arisen following the latest advances in genetics. The lines of work being traced by research both in the present and in the near future include: the identification of variations in the number of copies (both frequent and rare), indiscriminately linked to different disorders; the concurrence of multiple variants for a single disorder; the double hit phenomenon; and epigenetic modulation. The new version of the DSM, fully aware of the deficiencies in the current model, will mark a turning point that, while somewhat timid, is decidedly oriented towards incorporating a dimensional conception of mental disorders.

  16. Synthesizing Quantitative Evidence for Evidence-based Nursing: Systematic Review

    Directory of Open Access Journals (Sweden)

    Eui Geum Oh, PhD, RN

    2016-06-01

    Full Text Available As evidence-based practice has become an important issue in healthcare settings, the educational needs for knowledge and skills for the generation and utilization of healthcare evidence are increasing. Systematic review (SR, a way of evidence generation, is a synthesis of primary scientific evidence, which summarizes the best evidence on a specific clinical question using a transparent, a priori protocol driven approach. SR methodology requires a critical appraisal of primary studies, data extraction in a reliable and repeatable way, and examination for validity of the results. SRs are considered hierarchically as the highest form of evidence as they are a systematic search, identification, and summarization of the available evidence to answer a focused clinical question with particular attention to the methodological quality of studies or the credibility of opinion and text. The purpose of this paper is to introduce an overview of the fundamental knowledge, principals and processes in SR. The focus of this paper is on SR especially for the synthesis of quantitative data from primary research studies that examines the effectiveness of healthcare interventions. To activate evidence-based nursing care in various healthcare settings, the best and available scientific evidence are essential components. This paper will include some examples to promote understandings.

  17. Design of cinnamaldehyde amino acid Schiff base compounds based on the quantitative structure–activity relationship

    Science.gov (United States)

    Hui Wang; Mingyue Jiang; Shujun Li; Chung-Yun Hse; Chunde Jin; Fangli Sun; Zhuo Li

    2017-01-01

    Cinnamaldehyde amino acid Schiff base (CAAS) is a new class of safe, bioactive compounds which could be developed as potential antifungal agents for fungal infections. To design new cinnamaldehyde amino acid Schiff base compounds with high bioactivity, the quantitative structure–activity relationships (QSARs) for CAAS compounds against Aspergillus niger (A. niger) and...

  18. 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.

  19. Automated, quantitative cognitive/behavioral screening of mice: for genetics, pharmacology, animal cognition and undergraduate instruction.

    Science.gov (United States)

    Gallistel, C R; Balci, Fuat; Freestone, David; Kheifets, Aaron; King, Adam

    2014-02-26

    We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be

  20. High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

    Science.gov (United States)

    Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

    2017-07-14

    Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

  1. WNN-Based Network Security Situation Quantitative Prediction Method and Its Optimization

    Institute of Scientific and Technical Information of China (English)

    Ji-Bao Lai; Hui-Qiang Wang; Xiao-Wu Liu; Ying Liang; Rui-Juan Zheng; Guo-Sheng Zhao

    2008-01-01

    The accurate and real-time prediction of network security situation is the premise and basis of preventing intrusions and attacks in a large-scale network. In order to predict the security situation more accurately, a quantitative prediction method of network security situation based on Wavelet Neural Network with Genetic Algorithm (GAWNN) is proposed. After analyzing the past and the current network security situation in detail, we build a network security situation prediction model based on wavelet neural network that is optimized by the improved genetic algorithm and then adopt GAWNN to predict the non-linear time series of network security situation. Simulation experiments prove that the proposed method has advantages over Wavelet Neural Network (WNN) method and Back Propagation Neural Network (BPNN) method with the same architecture in convergence speed, functional approximation and prediction accuracy. What is more, system security tendency and laws by which security analyzers and administrators can adjust security policies in near real-time are revealed from the prediction results as early as possible.

  2. The genetic basis of adaptive population differentiation: A quantitative trait locus analysis of fitness traits in two wild barley populations from contrasting habitats

    NARCIS (Netherlands)

    Verhoeven, K.J.F.; Vanhala, T.K.; Biere, A.; Nevo, E.; Damme, van J.M.M.

    2004-01-01

    We used a quantitative trait locus (QTL) approach to study the genetic basis of population differentiation in wild barley, Hordeum spontaneum. Several ecotypes are recognized in this model species, and population genetic studies and reciprocal transplant experiments have indicated the role of local

  3. Genetic map construction and quantitative trait locus (QTL detection of growth-related traits in Litopenaeus vannamei for selective breeding applications.

    Directory of Open Access Journals (Sweden)

    Farafidy Andriantahina

    Full Text Available Growth is a priority trait from the point of view of genetic improvement. Molecular markers linked to quantitative trait loci (QTL have been regarded as useful for marker-assisted selection (MAS in complex traits as growth. Using an intermediate F2 cross of slow and fast growth parents, a genetic linkage map of Pacific whiteleg shrimp, Litopenaeusvannamei, based on amplified fragment length polymorphisms (AFLP and simple sequence repeats (SSR markers was constructed. Meanwhile, QTL analysis was performed for growth-related traits. The linkage map consisted of 451 marker loci (429 AFLPs and 22 SSRs which formed 49 linkage groups with an average marker space of 7.6 cM; they spanned a total length of 3627.6 cM, covering 79.50% of estimated genome size. 14 QTLs were identified for growth-related traits, including three QTLs for body weight (BW, total length (TL and partial carapace length (PCL, two QTLs for body length (BL, one QTL for first abdominal segment depth (FASD, third abdominal segment depth (TASD and first abdominal segment width (FASW, which explained 2.62 to 61.42% of phenotypic variation. Moreover, comparison of linkage maps between L. vannamei and Penaeusjaponicus was applied, providing a new insight into the genetic base of QTL affecting the growth-related traits. The new results will be useful for conducting MAS breeding schemes in L. vannamei .

  4. Quantitative determination of casein genetic variants in goat milk: Application in Girgentana dairy goat breed.

    Science.gov (United States)

    Montalbano, Maria; Segreto, Roberta; Di Gerlando, Rosalia; Mastrangelo, Salvatore; Sardina, Maria Teresa

    2016-02-01

    The study was conducted to develop a high-performance liquid chromatographic (HPLC) method to quantify casein genetic variants (αs2-, β-, and κ-casein) in milk of homozygous individuals of Girgentana goat breed. For calibration experiments, pure genetic variants were extracted from individual milk samples of animals with known genotypes. The described HPLC approach was precise, accurate and highly suitable for quantification of goat casein genetic variants of homozygous individuals. The amount of each casein per allele was: αs2-casein A = 2.9 ± 0.8 g/L and F = 1.8 ± 0.4 g/L; β-casein C = 3.0 ± 0.8 g/L and C1 = 2.0 ± 0.7 g/L and κ-casein A = 1.6 ± 0.3 g/L and B = 1.1 ± 0.2 g/L. A good correlation was found between the quantities of αs2-casein genetic variants A and F, and β-casein C and C1 with other previously described method. The main important result was obtained for κ-casein because, till now, no data were available on quantification of single genetic variants for this protein.

  5. Quantitative genetics of migration syndromes: a study of two barn swallow populations.

    Science.gov (United States)

    Teplitsky, C; Mouawad, N G; Balbontin, J; De Lope, F; Møller, A P

    2011-09-01

    Migration is a complex trait although little is known about genetic correlations between traits involved in such migration syndromes. To assess the migratory responses to climate change, we need information on genetic constraints on evolutionary potential of arrival dates in migratory birds. Using two long-term data sets on barn swallows Hirundo rustica (from Spain and Denmark), we show for the first time in wild populations that spring arrival dates are phenotypically and genetically correlated with morphological and life history traits. In the Danish population, length of outermost tail feathers and wing length were negatively genetically correlated with arrival date. In the Spanish population, we found a negative genetic correlation between arrival date and time elapsed between arrival date and laying date, constraining response to selection that favours both early arrival and shorter delays. This results in a decreased rate of adaptation, not because of constraints on arrival date, but constraints on delay before breeding, that is, a trait that can be equally important in the context of climate change.

  6. Disentangling the intertwined genetic bases of root and shoot growth in Arabidopsis.

    Science.gov (United States)

    Bouteillé, Marie; Rolland, Gaëlle; Balsera, Crispulo; Loudet, Olivier; Muller, Bertrand

    2012-01-01

    Root growth and architecture are major components of plant nutrient and water use efficiencies and these traits are the matter of extensive genetic analysis in several crop species. Because root growth relies on exported assimilate from the shoot, and changes in assimilate supply are known to alter root architecture, we hypothesized (i) that the genetic bases of root growth could be intertwined with the genetic bases of shoot growth and (ii) that the link could be either positive, with alleles favouring shoot growth also favouring root growth, or negative, because of competition for assimilates. We tested these hypotheses using a quantitative genetics approach in the model species Arabidopsis thaliana and the Bay-0 × Shahdara recombinant inbred lines population. In accordance with our hypothesis, root and shoot growth traits were strongly correlated and most root growth quantitative trait loci (QTLs) colocalized with shoot growth QTLs with positive alleles originating from either the same or the opposite parent. In order to identify regions that could be responsible for root growth independently of the shoot, we generated new variables either based on root to shoot ratios, residuals of root to shoot correlations or coordinates of principal component analysis. These variables showed high heritability allowing genetic analysis. They essentially all yielded similar results pointing towards two regions involved in the root--shoot balance. Using Heterogeneous Inbred Families (a kind of near-isogenic lines), we validated part of the QTLs present in these two regions for different traits. Our study thus highlights the difficulty of disentangling intertwined genetic bases of root and shoot growth and shows that this difficulty can be overcome by using simple statistical tools.

  7. Disentangling the intertwined genetic bases of root and shoot growth in Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Marie Bouteillé

    Full Text Available Root growth and architecture are major components of plant nutrient and water use efficiencies and these traits are the matter of extensive genetic analysis in several crop species. Because root growth relies on exported assimilate from the shoot, and changes in assimilate supply are known to alter root architecture, we hypothesized (i that the genetic bases of root growth could be intertwined with the genetic bases of shoot growth and (ii that the link could be either positive, with alleles favouring shoot growth also favouring root growth, or negative, because of competition for assimilates. We tested these hypotheses using a quantitative genetics approach in the model species Arabidopsis thaliana and the Bay-0 × Shahdara recombinant inbred lines population. In accordance with our hypothesis, root and shoot growth traits were strongly correlated and most root growth quantitative trait loci (QTLs colocalized with shoot growth QTLs with positive alleles originating from either the same or the opposite parent. In order to identify regions that could be responsible for root growth independently of the shoot, we generated new variables either based on root to shoot ratios, residuals of root to shoot correlations or coordinates of principal component analysis. These variables showed high heritability allowing genetic analysis. They essentially all yielded similar results pointing towards two regions involved in the root--shoot balance. Using Heterogeneous Inbred Families (a kind of near-isogenic lines, we validated part of the QTLs present in these two regions for different traits. Our study thus highlights the difficulty of disentangling intertwined genetic bases of root and shoot growth and shows that this difficulty can be overcome by using simple statistical tools.

  8. Selection of Suitable DNA Extraction Methods for Genetically Modified Maize 3272, and Development and Evaluation of an Event-Specific Quantitative PCR Method for 3272.

    Science.gov (United States)

    Takabatake, Reona; Masubuchi, Tomoko; Futo, Satoshi; Minegishi, Yasutaka; Noguchi, Akio; Kondo, Kazunari; Teshima, Reiko; Kurashima, Takeyo; Mano, Junichi; Kitta, Kazumi

    2016-01-01

    A novel real-time PCR-based analytical method was developed for the event-specific quantification of a genetically modified (GM) maize, 3272. We first attempted to obtain genome DNA from this maize using a DNeasy Plant Maxi kit and a DNeasy Plant Mini kit, which have been widely utilized in our previous studies, but DNA extraction yields from 3272 were markedly lower than those from non-GM maize seeds. However, lowering of DNA extraction yields was not observed with GM quicker or Genomic-tip 20/G. We chose GM quicker for evaluation of the quantitative method. We prepared a standard plasmid for 3272 quantification. The conversion factor (Cf), which is required to calculate the amount of a genetically modified organism (GMO), was experimentally determined for two real-time PCR instruments, the Applied Biosystems 7900HT (the ABI 7900) and the Applied Biosystems 7500 (the ABI7500). The determined Cf values were 0.60 and 0.59 for the ABI 7900 and the ABI 7500, respectively. To evaluate the developed method, a blind test was conducted as part of an interlaboratory study. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSDr). The determined values were similar to those in our previous validation studies. The limit of quantitation for the method was estimated to be 0.5% or less, and we concluded that the developed method would be suitable and practical for detection and quantification of 3272.

  9. Development and validation of tools to assess genetic discrimination and genetically based racism.

    Science.gov (United States)

    Parrott, Roxanne L; Silk, Kami J; Dillow, Megan R; Krieger, Janice L; Harris, Tina M; Condit, Celeste M

    2005-07-01

    It is possible that communication from mass media, public health or consumer advertising sources about human genetics and health may reify stereotypes of racialized social groups, perhaps cueing or exacerbating discriminatory and racist attitudes. This research used a multifaceted approach to assess lay perceptions of genetic discrimination and genetically based racism (N = 644). Two tools for use in strategic planning efforts associated with communicating about human genetics and health, the genetic discrimination instrument (GDI) and the genetically based racism instrument (GBRI), were derived. The GDI emerged as having five dimensions associated with lay perceptions of genetic discrimination. The GBRI was found to be unidimensional. Scale validation activities supported the tools' concurrent and discriminant validity characteristics. Significant differences between blacks and whites on the criminal control rights, social reproductive rights and employer rights factors as well as the GBRI were found. We recommend application of these screening tools prior to national dissemination of messages associated with genes and disease susceptibility, including school and university-based curricula.

  10. Quality control for quantitative PCR based on amplification compatibility test.

    Science.gov (United States)

    Tichopad, Ales; Bar, Tzachi; Pecen, Ladislav; Kitchen, Robert R; Kubista, Mikael; Pfaffl, Michael W

    2010-04-01

    Quantitative qPCR is a routinely used method for the accurate quantification of nucleic acids. Yet it may generate erroneous results if the amplification process is obscured by inhibition or generation of aberrant side-products such as primer dimers. Several methods have been established to control for pre-processing performance that rely on the introduction of a co-amplified reference sequence, however there is currently no method to allow for reliable control of the amplification process without directly modifying the sample mix. Herein we present a statistical approach based on multivariate analysis of the amplification response data generated in real-time. The amplification trajectory in its most resolved and dynamic phase is fitted with a suitable model. Two parameters of this model, related to amplification efficiency, are then used for calculation of the Z-score statistics. Each studied sample is compared to a predefined reference set of reactions, typically calibration reactions. A probabilistic decision for each individual Z-score is then used to identify the majority of inhibited reactions in our experiments. We compare this approach to univariate methods using only the sample specific amplification efficiency as reporter of the compatibility. We demonstrate improved identification performance using the multivariate approach compared to the univariate approach. Finally we stress that the performance of the amplification compatibility test as a quality control procedure depends on the quality of the reference set.

  11. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  12. Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

    Science.gov (United States)

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

  13. [Attempt at quantitative estimation of genetic effects of chemical pollution of atmospheric air in urban populations].

    Science.gov (United States)

    Antypenko, Ie M; Kohut, N M; Oleksiienko, P L

    1992-01-01

    Epidemiological investigation of spontaneous abortions and congenital anomalies in three towns of Ukraine has shown that mutation rate in Mariupol, the most contaminated town, as compared with relatively clean town is essentially higher. Genetical consequences due to environmental chemical pollution in Mariupol proved to be equivalent to the chronic influence of ionizing radiation for 30 years in the dose of 230 REM.

  14. Genetic analysis identifies quantitative trait loci controlling rosette mineral concentrations in Arabidopsis thaliana under drought

    NARCIS (Netherlands)

    Ghandilyan, A.; Barboza, L.; Tisne, S.; Granier, C.; Reymond, M.; Koornneef, M.; Schat, H.; Aarts, M.G.M.

    2009-01-01

    • Rosettes of 25 Arabidopsis thaliana accessions and an Antwerp-1 (An-1) × Landsberg erecta (Ler) population of recombinant inbred lines (RILs) grown in optimal watering conditions (OWC) and water deficit conditions (WDC) were analysed for mineral concentrations to identify genetic loci involved in

  15. Genetic relatedness of soybean genotypes based on agromorphological traits and RAPD markers

    Directory of Open Access Journals (Sweden)

    Perić Vesna

    2014-01-01

    Full Text Available Modern agriculture, breeding procedures, as well as competition among breeding institutions contribute to further reduction of already narrowed diversity of soybean commercial varieties. The objective of the study was to characterize eighteen soybean cultivars from three different breeding programs for agro-morphological traits and to reveal genetic diversity using molecular markers. Morphological description was performed with 13 qualitative and 9 quantitative traits. The genetic relationships were estimated using 21 RAPD markers. PIC was calculated for RAPD data, while the diversity of qualitative traits was described by Shannon genetic diversity index. Cluster analysis based on qualitative morphological characters showed clear separation of genotypes on the basis of their plant growth type. PC analysis performed for quantitative traits divided genotypes according to their maturity group. Grouping pattern based on molecular marker data was in agreement with pedigree of cultivars. A great similarity was found, primarily between the varieties under the same institution, and then among all examined varieties. Comparison of three methods in the assessment of diversity indicated that morphological markers might provide useful information in breeding process and allow classification by pedigree to some extent, but RAPD markers were found to be superior in assessing differences among genetically very similar genotypes. [Projekat Ministarstva nauke Republike Srbije, br. TR-31068

  16. Deterministic Pattern Classifier Based on Genetic Programming

    Institute of Scientific and Technical Information of China (English)

    LI Jian-wu; LI Min-qiang; KOU Ji-song

    2001-01-01

    This paper proposes a supervised training-test method with Genetic Programming (GP) for pattern classification. Compared and contrasted with traditional methods with regard to deterministic pattern classifiers, this method is true for both linear separable problems and linear non-separable problems. For specific training samples, it can formulate the expression of discriminate function well without any prior knowledge. At last, an experiment is conducted, and the result reveals that this system is effective and practical.

  17. Quantitative interferometric microscopy cytometer based on regularized optical flow algorithm

    Science.gov (United States)

    Xue, Liang; Vargas, Javier; Wang, Shouyu; Li, Zhenhua; Liu, Fei

    2015-09-01

    Cell detections and analysis are important in various fields, such as medical observations and disease diagnoses. In order to analyze the cell parameters as well as observe the samples directly, in this paper, we present an improved quantitative interferometric microscopy cytometer, which can monitor the quantitative phase distributions of bio-samples and realize cellular parameter statistics. The proposed system is able to recover the phase imaging of biological samples in the expanded field of view via a regularized optical flow demodulation algorithm. This algorithm reconstructs the phase distribution with high accuracy with only two interferograms acquired at different time points simplifying the scanning system. Additionally, the method is totally automatic, and therefore it is convenient for establishing a quantitative phase cytometer. Moreover, the phase retrieval approach is robust against noise and background. Excitingly, red blood cells are readily investigated with the quantitative interferometric microscopy cytometer system.

  18. Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations.

    Science.gov (United States)

    Ganesh, Santhi K; Chasman, Daniel I; Larson, Martin G; Guo, Xiuqing; Verwoert, Germain; Bis, Joshua C; Gu, Xiangjun; Smith, Albert V; Yang, Min-Lee; Zhang, Yan; Ehret, Georg; Rose, Lynda M; Hwang, Shih-Jen; Papanicolau, George J; Sijbrands, Eric J; Rice, Kenneth; Eiriksdottir, Gudny; Pihur, Vasyl; Ridker, Paul M; Vasan, Ramachandran S; Newton-Cheh, Christopher; Raffel, Leslie J; Amin, Najaf; Rotter, Jerome I; Liu, Kiang; Launer, Lenore J; Xu, Ming; Caulfield, Mark; Morrison, Alanna C; Johnson, Andrew D; Vaidya, Dhananjay; Dehghan, Abbas; Li, Guo; Bouchard, Claude; Harris, Tamara B; Zhang, He; Boerwinkle, Eric; Siscovick, David S; Gao, Wei; Uitterlinden, Andre G; Rivadeneira, Fernando; Hofman, Albert; Willer, Cristen J; Franco, Oscar H; Huo, Yong; Witteman, Jacqueline C M; Munroe, Patricia B; Gudnason, Vilmundur; Palmas, Walter; van Duijn, Cornelia; Fornage, Myriam; Levy, Daniel; Psaty, Bruce M; Chakravarti, Aravinda

    2014-07-03

    Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  19. Quantitative genetics, version 3.0: where have we gone since 1987 and where are we headed?

    Science.gov (United States)

    Walsh, Bruce

    2009-06-01

    The last 20 years since the previous World Congress have seen tremendous advancements in quantitative genetics, in large part due to the advancements in genomics, computation, and statistics. One central theme of this last 20 years has been the exploitation of the vast harvest of molecular markers--examples include QTL and association mapping, marker-assisted selection and introgression, scans for loci under selection, and methods to infer degree of coancestry, population membership, and past demographic history. One consequence of this harvest is that phenotyping, rather than genotyping, is now the bottleneck in molecular quantitative genetics studies. Equally important have been advances in statistics, many developed to effectively use this treasure trove of markers. Computational improvements in statistics, and in particular Markov Chain Monte Carlo (MCMC) methods, have facilitated many of these methods, as have significantly improved computational abilities for mixed models. Indeed, one could argue that mixed models have had at least as great an impact in quantitative genetics as have molecular markers. A final important theme over the past 20 years has been the fusion of population and quantitative genetics, in particular the importance of coalescence theory with its applications for association mapping, scans for loci under selection, and estimation of the demography history of a population. What are the future directions of the field? While obviously important surprises await us, the general trend seems to be moving into higher and higher dimensional traits and, in general, dimensional considerations. We have methods to deal with infinite-dimensional traits indexed by a single variable (such as a trait varying over time), but the future will require us to treat much more complex objects, such as infinite-dimensional traits indexed over several variables and with graphs and dynamical networks. A second important direction is the interfacing of quantitative

  20. A novel multi-walled carbon nanotube-based antibody conjugate for quantitative and semi-quantitative lateral flow assays.

    Science.gov (United States)

    Sun, Wenjuan; Hu, Xiaolong; Liu, Jia; Zhang, Yurong; Lu, Jianzhong; Zeng, Libo

    2017-10-01

    In this study, the multi-walled carbon nanotubes (MWCNTs) were applied in lateral flow strips (LFS) for semi-quantitative and quantitative assays. Firstly, the solubility of MWCNTs was improved using various surfactants to enhance their biocompatibility for practical application. The dispersed MWCNTs were conjugated with the methamphetamine (MET) antibody in a non-covalent manner and then manufactured into the LFS for the quantitative detection of MET. The MWCNTs-based lateral flow assay (MWCNTs-LFA) exhibited an excellent linear relationship between the values of test line and MET when its concentration ranges from 62.5 to 1500 ng/mL. The sensitivity of the LFS was evaluated by conjugating MWCNTs with HCG antibody and the MWCNTs conjugated method is 10 times more sensitive than the one conjugated with classical colloidal gold nanoparticles. Taken together, our data demonstrate that MWCNTs-LFA is a more sensitive and reliable assay for semi-quantitative and quantitative detection which can be used in forensic analysis.

  1. A method to prioritize quantitative traits and individuals for sequencing in family-based studies.

    Directory of Open Access Journals (Sweden)

    Kaanan P Shah

    Full Text Available Owing to recent advances in DNA sequencing, it is now technically feasible to evaluate the contribution of rare variation to complex traits and diseases. However, it is still cost prohibitive to sequence the whole genome (or exome of all individuals in each study. For quantitative traits, one strategy to reduce cost is to sequence individuals in the tails of the trait distribution. However, the next challenge becomes how to prioritize traits and individuals for sequencing since individuals are often characterized for dozens of medically relevant traits. In this article, we describe a new method, the Rare Variant Kinship Test (RVKT, which leverages relationship information in family-based studies to identify quantitative traits that are likely influenced by rare variants. Conditional on nuclear families and extended pedigrees, we evaluate the power of the RVKT via simulation. Not unexpectedly, the power of our method depends strongly on effect size, and to a lesser extent, on the frequency of the rare variant and the number and type of relationships in the sample. As an illustration, we also apply our method to data from two genetic studies in the Old Order Amish, a founder population with extensive genealogical records. Remarkably, we implicate the presence of a rare variant that lowers fasting triglyceride levels in the Heredity and Phenotype Intervention (HAPI Heart study (p = 0.044, consistent with the presence of a previously identified null mutation in the APOC3 gene that lowers fasting triglyceride levels in HAPI Heart study participants.

  2. Genetic diversity of Ghanaian local chicken populations based on ...

    African Journals Online (AJOL)

    Genetic diversity of Ghanaian local chicken populations based on ... raised across distinct agro-ecological zones and constitute unique populations with variable ... (GHFO) in the southwest and the Coastal Savannah (GHCS) along the coast in ...

  3. A monoclonal antibody-based VZV glycoprotein E quantitative assay and its application on antigen quantitation in VZV vaccine.

    Science.gov (United States)

    Liu, Jian; Zhu, Rui; Ye, Xiangzhong; Yang, Lianwei; Wang, Yongmei; Huang, Yanying; Wu, Jun; Wang, Wei; Ye, Jianghui; Li, Yimin; Zhao, Qinjian; Zhu, Hua; Cheng, Tong; Xia, Ningshao

    2015-06-01

    Varicella-zoster virus (VZV) is a highly infectious agent that causes varicella and herpes zoster (HZ), which may be associated with severe neuralgia. Vaccination is the most effective way to reduce the burden of the diseases. VZV glycoprotein E (gE) is the major and most immunogenic membrane protein that plays important roles in vaccine efficacy. A quantitative assay for gE content is desirable for the VZV vaccine process monitoring and product analysis. In this study, 70 monoclonal antibodies (mAbs) were obtained after immunizing mice with purified recombinant gE (rgE). The collection of mAbs was well-characterized, and a pair of high-affinity neutralization antibodies (capture mAb 4A2 and detection mAb 4H10) was selected to establish a specific and sensitive sandwich enzyme-linked immunosorbent assay (ELISA) to quantify the native and recombinant gE. The detection limit of this assay was found to be 1.95 ng/mL. Furthermore, a reasonably good correlation between the gE content (as measured by the mAb-based quantitative ELISA) and the virus titer (as measured by the "gold standard" plaque assay) was observed when both assays were performed for tracking the kinetics of virus growth during cell culture. A total of 16 batches of lyophilized VZV vaccine were tested using the newly developed quantitative ELISA and classical plaque assay, demonstrating reasonably good correlation between gE content and virus titer. Therefore, this mAb-based gE quantitative assay serves as a rapid, stable, and sensitive method for monitoring viral antigen content, one additional quantitative method for VZV vaccine process and product characterization. This quantitative ELISA may also serve as a complementary method for virus titering.

  4. A quantitative genetic study of starvation resistance at different geographic scales in natural populations of Drosophila melanogaster.

    Science.gov (United States)

    Goenaga, Julieta; José Fanara, Juan; Hasson, Esteban

    2010-08-01

    Food shortage is a stress factor that commonly affects organisms in nature. Resistance to food shortage or starvation resistance (SR) is a complex quantitative trait with direct implications on fitness. However, surveys of natural genetic variation in SR at different geographic scales are scarce. Here, we have measured variation in SR in sets of lines derived from nine natural populations of Drosophila melanogaster collected in western Argentina. Our study shows that within population variation explained a larger proportion of overall phenotypic variance (80%) than among populations (7·2%). We also noticed that an important fraction of variation was sex-specific. Overall females were more resistant to starvation than males; however, the magnitude of the sexual dimorphism (SD) in SR varied among lines and explained a significant fraction of phenotypic variance in all populations. Estimates of cross-sex genetic correlations suggest that the genetic architecture of SR is only partially shared between sexes in the populations examined, thus, facilitating further evolution of the SD.

  5. Estimates of genetic variability and association studies in quantitative plant traits of Eruca spp. landraces

    Directory of Open Access Journals (Sweden)

    Bozokalfa Kadri Mehmet

    2010-01-01

    Full Text Available Despite the increasing of economical importance of rocket plant limited information is available on genetic variability for the agronomic traits among Eruca spp. Hence, heritability and association studies of plant properties are necessities for a successful further rocket breeding programme. The objective of this study was to examine phenotypic and genotypic variability, broad sense heritability, genetic advance, genotypic and phenotypic correlation and mean for agronomic traits of rocket plant. The magnitude of phenotypic coefficient of variation values for all the traits were higher than the corresponding values and broad sense heritability estimates exceeded 65% for all traits. Phenotypic coefficients of variability (PCV ranged from 7.60 to 34.34% and genotypic coefficients of variability (GCV ranged between 5.58% for petiole thickness and 34.30% for plant weight. The results stated that plant weight, siliqua width, seed per siliqua and seed weight could be useful character for improved Eruca spp. breeding programme.

  6. Quantitative genetic variation for oviposition preference with respect to phenylthiocarbamide in Drosophila melanogaster.

    Science.gov (United States)

    Possidente, B; Mustafa, M; Collins, L

    1999-05-01

    Seven isogenic strains of Drosophila melanogaster were assayed for oviposition preference on food with phenylthiocarbamide (PTC) versus plain food. There was significant variation among strains for the percentage of eggs oviposited on each medium, ranging from 70 +/- 4% (SE) preference for plain food to no significant preference. Reciprocal hybrid, backcross, and F2 generations derived from two extreme parent strains revealed significant additive and nonadditive genetic variation but no evidence of maternal, paternal, or sex-chromosome effects.

  7. Grammar Based Genetic Programming Using Linear Representations

    Institute of Scientific and Technical Information of China (English)

    ZHANGHong; LUYinan; WANGFei

    2003-01-01

    In recent years,there has been a great interest in genetic programming(GP),which is used to solve many applications such as data mining,electronic engineering and pattern recognition etc.. Genetic programming paradigm as a from of adaptive learning is a functional approach to many problems that require a nonfixed representation and GP typically operates on a population of parse which usually represent computer programs whose nodes have single data type.In this paper GP using context-free grammars(CFGs) is described.This technique separates search space from solution space through a genotype to phenotype mapping.The genotypes and phenotypes of the individuals both act on different linear representations.A phenotype is postfix expression,a new method of representing which is described by making use of the definition and related features of a context-free grammar,i.e.a genotype is a variable length,linear valid genome determined by a simplifled derivation tree(SDT) generated from a context-free grammar.A CFG is used to specify how the possible solutions are created according to experiential knowledge and to direct legal crossover(ormutation)operations without any explicit reference to the process of program generation and parsing,and automatically ensuring typing and syntax correctness.Some related definitions involving genetic operators are described.Fitness evaluation is given.This technique is applied to a symbol regression problem-the identification of nonlinear dynamic characteristics of cushioning packaging.Experimental results show this method can flnd good relations between variables and is better than basic GP without a grammar.Future research on it is outlined.

  8. Genetic bases of the evolution of organisms

    Directory of Open Access Journals (Sweden)

    Marinković Dragoslav M.

    2002-01-01

    Full Text Available Biological progress consists of the continuous increase of divergence with simultaneous maintenance and the increase of conformance (harmoniousness of living systems. A mutual balance between divergence of forms and the degree of perfection of their structure and function indicates a level of the evolutionary development of a particular group of organisms, i.e. a level and prospects of their evolutionary progress. An enormous potential of combined genetic polymorphousness is reduced to adaptive landscapes of a limited number of developmental programmes that make actual units of inheritance and variability within each species.

  9. Quantitative genetic modeling and inference in the presence of nonignorable missing data.

    Science.gov (United States)

    Steinsland, Ingelin; Larsen, Camilla Thorrud; Roulin, Alexandre; Jensen, Henrik

    2014-06-01

    Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

  10. Genetic counseling follow-up - a retrospective study with a quantitative approach

    Directory of Open Access Journals (Sweden)

    De Pina-Neto João M.

    1999-01-01

    Full Text Available The impact of genetic counseling (GC was evaluated in families, who were interviewed at least two and half years and at most seven years after GC at the Genetics Service of the University Hospital, Faculty of Medicine of Ribeirão Preto, University of São Paulo (HC, FMRP, USP. The 113 families interviewed in this study were asked 48 questions and all children born after GC were studied clinically. We evaluated the families for spontaneous motivation for GC and understanding of GC information, their reproductive decisions, changes in the family after GC and the health status of new children. The majority of families seen at the Hospital das Clínicas de Ribeirão Preto were not spontaneously motivated to undergo GC. They had a low level of understanding about the information they received during GC. Generally families were using contraceptive methods (even when at low genetic risk with a consequent low rate of pregnancies and children born after GC. These families also had a very low rate of child adoption and divorces when compared to other studies.

  11. CANDU in-reactor quantitative visual-based inspection techniques

    Science.gov (United States)

    Rochefort, P. A.

    2009-02-01

    This paper describes two separate visual-based inspection procedures used at CANDU nuclear power generating stations. The techniques are quantitative in nature and are delivered and operated in highly radioactive environments with access that is restrictive, and in one case is submerged. Visual-based inspections at stations are typically qualitative in nature. For example a video system will be used to search for a missing component, inspect for a broken fixture, or locate areas of excessive corrosion in a pipe. In contrast, the methods described here are used to measure characteristic component dimensions that in one case ensure ongoing safe operation of the reactor and in the other support reactor refurbishment. CANDU reactors are Pressurized Heavy Water Reactors (PHWR). The reactor vessel is a horizontal cylindrical low-pressure calandria tank approximately 6 m in diameter and length, containing heavy water as a neutron moderator. Inside the calandria, 380 horizontal fuel channels (FC) are supported at each end by integral end-shields. Each FC holds 12 fuel bundles. The heavy water primary heat transport water flows through the FC pressure tube, removing the heat from the fuel bundles and delivering it to the steam generator. The general design of the reactor governs both the type of measurements that are required and the methods to perform the measurements. The first inspection procedure is a method to remotely measure the gap between FC and other in-core horizontal components. The technique involves delivering vertically a module with a high-radiation-resistant camera and lighting into the core of a shutdown but fuelled reactor. The measurement is done using a line-of-sight technique between the components. Compensation for image perspective and viewing elevation to the measurement is required. The second inspection procedure measures flaws within the reactor's end shield FC calandria tube rolled joint area. The FC calandria tube (the outer shell of the FC) is

  12. Genetic interaction mapping with microfluidic-based single cell sequencing

    Science.gov (United States)

    Haliburton, John R.; Shao, Wenjun; Deutschbauer, Adam; Arkin, Adam; Abate, Adam R.

    2017-01-01

    Genetic interaction mapping is useful for understanding the molecular basis of cellular decision making, but elucidating interactions genome-wide is challenging due to the massive number of gene combinations that must be tested. Here, we demonstrate a simple approach to thoroughly map genetic interactions in bacteria using microfluidic-based single cell sequencing. Using single cell PCR in droplets, we link distinct genetic information into single DNA sequences that can be decoded by next generation sequencing. Our approach is scalable and theoretically enables the pooling of entire interaction libraries to interrogate multiple pairwise genetic interactions in a single culture. The speed, ease, and low-cost of our approach makes genetic interaction mapping viable for routine characterization, allowing the interaction network to be used as a universal read out for a variety of biology experiments, and for the elucidation of interaction networks in non-model organisms. PMID:28170417

  13. Genetic Algorithm Based Microscale Vehicle Emissions Modelling

    Directory of Open Access Journals (Sweden)

    Sicong Zhu

    2015-01-01

    Full Text Available There is a need to match emission estimations accuracy with the outputs of transport models. The overall error rate in long-term traffic forecasts resulting from strategic transport models is likely to be significant. Microsimulation models, whilst high-resolution in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. At the microlevel, this paper discusses the limitations of existing emissions estimation approaches. Emission models for predicting emission pollutants other than CO2 are proposed. A genetic algorithm approach is adopted to select the predicting variables for the black box model. The approach is capable of solving combinatorial optimization problems. Overall, the emission prediction results reveal that the proposed new models outperform conventional equations in terms of accuracy and robustness.

  14. Warehouse Optimization Model Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Guofeng Qin

    2013-01-01

    Full Text Available This paper takes Bao Steel logistics automated warehouse system as an example. The premise is to maintain the focus of the shelf below half of the height of the shelf. As a result, the cost time of getting or putting goods on the shelf is reduced, and the distance of the same kind of goods is also reduced. Construct a multiobjective optimization model, using genetic algorithm to optimize problem. At last, we get a local optimal solution. Before optimization, the average cost time of getting or putting goods is 4.52996 s, and the average distance of the same kinds of goods is 2.35318 m. After optimization, the average cost time is 4.28859 s, and the average distance is 1.97366 m. After analysis, we can draw the conclusion that this model can improve the efficiency of cargo storage.

  15. Development of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

    Science.gov (United States)

    Oguchi, Taichi; Onishi, Mari; Minegishi, Yasutaka; Kurosawa, Yasunori; Kasahara, Masaki; Akiyama, Hiroshi; Teshima, Reiko; Futo, Satoshi; Furui, Satoshi; Hino, Akihiro; Kitta, Kazumi

    2009-06-01

    A duplex real-time PCR method was developed for quantitative screening analysis of GM maize. The duplex real-time PCR simultaneously detected two GM-specific segments, namely the cauliflower mosaic virus (CaMV) 35S promoter (P35S) segment and an event-specific segment for GA21 maize which does not contain P35S. Calibration was performed with a plasmid calibrant specially designed for the duplex PCR. The result of an in-house evaluation suggested that the analytical precision of the developed method was almost equivalent to those of simplex real-time PCR methods, which have been adopted as ISO standard methods for the analysis of GMOs in foodstuffs and have also been employed for the analysis of GMOs in Japan. In addition, this method will reduce both the cost and time requirement of routine GMO analysis by half. The high analytical performance demonstrated in the current study would be useful for the quantitative screening analysis of GM maize. We believe the developed method will be useful for practical screening analysis of GM maize, although interlaboratory collaborative studies should be conducted to confirm this.

  16. A Quantitative ADME-base Tool for Exploring Human ...

    Science.gov (United States)

    Exposure to a wide range of chemicals through our daily habits and routines is ubiquitous and largely unavoidable within modern society. The potential for human exposure, however, has not been quantified for the vast majority of chemicals with wide commercial use. Creative advances in exposure science are needed to support efficient and effective evaluation and management of chemical risks, particularly for chemicals in consumer products. The U.S. Environmental Protection Agency Office of Research and Development is developing, or collaborating in the development of, scientifically-defensible methods for making quantitative or semi-quantitative exposure predictions. The Exposure Prioritization (Ex Priori) model is a simplified, quantitative visual dashboard that provides a rank-ordered internalized dose metric to simultaneously explore exposures across chemical space (not chemical by chemical). Diverse data streams are integrated within the interface such that different exposure scenarios for “individual,” “population,” or “professional” time-use profiles can be interchanged to tailor exposure and quantitatively explore multi-chemical signatures of exposure, internalized dose (uptake), body burden, and elimination. Ex Priori has been designed as an adaptable systems framework that synthesizes knowledge from various domains and is amenable to new knowledge/information. As such, it algorithmically captures the totality of exposure across pathways. It

  17. GENES - a software package for analysis in experimental statistics and quantitative genetics

    Directory of Open Access Journals (Sweden)

    Cosme Damião Cruz

    2013-06-01

    Full Text Available GENES is a software package used for data analysis and processing with different biometricmodels and is essential in genetic studies applied to plant and animal breeding. It allows parameterestimation to analyze biologicalphenomena and is fundamental for the decision-making process andpredictions of success and viability of selection strategies. The program can be downloaded from theInternet (http://www.ufv.br/dbg/genes/genes.htm orhttp://www.ufv.br/dbg/biodata.htm and is available inPortuguese, English and Spanish. Specific literature (http://www.livraria.ufv.br/ and a set of sample filesare also provided, making GENES easy to use. The software is integrated into the programs MS Word, MSExcel and Paint, ensuring simplicity and effectiveness indata import and export ofresults, figures and data.It is also compatible with the free software R and Matlab, through the supply of useful scripts available forcomplementary analyses in different areas, including genome wide selection, prediction of breeding valuesand use of neural networks in genetic improvement.

  18. Quantitative genetic insights into the coevolutionary dynamics of male and female genitalia.

    Science.gov (United States)

    Evans, Jonathan P; van Lieshout, Emile; Gasparini, Clelia

    2013-07-22

    The spectacular variability that typically characterizes male genital traits has largely been attributed to the role of sexual selection. Among the evolutionary mechanisms proposed to account for this diversity, two processes in particular have generated considerable interest. On the one hand, females may exploit postcopulatory mechanisms of selection to favour males with preferred genital traits (cryptic female choice; CFC), while on the other hand females may evolve structures or behaviours that mitigate the direct costs imposed by male genitalia (sexual conflict; SC). A critical but rarely explored assumption underlying both processes is that male and female reproductive traits coevolve, either via the classic Fisherian model of preference-trait coevolution (CFC) or through sexually antagonistic selection (SC). Here, we provide evidence for this prediction in the guppy (Poecilia reticulata), a polyandrous livebearing fish in which males transfer sperm internally to females via consensual and forced matings. Our results from a paternal half-sibling breeding design reveal substantial levels of additive genetic variation underlying male genital size and morphology-two traits known to predict mating success during non-consensual matings. Our subsequent finding that physically interacting female genital traits exhibit corresponding levels of genetic (co)variation reveals the potential intersexual coevolutionary dynamics of male and female genitalia, thereby fulfilling a fundamental assumption underlying CFC and SC theory.

  19. Topology control based on quantum genetic algorithm in sensor networks

    Institute of Scientific and Technical Information of China (English)

    SUN Lijuan; GUO Jian; LU Kai; WANG Ruchuan

    2007-01-01

    Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service (QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.

  20. Restart-Based Genetic Algorithm for the Quadratic Assignment Problem

    Science.gov (United States)

    Misevicius, Alfonsas

    The power of genetic algorithms (GAs) has been demonstrated for various domains of the computer science, including combinatorial optimization. In this paper, we propose a new conceptual modification of the genetic algorithm entitled a "restart-based genetic algorithm" (RGA). An effective implementation of RGA for a well-known combinatorial optimization problem, the quadratic assignment problem (QAP), is discussed. The results obtained from the computational experiments on the QAP instances from the publicly available library QAPLIB show excellent performance of RGA. This is especially true for the real-life like QAPs.

  1. [Genetic selection of mice for quantitative responsiveness of lymphocytes to phytohemagglutinin].

    Science.gov (United States)

    Stiffel, C; Liacopoulos-Briot, M; Decreusefond, C; Lambert, F

    1977-01-01

    A two-way selection was performed in mice according to the quantitative response of small lymphocytes to the mitogenic activity of phytohaemagglutinin (PHA). The response of inguinal lymph node cells of each mouse to an optimal dose of PHA was measured by 3H-thymidine incorporation using a micro-plate method. Starting from four outbred mouse strains we mated on the one hand mice getting the best response and on the other hand mice getting the poorest response. A progressive separation of the two lines was observed. At the 7th generation a 3-fold difference was found between the two lines. A similar interline difference was observed when concanavalin A (ConA) was used as mitogen. The separation of the two lines was also evident when spleen cells or thymus cells were cultured with PHA or ConA.

  2. How can we harness quantitative genetic variation in crop root systems for agricultural improvement?

    Institute of Scientific and Technical Information of China (English)

    Christopher N. Topp; Adam L. Bray

    2016-01-01

    Root systems are a black box obscuring a comprehensive understanding of plant function, from the ecosystem scale down to the individual. In particular, a lack of knowledge about the genetic mechanisms and environmental effects that condition root system growth hinders our ability to develop the next generation of crop plants for improved agricultural productivity and sustainability. We discuss how the methods and metrics we use to quantify root systems can affect our ability to understand them, how we can bridge knowledge gaps and accelerate the derivation of structure-function relationships for roots, and why a detailed mecha-nistic understanding of root growth and function will be important for future agricultural gains.

  3. Genetic bases of arrhythmogenic right ventricular cardiomyopathy

    Directory of Open Access Journals (Sweden)

    Alessandra Rampazzo

    2010-05-01

    Full Text Available Arrhythmogenic right ventricular cardiomyopathy (ARVC is a heart muscle disease in which the pathological substrate is a fibro-fatty replacement of the right ventricular myocardium. The major clinical features are different types of arrhythmias with a left branch block pattern. ARVC shows autosomal dominant inheritance with incomplete penetrance. Recessive forms were also described, although in association with skin disorders. Ten genetic loci have been discovered so far and mutations were reported in five different genes. ARVD1 was associated with regulatory mutations of transforming growth factor beta-3 (TGFβ3, whereas ARVD2, characterized by effort-induced polymorphic arrhythmias, was associated with mutations in cardiac ryanodine receptor-2 (RYR2. All other mutations identified to date have been detected in genes encoding desmosomal proteins: plakoglobin (JUP which causes Naxos disease (a recessive form of ARVC associated with palmoplantar keratosis and woolly hair; desmoplakin (DSP which causes the autosomal dominant ARVD8 and plakophilin-2 (PKP2 involved in ARVD9. Desmosomes are important cell-to-cell adhesion junctions predominantly found in epidermis and heart; they are believed to couple cytoskeletal elements to plasma membrane in cell-to-cell or cell-to-substrate adhesions.

  4. The role of quantitative genetic studies in animal physiological ecology El rol de los estudios genético-cuantitativos en ecología fisiológica animal

    OpenAIRE

    2005-01-01

    Evolutionary physiology is a new discipline with roots in comparative physiology. One major change in the emergence of this discipline was an explicit new focus on viewing organisms as the evolutionary products of natural selection. The shift in research emphasis from comparative physiology to evolutionary physiology has resulted in physiological traits becoming important elements in broad research programs of evolution and ecology. Evolutionary quantitative genetics is a theory-based biologi...

  5. A dense genetic linkage map for common carp and its integration with a BAC-based physical map.

    Directory of Open Access Journals (Sweden)

    Lan Zhao

    Full Text Available BACKGROUND: Common carp (Cyprinus carpio is one of the most important aquaculture species with an annual global production of 3.4 million metric tons. It is also an important ornamental species as well as an important model species for aquaculture research. To improve the economically important traits of this fish, a number of genomic resources and genetic tools have been developed, including several genetic maps and a bacterial artificial chromosome (BAC-based physical map. However, integrated genetic and physical maps are not available to study quantitative trait loci (QTL and assist with fine mapping, positional cloning and whole genome sequencing and assembly. The objective of this study was to integrate the currently available BAC-based physical and genetic maps. RESULTS: The genetic map was updated with 592 novel markers, including 312 BAC-anchored microsatellites and 130 SNP markers, and contained 1,209 genetic markers on 50 linkage groups, spanning 3,565.9 cM in the common carp genome. An integrated genetic and physical map of the common carp genome was then constructed, which was composed of 463 physical map contigs and 88 single BACs. Combined lengths of the contigs and single BACs covered a physical length of 498.75 Mb, or around 30% of the common carp genome. Comparative analysis between common carp and zebrafish genomes was performed based on the integrated map, providing more insights into the common carp specific whole genome duplication and segmental rearrangements in the genome. CONCLUSION: We integrated a BAC-based physical map to a genetic linkage map of common carp by anchoring BAC-associated genetic markers. The density of the genetic linkage map was significantly increased. The integrated map provides a tool for both genetic and genomic studies of common carp, which will help us to understand the genomic architecture of common carp and facilitate fine mapping and positional cloning of economically important traits for

  6. Qualitative and quantitative event-specific PCR detection methods for oxy-235 canola based on the 3' integration flanking sequence.

    Science.gov (United States)

    Yang, Litao; Guo, Jinchao; Zhang, Haibo; Liu, Jia; Zhang, Dabing

    2008-03-26

    As more genetically modified plant events are approved for commercialization worldwide, the event-specific PCR method has become the key method for genetically modified organism (GMO) identification and quantification. This study reveals the 3' flanking sequence of the exogenous integration of Oxy-235 canola employing thermal asymmetric interlaced PCR (TAIL-PCR). On the basis of the revealed 3' flanking sequence, PCR primers and TaqMan probe were designed and qualitative and quantitative PCR assays were established for Oxy-235 canola. The specificity and limits of detection (LOD) and quantification (LOQ) of these two PCR assays were validated to as low as 0.1% for the relative LOD of qualitative PCR assay; the absolute LOD and LOQ were low to 10 and 20 copies of canola genomic DNA in quantitative PCR assay, respectively. Furthermore, ideal quantified results were obtained in the practical canola sample detection. All of the results indicate that the developed qualitative and quantitative PCR methods based on the revealed 3' integration flanking sequence are suitable for GM canola Oxy-235 identification and quantification.

  7. Molecular Characterization and SYBR Green Ⅰ-Based Quantitative PCR for Duck Hepatitis Virus Type 1

    Institute of Scientific and Technical Information of China (English)

    LUO Yu-jun; ZHANG Gui-hong; XU Xiao-qin; CHEN Jian-hong; LIAO Ming

    2008-01-01

    To determine the genomic sequence of a duck hepatitis virus type 1 (DHV-1) strain,real-time quantitative polyrnerase chain reaction (RTQ-PCR) assay based on SYBR Green Ⅰ technology was developed to target 3D gene of DHV-1.Comparative sequence analysis showed that the genome has a typical picornarivus genetic organization,and strain DHV-1 R genetic organaiztion is 5' untranslated region (UTR)-VPO-VP3-VP1-2A1-2A2-2B-2C-3A-3B-3C-3D-3' UTR,DHV-1 R has close relationship with Parechovirus,and has 95.1-99.1% nucleotide sequence identity with other DHV-1 strains.Based on the DHV-1 sequences in GenBank,three pairs of specific primers were designed to amplify DHV-1 using real-time PCR.The results showed that real-time PCR Tm value is 85.6℃ and the real-time PCR provides a broad dynamic range,detecting from 102 to 109 copies of DHV-1 cDNA per reaction.No cross-reactions were found in specimens containing DPV,AIV and NDV.It is concluded that DHV-1 belongs to a new group of the family Picornaviridae that may form a separate genus most closely related to the genus Parechovirus.All results showed that the real-time PCR has high sensitivity and specificity to detect DHV-1 using SYBR Green Ⅰ dissociation curve analysis,isolates can be distinguished by their melting temperature.These methods are rapid,sensitive,and reliable,and can be readily adapted for detection of DHV-1 from other clinical samples.

  8. Interlaboratory validation of quantitative duplex real-time PCR method for screening analysis of genetically modified maize.

    Science.gov (United States)

    Takabatake, Reona; Koiwa, Tomohiro; Kasahara, Masaki; Takashima, Kaori; Futo, Satoshi; Minegishi, Yasutaka; Akiyama, Hiroshi; Teshima, Reiko; Oguchi, Taichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

    2011-01-01

    To reduce the cost and time required to routinely perform the genetically modified organism (GMO) test, we developed a duplex quantitative real-time PCR method for a screening analysis simultaneously targeting an event-specific segment for GA21 and Cauliflower Mosaic Virus 35S promoter (P35S) segment [Oguchi et al., J. Food Hyg. Soc. Japan, 50, 117-125 (2009)]. To confirm the validity of the method, an interlaboratory collaborative study was conducted. In the collaborative study, conversion factors (Cfs), which are required to calculate the GMO amount (%), were first determined for two real-time PCR instruments, the ABI PRISM 7900HT and the ABI PRISM 7500. A blind test was then conducted. The limit of quantitation for both GA21 and P35S was estimated to be 0.5% or less. The trueness and precision were evaluated as the bias and reproducibility of the relative standard deviation (RSD(R)). The determined bias and RSD(R) were each less than 25%. We believe the developed method would be useful for the practical screening analysis of GM maize.

  9. Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

    Science.gov (United States)

    Dobata, Shigeto

    2012-12-01

    Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

  10. A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models

    Directory of Open Access Journals (Sweden)

    Brian B. Haines

    2009-01-01

    Full Text Available Two genetically engineered, conditional mouse models of lung tumor formation, K-rasLSL-G12D and K-rasLSL-G12D/p53LSL-R270H, are commonly used to model human lung cancer. Developed by Tyler Jacks and colleagues, these models have been invaluable to study in vivo lung cancer initiation and progression in a genetically and physiologically relevant context. However, heterogeneity, multiplicity and complexity of tumor formation in these models make it challenging to monitor tumor growth in vivo and have limited the application of these models in oncology drug discovery. Here, we describe a novel analytical method to quantitatively measure total lung tumor burden in live animals using micro-computed tomography imaging. Applying this methodology, we studied the kinetics of tumor development and response to targeted therapy in vivo in K-ras and K-ras/p53 mice. Consistent with previous reports, lung tumors in both models developed in a time- and dose (Cre recombinase-dependent manner. Furthermore, the compound K-rasLSL-G12D/p53LSL-R270H mice developed tumors faster and more robustly than mice harboring a single K-rasLSL-G12D oncogene, as expected. Erlotinib, a small molecule inhibitor of the epidermal growth factor receptor, significantly inhibited tumor growth in K-rasLSL-G12D/p53LSL-R270H mice. These results demonstrate that this novel imaging technique can be used to monitor both tumor progression and response to treatment and therefore supports a broader application of these genetically engineered mouse models in oncology drug discovery and development.

  11. OPTIMIZATION BASED ON LMPROVED REAL—CODED GENETIC ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    ShiYu; YuShenglin

    2002-01-01

    An improved real-coded genetic algorithm is pro-posed for global optimization of functionsl.The new algo-rithm is based om the judgement of the searching perfor-mance of basic real-coded genetic algorithm.The opera-tions of basic real-coded genetic algorithm are briefly dis-cussed and selected.A kind of chaos sequence is described in detail and added in the new algorithm ad a disturbance factor.The strategy of field partition is also used to im-prove the strcture of the new algorithm.Numerical ex-periment shows that the mew genetic algorithm can find the global optimum of complex funtions with satistaiting precision.

  12. Numeral eddy current sensor modelling based on genetic neural network

    Institute of Scientific and Technical Information of China (English)

    Yu A-Long

    2008-01-01

    This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness,on-line modelling and high precision.The maximum nonlinearity error can be reduced to 0.037% by using GNN.However, the maximum nonlinearity error is 0.075% using the least square method.

  13. Mobile robot dynamic path planning based on improved genetic algorithm

    Science.gov (United States)

    Wang, Yong; Zhou, Heng; Wang, Ying

    2017-08-01

    In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

  14. Genetic Identification of Quantitative Trait Loci for Contents of Mineral Nutrients in Rice Grain

    Institute of Scientific and Technical Information of China (English)

    Ana Luisa Garcia-Oliveira; Lubin Tan; Yongcai Fu; Chuanqing Sun

    2009-01-01

    In present study, Fe, Zn, Mn, Cu, Ca, Mg, P and K contents of 85 Introgression linee (ILs) derived from a cross between an elite indica cultivar Teqing and the wild rice (Oryza rufipogon) were measured by inductively coupled argon plasma (ICAP) spectrometry. Substantial variation was observed for all traits and most of the mineral elements were significantly positive correlated or independent except for Fe with Cu. A total of 31 putative quantitative trait loci (QTLs) were detected for these eight mineral elements by single point analysis. Wild rice (O. rufipogon) contributed favorable alleles for most of the QTLs (26 QTLs), and chromosomes 1, 9 and 12 exhibited 14 QTLs (45%) for these traits. One major effect of QTL for zinc content accounted for the largest proportion of phenotypic variation (11%-19%) was detected near the simple sequence repeats marker RM152 on chromosome 8. The co-locations of QTLs for some mineral elements observed in this mapping population suggested the relationship was at a molecular level among these traits and could be helpful for simultaneous improvement of these traits in rice grain by marker assisted selection.

  15. MS-based analytical methodologies to characterize genetically modified crops.

    Science.gov (United States)

    García-Cañas, Virginia; Simó, Carolina; León, Carlos; Ibáñez, Elena; Cifuentes, Alejandro

    2011-01-01

    The development of genetically modified crops has had a great impact on the agriculture and food industries. However, the development of any genetically modified organism (GMO) requires the application of analytical procedures to confirm the equivalence of the GMO compared to its isogenic non-transgenic counterpart. Moreover, the use of GMOs in foods and agriculture faces numerous criticisms from consumers and ecological organizations that have led some countries to regulate their production, growth, and commercialization. These regulations have brought about the need of new and more powerful analytical methods to face the complexity of this topic. In this regard, MS-based technologies are increasingly used for GMOs analysis to provide very useful information on GMO composition (e.g., metabolites, proteins). This review focuses on the MS-based analytical methodologies used to characterize genetically modified crops (also called transgenic crops). First, an overview on genetically modified crops development is provided, together with the main difficulties of their analysis. Next, the different MS-based analytical approaches applied to characterize GM crops are critically discussed, and include "-omics" approaches and target-based approaches. These methodologies allow the study of intended and unintended effects that result from the genetic transformation. This information is considered to be essential to corroborate (or not) the equivalence of the GM crop with its isogenic non-transgenic counterpart.

  16. Manufacturing Resource Planning Technology Based on Genetic Programming Simulation

    Institute of Scientific and Technical Information of China (English)

    GAO Shiwen; LIAO Wenhe; GUO Yu; LIU Jinshan; SU Yan

    2009-01-01

    Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.

  17. Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance.

    Science.gov (United States)

    Grieder, Christoph; Dhillon, Baldev S; Schipprack, Wolfgang; Melchinger, Albrecht E

    2012-04-01

    Biofuels have gained importance recently and the use of maize biomass as substrate in biogas plants for production of methane has increased tremendously in Germany. The objectives of our research were to (1) estimate variance components and heritability for different traits relevant to biogas production in testcrosses (TCs) of maize, (2) study correlations among traits, and (3) discuss strategies to breed maize as a substrate for biogas fermenters. We evaluated 570 TCs of 285 diverse dent maize lines crossed with two flint single-cross testers in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and methane yield (MY), the product of DMY and MFY, as the main target trait. Estimates of variance components showed general combining ability (GCA) to be the major source of variation. Estimates of heritability exceeded 0.67 for all traits and were even much greater in most instances. Methane yield was perfectly correlated with DMY but not with MFY, indicating that variation in MY is primarily determined by DMY. Further, DMY had a larger heritability and coefficient of genetic variation than MFY. Hence, for improving MY, selection should primarily focus on DMY rather than MFY. Further, maize breeding for biogas production may diverge from that for forage production because in the former case, quality traits seem to be of much lower importance.

  18. Development and optimisation of a label-free quantitative proteomic procedure and its application in the assessment of genetically modified tomato fruit.

    Science.gov (United States)

    Mora, Leticia; Bramley, Peter M; Fraser, Paul D

    2013-06-01

    A key global challenge for plant biotechnology is addressing food security, whereby provision must be made to feed 9 billion people with nutritional feedstuffs by 2050. To achieve this step change in agricultural production new crop varieties are required that are tolerant to environmental stresses imposed by climate change, have better yields, are more nutritious and require less resource input. Genetic modification (GM) and marker-assisted screening will need to be fully utilised to deliver these new crop varieties. To evaluate these varieties both in terms of environmental and food safety and the rational design of traits a systems level characterisation is necessary. To link the transcriptome to the metabolome, quantitative proteomics is required. Routine quantitative proteomics is an important challenge. Gel-based densitometry and MS analysis after stable isotope labeling have been employed. In the present article, we describe the application of a label-free approach that can be used in combination with SDS-PAGE and reverse-phase chromatography to evaluate the changes in the proteome of new crop varieties. The workflow has been optimised for protein coverage, accuracy and robustness, then its application demonstrated using a GM tomato variety engineered to deliver nutrient dense fruit.

  19. Optimal design of steel portal frames based on genetic algorithms

    Institute of Scientific and Technical Information of China (English)

    Yue CHEN; Kai HU

    2008-01-01

    As for the optimal design of steel portal frames, due to both the complexity of cross selections of beams and columns and the discreteness of design variables, it is difficult to obtain satisfactory results by traditional optimization. Based on a set of constraints of the Technical Specification for Light-weighted Steel Portal Frames of China, a genetic algorithm (GA) optimization program for portal frames, written in MATLAB code, was proposed in this paper. The graph user interface (GUI) is also developed for this optimal program, so that it can be used much more conveniently. Finally, some examples illustrate the effectiveness and efficiency of the genetic-algorithm-based optimal program.

  20. Genetics

    Science.gov (United States)

    ... Inheritance; Heterozygous; Inheritance patterns; Heredity and disease; Heritable; Genetic markers ... The chromosomes are made up of strands of genetic information called DNA. Each chromosome contains sections of ...

  1. Quantitative analysis of mutation and selection pressures on base composition skews in bacterial chromosomes

    Directory of Open Access Journals (Sweden)

    Chen Carton W

    2007-08-01

    Full Text Available Abstract Background Most bacterial chromosomes exhibit asymmetry of base composition with respect to leading vs. lagging strands (GC and AT skews. These skews reflect mainly those in protein coding sequences, which are driven by asymmetric mutation pressures during replication and transcription (notably asymmetric cytosine deamination plus subsequent selection for preferred structures, signals, amino acid or codons. The transcription-associated effects but not the replication-associated effects contribute to the overall skews through the uneven distribution of the coding sequences on the leading and lagging strands. Results Analysis of 185 representative bacterial chromosomes showed diverse and characteristic patterns of skews among different clades. The base composition skews in the coding sequences were used to derive quantitatively the effect of replication-driven mutation plus subsequent selection ('replication-associated pressure', RAP, and the effect of transcription-driven mutation plus subsequent selection at translation level ('transcription-associate pressure', TAP. While different clades exhibit distinct patterns of RAP and TAP, RAP is absent or nearly absent in some bacteria, but TAP is present in all. The selection pressure at the translation level is evident in all bacteria based on the analysis of the skews at the three codon positions. Contribution of asymmetric cytosine deamination was found to be weak to TAP in most phyla, and strong to RAP in all the Proteobacteria but weak in most of the Firmicutes. This possibly reflects the differences in their chromosomal replication machineries. A strong negative correlation between TAP and G+C content and between TAP and chromosomal size were also revealed. Conclusion The study reveals the diverse mutation and selection forces associated with replication and transcription in various groups of bacteria that shape the distinct patterns of base composition skews in the chromosomes during

  2. A Quantitative Tool for Producing DNA-Based Diagnostic Arrays

    Energy Technology Data Exchange (ETDEWEB)

    Tom J. Whitaker

    2008-07-11

    The purpose of this project was to develop a precise, quantitative method to analyze oligodeoxynucleotides (ODNs) on an array to enable a systematic approach to quality control issues affecting DNA microarrays. Two types of ODN's were tested; ODN's formed by photolithography and ODN's printed onto microarrays. Initial work in Phase I, performed in conjunction with Affymetrix, Inc. who has a patent on a photolithographic in situ technique for creating DNA arrays, was very promising but did seem to indicate that the atomization process was not complete. Soon after Phase II work was under way, Affymetrix had further developed fluorescent methods and indicated they were no longer interested in our resonance ionization technique. This was communicated to the program manager and it was decided that the project would continue and be focused on printed ODNs. The method being tested is called SIRIS, Sputter-Initiated Resonance Ionization Spectroscopy. SIRIS has been shown to be a highly sensitive, selective, and quantitative tool for atomic species. This project was aimed at determining if an ODN could be labeled in such a way that SIRIS could be used to measure the label and thus provide quantitative measurements of the ODN on an array. One of the largest problems in this study has been developing a method that allows us to know the amount of an ODN on a surface independent of the SIRIS measurement. Even though we could accurately determine the amount of ODN deposited on a surface, the amount that actually attached to the surface is very difficult to measure (hence the need for a quantitative tool). A double-labeling procedure was developed in which 33P and Pt were both used to label ODNs. The radioactive 33P could be measured by a proportional counter that maps the counts in one dimension. This gave a good measurement of the amount of ODN remaining on a surface after immobilization and washing. A second label, Pt, was attached to guanine nucleotides in the

  3. cDNA-AFLP-based genetical genomics in cotton fibers.

    Science.gov (United States)

    Claverie, Michel; Souquet, Marlène; Jean, Janine; Forestier-Chiron, Nelly; Lepitre, Vincent; Pré, Martial; Jacobs, John; Llewellyn, Danny; Lacape, Jean-Marc

    2012-03-01

    Genetical genomics, or genetic analysis applied to gene expression data, has not been widely used in plants. We used quantitative cDNA-AFLP to monitor the variation in the expression level of cotton fiber transcripts among a population of inter-specific Gossypium hirsutum × G. barbadense recombinant inbred lines (RILs). Two key fiber developmental stages, elongation (10 days post anthesis, dpa), and secondary cell wall thickening (22 dpa), were studied. Normalized intensity ratios of 3,263 and 1,201 transcript-derived fragments (TDFs) segregating over 88 RILs were analyzed for quantitative trait loci (QTL) mapping for the 10 and 22 dpa fibers, respectively. Two-thirds of all TDFs mapped between 1 and 6 eQTLs (LOD > 3.5). Chromosome 21 had a higher density of eQTLs than other chromosomes in both data sets and, within chromosomes, hotspots of presumably trans-acting eQTLs were identified. The eQTL hotspots were compared to the location of phenotypic QTLs for fiber characteristics among the RILs, and several cases of co-localization were detected. Quantitative RT-PCR for 15 sequenced TDFs showed that 3 TDFs had at least one eQTL at a similar location to those identified by cDNA-AFLP, while 3 other TDFs mapped an eQTL at a similar location but with opposite additive effect. In conclusion, cDNA-AFLP proved to be a cost-effective and highly transferable platform for genome-wide and population-wide gene expression profiling. Because TDFs are anonymous, further validation and interpretation (in silico analysis, qPCR gene profiling) of the eQTL and eQTL hotspots will be facilitated by the increasing availability of cDNA and genomic sequence resources in cotton.

  4. A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

    Science.gov (United States)

    Liu, Chun; Bridges, Melissa E; Kaundun, Shiv S; Glasgow, Les; Owen, Micheal Dk; Neve, Paul

    2017-02-01

    Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  5. Comparing partial least square approaches in a gene- or region-based association study for multiple quantitative phenotypes.

    Science.gov (United States)

    Yuan, Zhongshang; Zhang, Xiaoshuai; Li, Fangyu; Zhao, Jinghua; Xue, Fuzhong

    2014-01-01

    On thinking quantitatively of complex diseases, there are at least three statistical strategies for association studies: one single-nucleotide polymorphism (SNP) on a single trait, gene or region (with multiple SNPs) on a single trait, and gene or region on multiple traits. The third approach is the most general in dissecting genetic mechanisms underlying complex diseases underpinning multiple quantitative traits. Gene or region association methods based on partial least square (PLS) approaches have been shown to have apparent power advantage. However, few approaches have been developed for multiple quantitative phenotypes or traits underlying a condition or disease, and the performance of various PLS approaches used in association studies for multiple quantitative traits have not been assessed. Here we exploit association between multiple SNPs and multiple phenotypes or traits, from a regression perspective, through exhaustive scan statistics (sliding window) using PLS and sparse PLS regressions. Simulations were conducted to assess the performance of the proposed scan statistics and compare them with existing methods. The proposed methods were applied to 12 regions of genome-wide association study data from the European Prospective Investigation of Cancer-Norfolk study.

  6. Incorporating privileged genetic information for fundus image based glaucoma detection.

    Science.gov (United States)

    Duan, Lixin; Xu, Yanwu; Li, Wen; Chen, Lin; Wing, Damon Wing Kee; Wong, Tien Yin; Liu, Jiang

    2014-01-01

    Visual features extracted from retinal fundus images have been increasingly used for glaucoma detection, as those images are generally easy to acquire. In recent years, genetic researchers have found that some single nucleic polymorphisms (SNPs) play important roles in the manifestation of glaucoma and also show superiority over fundus images for glaucoma detection. In this work, we propose to use the SNPs to form the so-called privileged information and deal with a practical problem where both fundus images and privileged genetic information exist for the training subjects, while the test objects only have fundus images. To solve this problem, we present an effective approach based on the learning using privileged information (LUPI) paradigm to train a predictive model for the image visual features. Extensive experiments demonstrate the usefulness of our approach in incorporating genetic information for fundus image based glaucoma detection.

  7. Genetic program based data mining to reverse engineer digital logic

    Science.gov (United States)

    Smith, James F., III; Nguyen, Thanh Vu H.

    2006-04-01

    A data mining based procedure for automated reverse engineering and defect discovery has been developed. The data mining algorithm for reverse engineering uses a genetic program (GP) as a data mining function. A genetic program is an algorithm based on the theory of evolution that automatically evolves populations of computer programs or mathematical expressions, eventually selecting one that is optimal in the sense it maximizes a measure of effectiveness, referred to as a fitness function. The system to be reverse engineered is typically a sensor. Design documents for the sensor are not available and conditions prevent the sensor from being taken apart. The sensor is used to create a database of input signals and output measurements. Rules about the likely design properties of the sensor are collected from experts. The rules are used to create a fitness function for the genetic program. Genetic program based data mining is then conducted. This procedure incorporates not only the experts' rules into the fitness function, but also the information in the database. The information extracted through this process is the internal design specifications of the sensor. Uncertainty related to the input-output database and the expert based rule set can significantly alter the reverse engineering results. Significant experimental and theoretical results related to GP based data mining for reverse engineering will be provided. Methods of quantifying uncertainty and its effects will be presented. Finally methods for reducing the uncertainty will be examined.

  8. Selective quantitative writing on ADHD genetics in study books : A critical analysis

    NARCIS (Netherlands)

    te Meerman, Sanne; Batstra, Laura; Hoekstra, Rink; Grietens, Hans

    2016-01-01

    Objectives It is often claimed that ADHD is a brain-based and highly heritable disorder. However, although all behavior relates to the brain in some way, there are no physiological, neuro-chemical or anatomical studies showing differences other than on a group level. Such claims are in fact generali

  9. A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize.

    Science.gov (United States)

    Welcker, Claude; Sadok, Walid; Dignat, Grégoire; Renault, Morgan; Salvi, Silvio; Charcosset, Alain; Tardieu, François

    2011-10-01

    Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material.

  10. Quantitative analysis for nonlinear fluorescent spectra based on edges matching

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A novel spectra-edge-matching approach is proposed for the quantitative analysis of the nonlinear fluorescence spectra of the air impurities excited by a femtosecond laser.The fluorescence spectra are first denoised and compressed,both by wavelet transform,and several peak groups are then picked from each spectrum according to a threshold of intensity and are used to extract the spectral features through principal component analysis.It is indicated that the first two principle components actually cover up to 98% of the total information and are sufficient for the final concentration analysis.The analysis reveals a monotone relationship between the spectra intensity and the concentration of the air impurities,suggesting that the femtosecond laser induced fluorescence spectroscopy along with the proposed spectra analysis method can become a powerful tool for monitoring environmental pollutants.

  11. Quantitative metagenomic analyses based on average genome size normalization

    DEFF Research Database (Denmark)

    Frank, Jeremy Alexander; Sørensen, Søren Johannes

    2011-01-01

    Over the past quarter-century, microbiologists have used DNA sequence information to aid in the characterization of microbial communities. During the last decade, this has expanded from single genes to microbial community genomics, or metagenomics, in which the gene content of an environment can...... by estimating average genome sizes. This normalization can relieve comparative biases introduced by differences in community structure, number of sequencing reads, and sequencing read lengths between different metagenomes. We demonstrate the utility of this approach by comparing metagenomes from two different...... marine sources using both conventional small-subunit (SSU) rRNA gene analyses and our quantitative method to calculate the proportion of genomes in each sample that are capable of a particular metabolic trait. With both environments, to determine what proportion of each community they make up and how...

  12. Graphics processing unit-based quantitative second-harmonic generation imaging.

    Science.gov (United States)

    Kabir, Mohammad Mahfuzul; Jonayat, A S M; Patel, Sanjay; Toussaint, Kimani C

    2014-09-01

    We adapt a graphics processing unit (GPU) to dynamic quantitative second-harmonic generation imaging. We demonstrate the temporal advantage of the GPU-based approach by computing the number of frames analyzed per second from SHG image videos showing varying fiber orientations. In comparison to our previously reported CPU-based approach, our GPU-based image analysis results in ∼10× improvement in computational time. This work can be adapted to other quantitative, nonlinear imaging techniques and provides a significant step toward obtaining quantitative information from fast in vivo biological processes.

  13. DESCIFRANDO LAS BASES MOLECULARES DE LA RESISTENCIA CUANTITATIVA Deciphering the Molecular Bases of Quantitative Resistance

    Directory of Open Access Journals (Sweden)

    CAMILO LÓPEZ

    2011-08-01

    Full Text Available Uno de los factores que más afectan los cultivos son las enfermedades ocasionadas por patógenos. La resistencia vegetal ha sido clásicamente dividida en dos tipos: i completa, vertical o cualitativa que es gobernada por un solo gen e ii incompleta, horizontal o cuantitativa la cual es gobernada por varios genes. Aunque la resistencia cuantitativa provee resistencia de amplio espectro y es durable, los mecanismos moleculares subyacentes no han sido estudiados en detalle. En esta revisión se propone un modelo basado en co-localización de genes similares a los genes clásicos de resistencia cualitativa con QTLs (Quantitative Trait Loci para explicar el mecanismo involucrado en el reconocimiento del patógeno durante la resistencia cuantitativa. Además se presenta información acerca del progreso obtenido en los últimos tres años para entender este tipo de resistencia, lo que culminó con la clonación de varios genes asociados a resistencia cuantitativa. En conjunto, estos datos proveen nuevas luces sobre la naturaleza genética de este tipo de resistencia y de cómo puede ser empleada en programas de mejoramiento genético.Plant pathogens are some of the most important factors affecting crop production. Classically two general types of plant resistance to pathogens have been recognized: i complete, vertical or qualitative resistance governed by a single gene; and ii incomplete, horizontal or quantitative resistance, which is governed by several genes. Although quantitative resistance provides broad spectrum and more durable resistance, the underlying molecular mechanism involved in pathogen recognition has not been deeply studied. In this review, we proposed a model to explain the molecular mechanism involved in the pathogen recognition during the quantitative resistance. This is based on the co-localization of similar classical qualitative resistance genes with QTL (Quantitative Trait Loci. In addition, information is presented about the

  14. Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing

    DEFF Research Database (Denmark)

    Sørensen, Peter; de los Campos, Gustavo; Morgante, Fabio

    2015-01-01

    Genetic studies usually focus on quantifying and understanding the existence of genetic control on expected phenotypic outcomes. However, there is compelling evidence suggesting the existence of genetic control at the level of environmental variability, with some genotypes exhibiting more stable ...

  15. GeneNetwork: framework for web-based genetics

    NARCIS (Netherlands)

    Sloan, Zachary; Arends, Danny; Broman, Karl W.; Centeno, Arthur; Furlotte, Nicholas; Nijveen, H.; Yan, Lei; Zhou, Xiang; Williams, Robert W.; Prins, Pjotr

    2016-01-01

    GeneNetwork (GN) is a free and open source (FOSS) framework for web-based genetics that can be deployed anywhere. GN allows biologists to upload high-throughput experimental data, such as expression data from microarrays and RNA-seq, and also `classic' phenotypes, such as disease phenotypes. These p

  16. QTL IciMapping:Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Institute of Scientific and Technical Information of China (English)

    Lei; Meng; Huihui; Li; Luyan; Zhang; Jiankang; Wang

    2015-01-01

    QTL Ici Mapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci(QTL) in biparental populations. Eight functionalities are integrated in this software package:(1) BIN: binning of redundant markers;(2) MAP: construction of linkage maps in biparental populations;(3) CMP: consensus map construction from multiple linkage maps sharing common markers;(4) SDL: mapping of segregation distortion loci;(5) BIP: mapping of additive, dominant, and digenic epistasis genes;(6) MET: QTL-by-environment interaction analysis;(7) CSL: mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and(8) NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL,and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci,and to perform analysis of variance for multi-environmental trials.

  17. QTL IciMapping:Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Institute of Scientific and Technical Information of China (English)

    Lei Meng; Huihui Li; Luyan Zhang; Jiankang Wang

    2015-01-01

    QTL IciMapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci (QTL) in biparental populations. Eight func-tionalities are integrated in this software package: (1) BIN:binning of redundant markers;(2) MAP: construction of linkage maps in biparental populations; (3) CMP: consensus map construction from multiple linkage maps sharing common markers; (4) SDL: mapping of segregation distortion loci;(5) BIP:mapping of additive, dominant, and digenic epistasis genes;(6) MET:QTL-by-environment interaction analysis;(7) CSL:mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and (8) NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL, and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci, and to perform analysis of variance for multi-environmental trials.

  18. QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations

    Directory of Open Access Journals (Sweden)

    Lei Meng

    2015-06-01

    Full Text Available QTL IciMapping is freely available public software capable of building high-density linkage maps and mapping quantitative trait loci (QTL in biparental populations. Eight functionalities are integrated in this software package: (1 BIN: binning of redundant markers; (2 MAP: construction of linkage maps in biparental populations; (3 CMP: consensus map construction from multiple linkage maps sharing common markers; (4 SDL: mapping of segregation distortion loci; (5 BIP: mapping of additive, dominant, and digenic epistasis genes; (6 MET: QTL-by-environment interaction analysis; (7 CSL: mapping of additive and digenic epistasis genes with chromosome segment substitution lines; and (8 NAM: QTL mapping in NAM populations. Input files can be arranged in plain text, MS Excel 2003, or MS Excel 2007 formats. Output files have the same prefix name as the input but with different extensions. As examples, there are two output files in BIN, one for summarizing the identified bin groups and deleted markers in each bin, and the other for using the MAP functionality. Eight output files are generated by MAP, including summary of the completed linkage maps, Mendelian ratio test of individual markers, estimates of recombination frequencies, LOD scores, and genetic distances, and the input files for using the BIP, SDL, and MET functionalities. More than 30 output files are generated by BIP, including results at all scanning positions, identified QTL, permutation tests, and detection powers for up to six mapping methods. Three supplementary tools have also been developed to display completed genetic linkage maps, to estimate recombination frequency between two loci, and to perform analysis of variance for multi-environmental trials.

  19. Enfermedades de base genética Genetically based diseases

    Directory of Open Access Journals (Sweden)

    D. González-Lamuño

    2008-01-01

    Full Text Available La genética constituye uno de los mayores avances científicos del siglo XX, que comienza con el redescubrimiento de las leyes de Mendel y termina con la elaboración del primer "borrador" de la secuencia completa del genoma humano. La genética utiliza diferentes estrategias de investigación, como los estudios de gemelos y de adopción, que investigan la influencia de los factores genéticos y ambientales, y las estrategias para identificar genes específicos (genética molecular. Además del importante grado de discapacidad que generan, el impacto social de las enfermedades hereditarias es enorme, por su carácter potencialmente recurrente en una misma familia y por el elevado coste socio-sanitario derivado de la enorme carga de cuidados que requiere. El diagnóstico de las enfermedades hereditarias presenta características diferenciadoras muy significativas ya que el resultado de un diagnóstico genético tiene no sólo efectos sobre el paciente sino también sobre todos los individuos emparentados. Por tanto, la unidad de estudio en el diagnóstico genético es la familia y todo proceso de diagnóstico implica una investigación familiar. También conviene tener en cuenta que los protocolos de diagnóstico se desarrollan de forma paralela a la investigación básica y generalmente están poco estandarizados. Los resultados obtenidos en los estudios genéticos y el tipo de información que se facilita al paciente y a su familia deben ser matizados dentro del proceso del "consejo genético".Genetics is one of the greatest scientific advances of the XX century, which begins with the rediscovery of Mendel’s laws and culminates in the elaboration of the first "draft" of the complete sequence of the human genome. Genetics employs different research strategies, such as the study of twins and adoption, investigating the influence of genetic and environmental factors, and strategies for identifying specific genes (molecular genetics. Besides the

  20. Quantitative Assessment of the Association between Genetic Variants in MicroRNAs and Colorectal Cancer Risk

    Directory of Open Access Journals (Sweden)

    Xiao-Xu Liu

    2015-01-01

    Full Text Available Background. The associations between polymorphisms in microRNAs and the susceptibility of colorectal cancer (CRC were inconsistent in previous studies. This study aims to quantify the strength of the correlation between the four common polymorphisms among microRNAs (hsa-mir-146a rs2910164, hsa-mir-149 rs2292832, hsa-mir-196a2 rs11614913, and hsa-mir-499 rs3746444 and CRC risk. Methods. We searched PubMed, Web of Knowledge, and CNKI to find relevant studies. The combined odds ratio (OR with 95% confidence interval (95% CI was used to estimate the strength of the association in a fixed or random effect model. Results. 15 studies involving 5,486 CRC patients and 7,184 controls were included. Meta-analyses showed that rs3746444 had association with CRC risk in Caucasians (OR = 0.57, 95% CI = 0.34–0.95. In the subgroup analysis, we found significant associations between rs2910164 and CRC in hospital based studies (OR = 1.24, 95% CI = 1.03–1.49. rs2292832 may be a high risk factor of CRC in population based studied (OR = 1.18, 95% CI = 1.08–1.38. Conclusion. This meta-analysis showed that rs2910164 and rs2292832 may increase the risk of CRC. However, rs11614913 polymorphism may reduce the risk of CRC. rs3746444 may have a decreased risk to CRC in Caucasians.

  1. DISQOVER the Landcover - R based tools for quantitative vegetation reconstruction

    Science.gov (United States)

    Theuerkauf, Martin; Couwenberg, John; Kuparinen, Anna; Liebscher, Volkmar

    2016-04-01

    Quantitative methods have gained increasing attention in the field of vegetation reconstruction over the past decade. The DISQOVER package implements key tools in the R programming environment for statistical computing. This implementation has three main goals: 1) Provide a user-friendly, transparent, and open implementation of the methods 2) Provide full flexibility in all parameters (including the underlying pollen dispersal model) 3) Provide a sandbox for testing the sensitivity of the methods. We illustrate the possibilities of the package with tests of the REVEALS model and of the extended downscaling approach (EDA). REVEALS (Sugita 2007) is designed to translate pollen data from large lakes into regional vegetation composition. We applied REVEALSinR on pollen data from Lake Tiefer See (NE-Germany) and validated the results with historic landcover data. The results clearly show that REVEALS is sensitive to the underlying pollen dispersal model; REVEALS performs best when applied with the state of the art Lagrangian stochastic dispersal model. REVEALS applications with the conventional Gauss model can produce realistic results, but only if unrealistic pollen productivity estimates are used. The EDA (Theuerkauf et al. 2014) employs pollen data from many sites across a landscape to explore whether species distributions in the past were related to know stable patterns in the landscape, e.g. the distribution of soil types. The approach had so far only been implemented in simple settings with few taxa. Tests with EDAinR show that it produces sharp results in complex settings with many taxa as well. The DISQOVER package is open source software, available from disqover.uni-greifswald.de. This website can be used as a platform to discuss and improve quantitative methods in vegetation reconstruction. To introduce the tool we plan a short course in autumn of this year. This study is a contribution to the Virtual Institute of Integrated Climate and Landscape Evolution

  2. New Iris Localization Method Based on Chaos Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    Jia Dongli; Muhammad Khurram Khan; Zhang Jiashu

    2005-01-01

    This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is used to extract the boundary of the iris. Simulation results show that the proposed algorithms is efficient and robust, and can achieve sub pixel precision. Because Genetic Algorithms (GAs) can search in a large space, the algorithm does not need accurate estimation of iris center for subsequent localization, and hence can lower the requirement for original iris image processing. On this point, the present localization algirithm is superior to Daugmans algorithm.

  3. Stellar Population Analysis of Galaxies based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    Abdel-Fattah Attia; H.A.Ismail; I.M.Selim; A.M.Osman; I.A.Isaa; M.A.Marie; A.A.Shaker

    2005-01-01

    We present a new method for determining the age and relative contribution of different stellar populations in galaxies based on the genetic algorithm.We apply this method to the barred spiral galaxy NGC 3384, using CCD images in U, B, V, R and I bands. This analysis indicates that the galaxy NGC 3384 is mainly inhabited by old stellar population (age > 109 yr). Some problems were encountered when numerical simulations are used for determining the contribution of different stellar populations in the integrated color of a galaxy. The results show that the proposed genetic algorithm can search efficiently through the very large space of the possible ages.

  4. Optimizing Combination of Units Commitment Based on Improved Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    LAI Yifei; ZHANG Qianhua; JIA Junping

    2007-01-01

    GAs are general purpose optimization techniques based on principles inspired from the biological evolution using metaphors of mechanisms, such as natural selection, genetic recombination and survival of the fittest. By use of coding betterment, the dynamic changes of the mutation rate and the crossover probability, the dynamic choice of subsistence, the reservation of the optimal fitness value, a modified genetic algorithm for optimizing combination of units in thermal power plants is proposed.And through taking examples, test result are analyzed and compared with results of some different algorithms. Numerical results show available value for the unit commitment problem with examples.

  5. Intelligent DNA-based molecular diagnostics using linked genetic markers

    Energy Technology Data Exchange (ETDEWEB)

    Pathak, D.K.; Perlin, M.W.; Hoffman, E.P.

    1994-12-31

    This paper describes a knowledge-based system for molecular diagnostics, and its application to fully automated diagnosis of X-linked genetic disorders. Molecular diagnostic information is used in clinical practice for determining genetic risks, such as carrier determination and prenatal diagnosis. Initially, blood samples are obtained from related individuals, and PCR amplification is performed. Linkage-based molecular diagnosis then entails three data analysis steps. First, for every individual, the alleles (i.e., DNA composition) are determined at specified chromosomal locations. Second, the flow of genetic material among the individuals is established. Third, the probability that a given individual is either a carrier of the disease or affected by the disease is determined. The current practice is to perform each of these three steps manually, which is costly, time consuming, labor-intensive, and error-prone. As such, the knowledge-intensive data analysis and interpretation supersede the actual experimentation effort as the major bottleneck in molecular diagnostics. By examining the human problem solving for the task, we have designed and implemented a prototype knowledge-based system capable of fully automating linkage-based molecular diagnostics in X-linked genetic disorders, including Duchenne Muscular Dystrophy (DMD). Our system uses knowledge-based interpretation of gel electrophoresis images to determine individual DNA marker labels, a constraint satisfaction search for consistent genetic flow among individuals, and a blackboard-style problem solver for risk assessment. We describe the system`s successful diagnosis of DMD carrier and affected individuals from raw clinical data.

  6. Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index.

    Science.gov (United States)

    Bae, Sunghwan; Choi, Sungkyoung; Kim, Sung Min; Park, Taesung

    2016-12-01

    With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

  7. Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

    Directory of Open Access Journals (Sweden)

    Sunghwan Bae

    2016-12-01

    Full Text Available With the success of the genome-wide association studies (GWASs, many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR, least absolute shrinkage and selection operator (LASSO, and Elastic-Net (EN, using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE value on data from the Korea Association Resource (KARE with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

  8. Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

    Science.gov (United States)

    Bae, Sunghwan; Choi, Sungkyoung; Kim, Sung Min

    2016-01-01

    With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

  9. Quantitative Study on Polymer Flocculation Mechanism Based on Mathematical Morphology

    Institute of Scientific and Technical Information of China (English)

    GUO Ling-xiang; WANG Chen-yi

    2006-01-01

    Until now, understanding of polymer flocculation has remained restricted within the qualitative explanations of the bridge unite theory and the electricity neutralization theory, because people not only lacked the systemic knowledge of the polymer flocculation mechanism, the flocculation dynamic process study and the flocculation effect estimate, but also could not penetrate within the flocculation process microscopic field to obtain the structural character parameters such as floccule structure, the frame bridge models and so on. In this paper, not only coal slurry flocculation images were photographed by using the transmission electron microscope, but also the basic theory of the mathematical morphology was applied to the coal slurry flocculation image processing. The steps and methods of the mathematical morphology were expounded in detail. The micro-structural parameters such as the flocculate size and the bridge length were obtained, which combined the microscopic flocculation grain configuration observations with the macroscopic flocculation effect, so as to get the maximum amount of veracious information to describe and explain the whole flocculation course by rule and line. On this basis, not only the flocculation models of polymers in the coal slurry are suggested, but the quantitative study on flocculation mechanism has been achieved.

  10. Immune and Genetic Algorithm Based Assembly Sequence Planning

    Institute of Scientific and Technical Information of China (English)

    YANG Jian-guo; LI Bei-zhi; YU Lei; JIN Yu-song

    2004-01-01

    In this paper an assembly sequence planning model inspired by natural immune and genetic algorithm (ASPIG) based on the part degrees of freedom matrix (PDFM) is proposed, and a proto system - DSFAS based on the ASPIG is introduced to solve assembly sequence problem. The concept and generation of PDFM and DSFAS are also discussed. DSFAS can prevent premature convergence, and promote population diversity, and can accelerate the learning and convergence speed in behavior evolution problem.

  11. [Improvement of genetics teaching using literature-based learning model].

    Science.gov (United States)

    Liang, Liang; Shiqian, Liang; Hongyan, Qin; Yong, Ji; Hua, Han

    2015-06-01

    Genetics is one of the most important courses for undergraduate students majoring in life science. In recent years, new knowledge and technologies are continually updated with deeper understanding of life science. However, the teaching model of genetics is still based on theoretical instruction, which makes the abstract principles hard to understand by students and directly affects the teaching effect. Thus, exploring a new teaching model is necessary. We have carried out a new teaching model, literature-based learning, in the course on Microbial Genetics for undergraduate students majoring in biotechnology since 2010. Here we comprehensively analyzed the implementation and application value of this model including pre-course knowledge, how to choose professional literature, how to organize teaching process and the significance of developing this new teaching model for students and teachers. Our literature-based learning model reflects the combination of "cutting-edge" and "classic" and makes book knowledge easy to understand, which improves students' learning effect, stimulates their interests, expands their perspectives and develops their ability. This practice provides novel insight into exploring new teaching model of genetics and cultivating medical talents capable of doing both basic and clinical research in the "precision medicine" era.

  12. Method of stereo matching based on genetic algorithm

    Science.gov (United States)

    Lu, Chaohui; An, Ping; Zhang, Zhaoyang

    2003-09-01

    A new stereo matching scheme based on image edge and genetic algorithm (GA) is presented to improve the conventional stereo matching method in this paper. In order to extract robust edge feature for stereo matching, infinite symmetric exponential filter (ISEF) is firstly applied to remove the noise of image, and nonlinear Laplace operator together with local variance of intensity are then used to detect edges. Apart from the detected edge, the polarity of edge pixels is also obtained. As an efficient search method, genetic algorithm is applied to find the best matching pair. For this purpose, some new ideas are developed for applying genetic algorithm to stereo matching. Experimental results show that the proposed methods are effective and can obtain good results.

  13. Bovine serum albumin detection and quantitation based on capacitance measurements of liquid crystals

    Science.gov (United States)

    Lin, Chi-Hao; Lee, Mon-Juan; Lee, Wei

    2016-08-01

    Liquid crystal (LC)-based biosensing is generally limited by the lack of accurate quantitative strategies. This study exploits the unique electric capacitance properties of LCs to establish quantitative assay methods for bovine serum albumin (BSA) biomolecules. By measuring the voltage-dependent electric capacitance of LCs under an alternating-current field with increasing amplitude, positive correlations were derived between the BSA concentration and the electric capacitance parameters of LCs. This study demonstrates that quantitative analysis can be achieved in LC-based biosensing through electric capacitance measurements extensively employed in LCD research and development.

  14. A droplet-based, optofluidic device for high-throughput, quantitative bioanalysis

    OpenAIRE

    Guo, Feng; Lapsley, Michael Ian; Nawaz, Ahmad Ahsan; Zhao, Yanhui; Lin, Sz-Chin Steven; Chen, Yuchao; Yang, Shikuan; Zhao, Xing-Zhong; Huang, Tony Jun

    2012-01-01

    Analysis of chemical or biomolecular contents in a tiny amount of specimen presents a significant challenge in many biochemical studies and diagnostic applications. In this work, we present a single-layer, optofluidic device for real-time, high-throughput, quantitative analysis of droplet contents. Our device integrates an optical fiber-based, on-chip detection unit with a droplet-based microfluidic unit. It can quantitatively analyze the contents of individual droplets in real-time. It also ...

  15. International collaborative study of the endogenous reference gene LAT52 used for qualitative and quantitative analyses of genetically modified tomato.

    Science.gov (United States)

    Yang, Litao; Zhang, Haibo; Guo, Jinchao; Pan, Liangwen; Zhang, Dabing

    2008-05-28

    One tomato ( Lycopersicon esculentum) gene, LAT52, has been proved to be a suitable endogenous reference gene for genetically modified (GM) tomato detection in a previous study. Herein are reported the results of a collaborative ring trial for international validation of the LAT52 gene as endogenous reference gene and its analytical systems; 14 GMO detection laboratories from 8 countries were invited, and results were finally received from 13. These data confirmed the species specificity by testing 10 plant genomic DNAs, less allelic variation and stable single copy number of the LAT52 gene, among 12 different tomato cultivars. Furthermore, the limit of detection of LAT52 qualitative PCR was proved to be 0.1%, which corresponded to 11 copies of haploid tomato genomic DNA, and the limit of quantification for the quantitative PCR system was about 10 copies of haploid tomato genomic DNA with acceptable PCR efficiency and linearity. Additionally, the bias between the test and true values of 8 blind samples ranged from 1.94 to 10.64%. All of these validated results indicated that the LAT52 gene is suitable for use as an endogenous reference gene for the identification and quantification of GM tomato and its derivates.

  16. Molecular–Genetic Imaging: A Nuclear Medicine–Based Perspective

    Directory of Open Access Journals (Sweden)

    Ronald G. Blasberg

    2002-07-01

    Full Text Available Molecular imaging is a relatively new discipline, which developed over the past decade, initially driven by in situ reporter imaging technology. Noninvasive in vivo molecular–genetic imaging developed more recently and is based on nuclear (positron emission tomography [PET], gamma camera, autoradiography imaging as well as magnetic resonance (MR and in vivo optical imaging. Molecular–genetic imaging has its roots in both molecular biology and cell biology, as well as in new imaging technologies. The focus of this presentation will be nuclear-based molecular–genetic imaging, but it will comment on the value and utility of combining different imaging modalities. Nuclear-based molecular imaging can be viewed in terms of three different imaging strategies: (1 “indirect” reporter gene imaging; (2 “direct” imaging of endogenous molecules; or (3 “surrogate” or “bio-marker” imaging. Examples of each imaging strategy will be presented and discussed. The rapid growth of in vivo molecular imaging is due to the established base of in vivo imaging technologies, the established programs in molecular and cell biology, and the convergence of these disciplines. The development of versatile and sensitive assays that do not require tissue samples will be of considerable value for monitoring molecular–genetic and cellular processes in animal models of human disease, as well as for studies in human subjects in the future. Noninvasive imaging of molecular–genetic and cellular processes will complement established ex vivo molecular–biological assays that require tissue sampling, and will provide a spatial as well as a temporal dimension to our understanding of various diseases and disease processes.

  17. A Quantitative Analysis of Published Skull Base Endoscopy Literature.

    Science.gov (United States)

    Hardesty, Douglas A; Ponce, Francisco A; Little, Andrew S; Nakaji, Peter

    2016-02-01

    Objectives Skull base endoscopy allows for minimal access approaches to the sinonasal contents and cranial base. Advances in endoscopic technique and applications have been published rapidly in recent decades. Setting We utilized an Internet-based scholarly database (Web of Science, Thomson Reuters) to query broad-based phrases regarding skull base endoscopy literature. Participants All skull base endoscopy publications. Main Outcome Measures Standard bibliometrics outcomes. Results We identified 4,082 relevant skull base endoscopy English-language articles published between 1973 and 2014. The 50 top-cited publications (n = 51, due to articles with equal citation counts) ranged in citation count from 397 to 88. Most of the articles were clinical case series or technique descriptions. Most (96% [49/51])were published in journals specific to either neurosurgery or otolaryngology. Conclusions A relatively small number of institutions and individuals have published a large amount of the literature. Most of the publications consisted of case series and technical advances, with a lack of randomized trials.

  18. Quantitative assessment of hip osteoarthritis based on image texture analysis.

    Science.gov (United States)

    Boniatis, I S; Costaridou, L I; Cavouras, D A; Panagiotopoulos, E C; Panayiotakis, G S

    2006-03-01

    A non-invasive method was developed to investigate the potential capacity of digital image texture analysis in evaluating the severity of hip osteoarthritis (OA) and in monitoring its progression. 19 textural features evaluating patterns of pixel intensity fluctuations were extracted from 64 images of radiographic hip joint spaces (HJS), corresponding to 32 patients with verified unilateral or bilateral OA. Images were enhanced employing custom developed software for the delineation of the articular margins on digitized pelvic radiographs. The severity of OA for each patient was assessed by expert orthopaedists employing the Kellgren and Lawrence (KL) scale. Additionally, an index expressing HJS-narrowing was computed considering patients from the unilateral OA-group. A textural feature that quantified pixel distribution non-uniformity (grey level non-uniformity, GLNU) demonstrated the strongest correlation with the HJS-narrowing index among all extracted features and utilized in further analysis. Classification rules employing GLNU feature were introduced to characterize a hip as normal or osteoarthritic and to assign it to one of three severity categories, formed in accordance with the KL scale. Application of the proposed rules resulted in relatively high classification accuracies in characterizing a hip as normal or osteoarthritic (90.6%) and in assigning it to the correct KL scale category (88.9%). Furthermore, the strong correlation between the HJS-narrowing index and the pathological GLNU (r = -0.9, p<0.001) was utilized to provide percentages quantifying hip OA-severity. Texture analysis may contribute in the quantitative assessment of OA-severity, in the monitoring of OA-progression and in the evaluation of a chondroprotective therapy.

  19. School-Based Home Instruction and Learning: A Quantitative Synthesis.

    Science.gov (United States)

    Graue, M. Elizabeth; And Others

    1983-01-01

    Research on elementary school-based programs for increasing the educationally stimulating qualities of the home environment was statistically synthesized in a qualitative analysis of 29 controlled studies. Of 121 comparisons made in the analysis, 91.1 percent favored treatment over control groups, thus pointing to the effectiveness of these…

  20. Quantitative exposure assessment in community-based studies

    NARCIS (Netherlands)

    Peters, S.M.|info:eu-repo/dai/nl/304822930

    2012-01-01

    Occupational epidemiology focuses on the associations between exposures at the workplace and disease outcomes, essentially concerned with the prevention of disease. Basically two types of studies can be distinguished in occupational epidemiology: industry-based studies which study a population at

  1. Genetic Algorithm based PID controller for Frequency Regulation Ancillary services

    Directory of Open Access Journals (Sweden)

    Sandeep Bhongade

    2010-12-01

    Full Text Available In this paper, the parameters of Proportional, Integral and Derivative (PID controller for Automatic Generation Control (AGC suitable in restructured power system is tuned according to Generic Algorithms (GAs based performance indices. The key idea of the proposed method is to use the fitness function based on Area Control Error (ACE. The functioning of the proposed Genetic Algorithm based PID (GAPID controller has been demonstrated on a 75-bus Indian power system network and the results have been compared with those obtained by using Least Square Minimization method.

  2. MaGelLAn 1.0: a software to facilitate quantitative and population genetic analysis of maternal inheritance by combination of molecular and pedigree information.

    Science.gov (United States)

    Ristov, Strahil; Brajkovic, Vladimir; Cubric-Curik, Vlatka; Michieli, Ivan; Curik, Ino

    2016-09-10

    Identification of genes or even nucleotides that are responsible for quantitative and adaptive trait variation is a difficult task due to the complex interdependence between a large number of genetic and environmental factors. The polymorphism of the mitogenome is one of the factors that can contribute to quantitative trait variation. However, the effects of the mitogenome have not been comprehensively studied, since large numbers of mitogenome sequences and recorded phenotypes are required to reach the adequate power of analysis. Current research in our group focuses on acquiring the necessary mitochondria sequence information and analysing its influence on the phenotype of a quantitative trait. To facilitate these tasks we have produced software for processing pedigrees that is optimised for maternal lineage analysis. We present MaGelLAn 1.0 (maternal genealogy lineage analyser), a suite of four Python scripts (modules) that is designed to facilitate the analysis of the impact of mitogenome polymorphism on quantitative trait variation by combining molecular and pedigree information. MaGelLAn 1.0 is primarily used to: (1) optimise the sampling strategy for molecular analyses; (2) identify and correct pedigree inconsistencies; and (3) identify maternal lineages and assign the corresponding mitogenome sequences to all individuals in the pedigree, this information being used as input to any of the standard software for quantitative genetic (association) analysis. In addition, MaGelLAn 1.0 allows computing the mitogenome (maternal) effective population sizes and probability of mitogenome (maternal) identity that are useful for conservation management of small populations. MaGelLAn is the first tool for pedigree analysis that focuses on quantitative genetic analyses of mitogenome data. It is conceived with the purpose to significantly reduce the effort in handling and preparing large pedigrees for processing the information linked to maternal lines. The software source

  3. Genetic Algorithm Based Hybrid Fuzzy System for Assessing Morningness

    Directory of Open Access Journals (Sweden)

    Animesh Biswas

    2014-01-01

    Full Text Available This paper describes a real life case example on the assessment process of morningness of individuals using genetic algorithm based hybrid fuzzy system. It is observed that physical and mental performance of human beings in different time slots of a day are majorly influenced by morningness orientation of those individuals. To measure the morningness of people various self-reported questionnaires were developed by different researchers in the past. Among them reduced version of Morningness-Eveningness Questionnaire is mostly accepted. Almost all of the linguistic terms used in questionnaires are fuzzily defined. So, assessing them in crisp environments with their responses does not seem to be justifiable. Fuzzy approach based research works for assessing morningness of people are very few in the literature. In this paper, genetic algorithm is used to tune the parameters of a Mamdani fuzzy inference model to minimize error with their predicted outputs for assessing morningness of people.

  4. Genetic algorithm-based evaluation of spatial straightness error

    Institute of Scientific and Technical Information of China (English)

    崔长彩; 车仁生; 黄庆成; 叶东; 陈刚

    2003-01-01

    A genetic algorithm ( GA ) -based approach is proposed to evaluate the straightness error of spatial lines. According to the mathematical definition of spatial straightness, a verification model is established for straightness error, and the fitness function of GA is then given and the implementation techniques of the proposed algorithm is discussed in detail. The implementation techniques include real number encoding, adaptive variable range choosing, roulette wheel and elitist combination selection strategies, heuristic crossover and single point mutation schemes etc. An application example is quoted to validate the proposed algorithm. The computation result shows that the GA-based approach is a superior nonlinear parallel optimization method. The performance of the evolution population can be improved through genetic operations such as reproduction, crossover and mutation until the optimum goal of the minimum zone solution is obtained. The quality of the solution is better and the efficiency of computation is higher than other methods.

  5. Genetic algorithm for network cost minimization using threshold based discounting

    Directory of Open Access Journals (Sweden)

    Hrvoje Podnar

    2003-01-01

    Full Text Available We present a genetic algorithm for heuristically solving a cost minimization problem applied to communication networks with threshold based discounting. The network model assumes that every two nodes can communicate and offers incentives to combine flow from different sources. Namely, there is a prescribed threshold on every link, and if the total flow on a link is greater than the threshold, the cost of this flow is discounted by a factor α. A heuristic algorithm based on genetic strategy is developed and applied to a benchmark set of problems. The results are compared with former branch and bound results using the CPLEX® solver. For larger data instances we were able to obtain improved solutions using less CPU time, confirming the effectiveness of our heuristic approach.

  6. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats

    NARCIS (Netherlands)

    Baud, Amelie; Hermsen, Roel; Guryev, Victor; Stridh, Pernilla; Graham, Delyth; McBride, Martin W.; Foroud, Tatiana; Calderari, Sophie; Diez, Margarita; Ockinger, Johan; Beyeen, Amennai D.; Gillett, Alan; Abdelmagid, Nada; Guerreiro-Cacais, Andre Ortlieb; Jagodic, Maja; Tuncel, Jonatan; Norin, Ulrika; Beattie, Elisabeth; Huynh, Ngan; Miller, William H.; Koller, Daniel L.; Alam, Imranul; Falak, Samreen; Osborne-Pellegrin, Mary; Martinez-Membrives, Esther; Canete, Toni; Blazquez, Gloria; Vicens-Costa, Elia; Mont-Cardona, Carme; Diaz-Moran, Sira; Tobena, Adolf; Hummel, Oliver; Zelenika, Diana; Saar, Kathrin; Patone, Giannino; Bauerfeind, Anja; Bihoreau, Marie-Therese; Heinig, Matthias; Lee, Young-Ae; Rintisch, Carola; Schulz, Herbert; Wheeler, David A.; Worley, Kim C.; Muzny, Donna M.; Gibbs, Richard A.; Lathrop, Mark; Lansu, Nico; Toonen, Pim; Ruzius, Frans Paul; de Bruijn, Ewart; Hauser, Heidi; Adams, David J.; Keane, Thomas; Atanur, Santosh S.; Aitman, Tim J.; Flicek, Paul; Malinauskas, Tomas; Jones, E. Yvonne; Ekman, Diana; Lopez-Aumatell, Regina; Dominiczak, Anna F.; Johannesson, Martina; Holmdahl, Rikard; Olsson, Tomas; Gauguier, Dominique; Hubner, Norbert; Fernandez-Teruel, Alberto; Cuppen, Edwin; Mott, Richard; Flint, Jonathan

    2013-01-01

    Genetic mapping on fully sequenced individuals is transforming understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We i

  7. Magnetic Resonance-based Motion Correction for Quantitative PET in Simultaneous PET-MR Imaging.

    Science.gov (United States)

    Rakvongthai, Yothin; El Fakhri, Georges

    2017-07-01

    Motion degrades image quality and quantitation of PET images, and is an obstacle to quantitative PET imaging. Simultaneous PET-MR offers a tool that can be used for correcting the motion in PET images by using anatomic information from MR imaging acquired concurrently. Motion correction can be performed by transforming a set of reconstructed PET images into the same frame or by incorporating the transformation into the system model and reconstructing the motion-corrected image. Several phantom and patient studies have validated that MR-based motion correction strategies have great promise for quantitative PET imaging in simultaneous PET-MR. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling (GPM) algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space, and the Particle Swarm Optimization (PSO) algorithm is used for Nonlinear Parameter Estimation (NPE) of dynamic model structures. In addition, GPM integrates the results of Nonlinear Time Series Analysis (NTSA) to adjust the parameters and takes them as the criteria of established models. Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  9. Broadening the application of evolutionarily based genetic pest management.

    Science.gov (United States)

    Gould, Fred

    2008-02-01

    Insect- and tick-vectored diseases such as malaria, dengue fever, and Lyme disease cause human suffering, and current approaches for prevention are not adequate. Invasive plants and animals such as Scotch broom, zebra mussels, and gypsy moths continue to cause environmental damage and economic losses in agriculture and forestry. Rodents transmit diseases and cause major pre- and postharvest losses, especially in less affluent countries. Each of these problems might benefit from the developing field of Genetic Pest Management that is conceptually based on principles of evolutionary biology. This article briefly describes the history of this field, new molecular tools in this field, and potential applications of those tools. There will be a need for evolutionary biologists to interact with researchers and practitioners in a variety of other fields to determine the most appropriate targets for genetic pest management, the most appropriate methods for specific targets, and the potential of natural selection to diminish the effectiveness of genetic pest management. In addition to producing environmentally sustainable pest management solutions, research efforts in this area could lead to new insights about the evolution of selfish genetic elements in natural systems and will provide students with the opportunity to develop a more sophisticated understanding of the role of evolutionary biology in solving societal problems.

  10. Quantitative trait locus mapping with background control in genetic populations of clonal F1 and double cross.

    Science.gov (United States)

    Zhang, Luyan; Li, Huihui; Ding, Junqiang; Wu, Jianyu; Wang, Jiankang

    2015-12-01

    In this study, we considered five categories of molecular markers in clonal F1 and double cross populations, based on the number of distinguishable alleles and the number of distinguishable genotypes at the marker locus. Using the completed linkage maps, incomplete and missing markers were imputed as fully informative markers in order to simplify the linkage mapping approaches of quantitative trait genes. Under the condition of fully informative markers, we demonstrated that dominance effect between the female and male parents in clonal F1 and double cross populations can cause the interactions between markers. We then developed an inclusive linear model that includes marker variables and marker interactions so as to completely control additive effects of the female and male parents, as well as the dominance effect between the female and male parents. The linear model was finally used for background control in inclusive composite interval mapping (ICIM) of quantitative trait locus (QTL). The efficiency of ICIM was demonstrated by extensive simulations and by comparisons with simple interval mapping, multiple-QTL models and composite interval mapping. Finally, ICIM was applied in one actual double cross population to identify QTL on days to silking in maize.

  11. Support Vector Machine Ensemble Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Ye; YIN Ru-po; CAI Yun-ze; XU Xiao-ming

    2006-01-01

    Support vector machines (SVMs) have been introduced as effective methods for solving classification problems.However, due to some limitations in practical applications,their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble (DGE), is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE.Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs,bagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.

  12. Evaluation of stable isotope labelling strategies for the quantitation of CP4 EPSPS in genetically modified soya

    Energy Technology Data Exchange (ETDEWEB)

    Ocana, Mireia Fernandez [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom)], E-mail: Mireia.FernandezOcana@pfizer.com; Fraser, Paul D. [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom); Patel, Raj K.P.; Halket, John M. [Specialist Bioanalytical Services Ltd., Royal Holloway, University of London, Egham TW20 0EX (United Kingdom); Bramley, Peter M. [Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX (United Kingdom)

    2009-02-16

    The introduction of genetically modified (GM) crops into the market has raised a general alertness relating to the control and safety of foods. The applicability of protein separation hyphenated to mass spectrometry to identify the bacterial enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) protein expressed in GM crops has been previously reported [M.F. Ocana, P.D. Fraser, R.K.P. Patel, J.M. Halket, P.M. Bramley, Rapid Commun. Mass Spectrom. 21 (2007) 319.]. Herein, we investigate the suitability of two strategies that employ heavy stable isotopes, i.e. AQUA and iTRAQ, to quantify different levels of CP4 EPSPS in up to four GM preparations. Both quantification strategies showed potential to determine whether the presence of GM material is above the limits established by the European Union. The AQUA quantification procedure involved protein solubilisation/fractionation and subsequent separation using SDS-PAGE. A segment of the gel in which the protein of interest was located was excised, the stable isotope labeled peptide added at a known concentration and proteolytic digestion initiated. Following recovery of the peptides, on-line separation and detection using LC-MS was carried out. A similar approach was used for the iTRAQ workflow with the exception that proteins were digested in solution and generated tryptic peptides were chemically tagged. Both procedures demonstrated the potential for quantitative detection at 0.5% (w/w) GM soya which is a level below the current European Union's threshold for food-labelling. In this context, a comparison between the two procedures is provided within the present study.

  13. Quantitative ultrasound of the hand phalanges in a cohort of monozygotic twins: influence of genetic and environmental factors

    Energy Technology Data Exchange (ETDEWEB)

    Guglielmi, G. [Scientific Institute Hospital, Department of Radiology, San Giovanni Rotondo (Italy); Terlizzi, F. de [IGEA Biophysics Lab, Carpi (Italy); Torrente, I.; Mingarelli, R. [Mendel Institute, Rome (Italy); Dallapiccola, B. [Scientific Institute Hospital, Department of Radiology, San Giovanni Rotondo (Italy); Mendel Institute, Rome (Italy)

    2005-11-01

    Our objective was to evaluate the similarities and differences in bone mass and structure between pairs of monozygotic twins as measured by means of the quantitative ultrasound (QUS) technique. A cohort of monozygotic twins was measured by QUS of the hand phalanges using the DBM sonic bone profiler (IGEA, Carpi, Italy). The parameters studied were amplitude-dependent speed of sound (AD-SoS), ultrasound bone profile index (UBPI), signal dynamics (SDy) and bone transmission time (BTT). Linear correlation coefficients, multivariate linear analysis and the ANOVA test were used to assess intrapair associations between variables and to determine which factors influence the intrapair differences in QUS variables. One hundred and six pairs of monozygotic twins were enrolled in the study, 68 females and 38 males in the age range 5 to 71 years. Significant intrapair correlations were obtained in the whole population and separately for males and females, regarding height (r =0.98-0.99, p <0.0001), weight (r =0.95-0.96, p <0.0001), AD-SoS (r =0.90-0.92, p <0.0001), BTT (r =0.94-0.95, p <0.0001) and other QUS parameters (r >0.74, p <0.0001). Multivariate analysis revealed that intrapair differences between AD-SoS, SDy, UBPI and BTT are significantly influenced by age in the whole population and in the female population. Furthermore, the ANOVA test showed, for the female group, a significant increase in the intrapair differences in SDy and UBPI above 40 years. A relative contribution of genetic factors to skeletal status could be observed by phalangeal QUS measurement in monozygotic twins. A significant increase in the intrapair difference in QUS parameters with increasing age and onset of menopause also suggests the importance of environmental factors in the female twin population. (orig.)

  14. Network-based group variable selection for detecting expression quantitative trait loci (eQTL

    Directory of Open Access Journals (Sweden)

    Zhang Xuegong

    2011-06-01

    Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

  15. A microcomputer-based system for quantitative petrographic analysis

    Science.gov (United States)

    Starkey, John; Samantaray, Abani Kanta

    1994-11-01

    An imaging system based on a videocamera and frame grabber is described which is capable of capturing and analyzing composite images. Individual images are captured interactively, this permits manipulation of the illumination to emphasize selected features of interest in sequentially captured images. Data from the sequential images are accumulated to form a synoptic image, which allows analysis to proceed in a manner which emulates the techniques of manual, polarized light microscopy. The effects of rotating a thin section in plane and crossed polarized light can be simulated so that mineral boundaries can be detected across which there is a lack of contrast at some orientations. The imaging system implements algorithms for digital filtering and boundary identification and incorporates facilities for image editing. Mathematical functions are provided for the interpolation of boundaries which are not detected in their entirety, in a way analogous to visual interpretation. The image data are written to 256-color PCX image files which can be manipulated by other software or transmitted electronically. The locations of the boundaries of the features of interest are available as lists of ( x, y) coordinates and as chain codes. From these the size, shape, and spatial parameters are computed. In addition, the gray-level and segmented images are used to obtain texture information. The imaging system is illustrated by application to the analysis of grain boundaries, modal composition, and grain shapes in petrographic thin sections. The analytical results are compared with results obtained by traditional petrographic analyses.

  16. Quantitative and Sensitive RNA Based Detection of Bacillus Spores

    Directory of Open Access Journals (Sweden)

    Ekaterina eOsmekhina

    2014-03-01

    Full Text Available The fast and reliable detection of bacterial spores is of great importance and still remains a challenge. Here we describe a direct RNA based diagnostic method for the specific detection of viable bacterial spores which does not depends on an enzymatic amplification step and therefore is directly appropriate for quantification. The procedure includes the following steps: (i heat activation of spores, (ii germination and enrichment cultivation, (iii cell lysis, and (iv analysis of 16S rRNA in crude cell lysates using a sandwich hybridization assay. The sensitivity of the method is dependent on the cultivation time and the detection limit; it is possible to detect 10 spores per ml when the RNA analysis is performed after 6 h of enrichment cultivation. At spore concentrations above 106 spores per ml the cultivation time can be shortened to 30 min. Total analysis times are in the range of 2 to 8 hours depending on the spore concentration in samples. The developed procedure is optimized at the example of Bacillus subtilis spores but should be applicable to other organisms. The new method can easily be modified for other target RNAs and is suitable for specific detection of spores from known groups of organisms.

  17. First application of a microsphere-based immunoassay to the detection of genetically modified organisms (GMOs): quantification of Cry1Ab protein in genetically modified maize.

    Science.gov (United States)

    Fantozzi, Anna; Ermolli, Monica; Marini, Massimiliano; Scotti, Domenico; Balla, Branko; Querci, Maddalena; Langrell, Stephen R H; Van den Eede, Guy

    2007-02-21

    An innovative covalent microsphere immunoassay, based on the usage of fluorescent beads coupled to a specific antibody, was developed for the quantification of the endotoxin Cry1Ab present in MON810 and Bt11 genetically modified (GM) maize lines. In particular, a specific protocol was developed to assess the presence of Cry1Ab in a very broad range of GM maize concentrations, from 0.1 to 100% [weight of genetically modified organism (GMO)/weight]. Test linearity was achieved in the range of values from 0.1 to 3%, whereas fluorescence signal increased following a nonlinear model, reaching a plateau at 25%. The limits of detection and quantification were equal to 0.018 and 0.054%, respectively. The present study describes the first application of quantitative high-throughput immunoassays in GMO analysis.

  18. Genetic Algorithm based Decentralized PI Type Controller: Load Frequency Control

    Science.gov (United States)

    Dwivedi, Atul; Ray, Goshaidas; Sharma, Arun Kumar

    2016-12-01

    This work presents a design of decentralized PI type Linear Quadratic (LQ) controller based on genetic algorithm (GA). The proposed design technique allows considerable flexibility in defining the control objectives and it does not consider any knowledge of the system matrices and moreover it avoids the solution of algebraic Riccati equation. To illustrate the results of this work, a load-frequency control problem is considered. Simulation results reveal that the proposed scheme based on GA is an alternative and attractive approach to solve load-frequency control problem from both performance and design point of views.

  19. A meta-learning system based on genetic algorithms

    Science.gov (United States)

    Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain

    2004-04-01

    The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system"s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.

  20. Evaluation of quantitative accuracy in CZT-based pre-clinical SPECT for various isotopes

    Science.gov (United States)

    Park, S.-J.; Yu, A. R.; Kim, Y.-s.; Kang, W.-S.; Jin, S. S.; Kim, J.-S.; Son, T. J.; Kim, H.-J.

    2015-05-01

    In vivo pre-clinical single-photon emission computed tomography (SPECT) is a valuable tool for functional small animal imaging, but several physical factors, such as scatter radiation, limit the quantitative accuracy of conventional scintillation crystal-based SPECT. Semiconductor detectors such as CZT overcome these deficiencies through superior energy resolution. To our knowledge, little scientific information exists regarding the accuracy of quantitative analysis in CZT-based pre-clinical SPECT systems for different isotopes. The aim of this study was to assess the quantitative accuracy of CZT-based pre-clinical SPECT for four isotopes: 201Tl, 99mTc, 123I, and 111In. The quantitative accuracy of the CZT-based Triumph X-SPECT (Gamma-Medica Ideas, Northridge, CA, U.S.A.) was compared with that of a conventional SPECT using GATE simulation. Quantitative errors due to the attenuation and scatter effects were evaluated for all four isotopes with energy windows of 5%, 10%, and 20%. A spherical source containing the isotope was placed at the center of the air-or-water-filled mouse-sized cylinder phantom. The CZT-based pre-clinical SPECT was more accurate than the conventional SPECT. For example, in the conventional SPECT with an energy window of 10%, scatter effects degraded quantitative accuracy by up to 11.52%, 5.10%, 2.88%, and 1.84% for 201Tl, 99mTc, 123I, and 111In, respectively. However, with the CZT-based pre-clinical SPECT, the degradations were only 9.67%, 5.45%, 2.36%, and 1.24% for 201Tl, 99mTc, 123I, and 111In, respectively. As the energy window was increased, the quantitative errors increased in both SPECT systems. Additionally, the isotopes with lower energy of photon emissions had greater quantitative error. Our results demonstrated that the CZT-based pre-clinical SPECT had lower overall quantitative errors due to reduced scatter and high detection efficiency. Furthermore, the results of this systematic assessment quantifying the accuracy of these SPECT

  1. PROSPECTIVE STUDY OF MULTIPLE GENETIC TUMOR MARKER ASSAY BY QUANTITATIVE REAL-TIME PCR TO PREDICT RECURRENCE IN COLORECTAL CANCER PATIENTS

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Objective To describe correlation between multiple genetic tumor markers,carcinoembryonic antigen (CEA),cytokeratin 20 (CK20),and Survivin,and clinicopathological features of colorectal cancer (CRC) and to assess prognostic diagnosis value in cancer recurrence and metastasis.Methods A total of 92 patients with CRC,68 patients with precancerous lesions,and 29 control volunteers were collected for the detection of CEA,CK20,and Survivin expressions by using quantitative Real-Time PCR technology.Associations am...

  2. A Quantitative Corpus-Based Approach to English Spatial Particles: Conceptual Symmetry and Its Pedagogical Implications

    Science.gov (United States)

    Chen, Alvin Cheng-Hsien

    2014-01-01

    The present study aims to investigate how conceptual symmetry plays a role in the use of spatial particles in English and to further examine its pedagogical implications via a corpus-based evaluation of the course books in senior high schools in Taiwan. More specifically, we adopt a quantitative corpus-based approach to investigate whether bipolar…

  3. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  4. Recognition of digital characteristics based new improved genetic algorithm

    Science.gov (United States)

    Wang, Meng; Xu, Guoqiang; Lin, Zihao

    2017-08-01

    In the field of digital signal processing, Estimating the characteristics of signal modulation parameters is an significant research direction. The paper determines the set of eigenvalue which can show the difference of the digital signal modulation based on the deep research of the new improved genetic algorithm. Firstly take them as the best gene pool; secondly, The best gene pool will be changed in the genetic evolvement by selecting, overlapping and eliminating each other; Finally, Adapting the strategy of futher enhance competition and punishment to more optimizer the gene pool and ensure each generation are of high quality gene. The simulation results show that this method not only has the global convergence, stability and faster convergence speed.

  5. A dynamic fuzzy clustering method based on genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHENG Yan; ZHOU Chunguang; LIANG Yanchun; GUO Dongwei

    2003-01-01

    A dynamic fuzzy clustering method is presented based on the genetic algorithm. By calculating the fuzzy dissimilarity between samples the essential associations among samples are modeled factually. The fuzzy dissimilarity between two samples is mapped into their Euclidean distance, that is, the high dimensional samples are mapped into the two-dimensional plane. The mapping is optimized globally by the genetic algorithm, which adjusts the coordinates of each sample, and thus the Euclidean distance, to approximate to the fuzzy dissimilarity between samples gradually. A key advantage of the proposed method is that the clustering is independent of the space distribution of input samples, which improves the flexibility and visualization. This method possesses characteristics of a faster convergence rate and more exact clustering than some typical clustering algorithms. Simulated experiments show the feasibility and availability of the proposed method.

  6. Healing Temperature of Hybrid Structures Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    赵中伟; 陈志华; 刘红波

    2016-01-01

    The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radiation was derived by FLUENT to investigate the influence of solar radiation on the determination of the healing temperature. Moreover, a multi-scale model was established to apply the complex temperature field under solar radiation. The change in the mechanical response of these two kinds of structures with the healing temperature was discussed. It can be concluded that solar radiation has great influence on the healing temperature, and the genetic algorithm can be effectively used in the optimization of the healing temperature for hybrid structures.

  7. Quantitative data analysis methods for bead-based DNA hybridization assays using generic flow cytometry platforms.

    Science.gov (United States)

    Corrie, S R; Lawrie, G A; Battersby, B J; Ford, K; Rühmann, A; Koehler, K; Sabath, D E; Trau, M

    2008-05-01

    Bead-based assays are in demand for rapid genomic and proteomic assays for both research and clinical purposes. Standard quantitative procedures addressing raw data quality and analysis are required to ensure the data are consistent and reproducible across laboratories independent of flow platform. Quantitative procedures have been introduced spanning raw histogram analysis through to absolute target quantitation. These included models developed to estimate the absolute number of sample molecules bound per bead (Langmuir isotherm), relative quantitative comparisons (two-sided t-tests), and statistical analyses investigating the quality of raw fluorescence data. The absolute target quantitation method revealed a concentration range (below probe saturation) of Cy5-labeled synthetic cytokeratin 19 (K19) RNA of c.a. 1 x 10(4) to 500 x 10(4) molecules/bead, with a binding constant of c.a. 1.6 nM. Raw hybridization frequency histograms were observed to be highly reproducible across 10 triplex assay replicates and only three assay replicates were required to distinguish overlapping peaks representing small sequence mismatches. This study provides a quantitative scheme for determining the absolute target concentration in nucleic acid hybridization reactions and the equilibrium binding constants for individual probe/target pairs. It is envisaged that such studies will form the basis of standard analytical procedures for bead-based cytometry assays to ensure reproducibility in inter- and intra-platform comparisons of data between laboratories. (c) 2008 International Society for Advancement of Cytometry.

  8. Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-06-01

    Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. UG157 and DPU915 were good general combiners. Two crosses namely PDB 88-31/DPU 915 and PLU 277/KAU7 had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

  9. Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

    Directory of Open Access Journals (Sweden)

    Supriyo CHAKRABORTY

    2010-06-01

    Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. �UG157� and �DPU915� were good general combiners. Two crosses namely �PDB 88-31�/�DPU 915� and �PLU 277�/�KAU7� had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

  10. Genetic map of Triticum turgidum based on a hexaploid wheat population without genetic recombination for D genome

    Directory of Open Access Journals (Sweden)

    Zhang Li

    2012-08-01

    Full Text Available Abstract Background A synthetic doubled-haploid hexaploid wheat population, SynDH1, derived from the spontaneous chromosome doubling of triploid F1 hybrid plants obtained from the cross of hybrids Triticum turgidum ssp. durum line Langdon (LDN and ssp. turgidum line AS313, with Aegilops tauschii ssp. tauschii accession AS60, was previously constructed. SynDH1 is a tetraploidization-hexaploid doubled haploid (DH population because it contains recombinant A and B chromosomes from two different T. turgidum genotypes, while all the D chromosomes from Ae. tauschii are homogenous across the whole population. This paper reports the construction of a genetic map using this population. Results Of the 606 markers used to assemble the genetic map, 588 (97% were assigned to linkage groups. These included 513 Diversity Arrays Technology (DArT markers, 72 simple sequence repeat (SSR, one insertion site-based polymorphism (ISBP, and two high-molecular-weight glutenin subunit (HMW-GS markers. These markers were assigned to the 14 chromosomes, covering 2048.79 cM, with a mean distance of 3.48 cM between adjacent markers. This map showed good coverage of the A and B genome chromosomes, apart from 3A, 5A, 6A, and 4B. Compared with previously reported maps, most shared markers showed highly consistent orders. This map was successfully used to identify five quantitative trait loci (QTL, including two for spikelet number on chromosomes 7A and 5B, two for spike length on 7A and 3B, and one for 1000-grain weight on 4B. However, differences in crossability QTL between the two T. turgidum parents may explain the segregation distortion regions on chromosomes 1A, 3B, and 6B. Conclusions A genetic map of T. turgidum including 588 markers was constructed using a synthetic doubled haploid (SynDH hexaploid wheat population. Five QTLs for three agronomic traits were identified from this population. However, more markers are needed to increase the density and resolution of

  11. A reference-gene-based quantitative PCR method as a tool to determine Fusarium resistance in wheat.

    Science.gov (United States)

    Brunner, Kurt; Kovalsky Paris, Maria P; Paolino, Guadalupe; Bürstmayr, Hermann; Lemmens, Marc; Berthiller, Franz; Schuhmacher, Rainer; Krska, Rudolf; Mach, Robert L

    2009-11-01

    In recent years, plant breeders made great progress in breeding Fusarium-tolerant wheat lines. However, total resistance to this genus of plant pathogenic fungi has not yet been achieved as the resistance genes are located on several distinct genetic regions. Visual scoring of disease symptoms in combination with the analysis of mycotoxins is commonly applied to assess the tolerance of new lines. Both approaches are indirect methods and do not mandatorily determine the accumulated fungal biomass. Quantitative PCR is a useful tool to assess fungal biomass based on the abundance of organism-specific DNA. The aim of this study was the development of a quantitative PCR assay for trichothecene-producing Fusarium species and to adapt this method for resistance assessment of wheat lines artificially infected with Fusarium graminearum and Fusarium culmorum. Several DNA-extraction methods for wheat samples were evaluated and optimized for downstream real-time PCR analysis and furthermore, a new reference-gene-based approach for more accurate quantification of Fusarium biomass in cereals is presented. The co-determination of a plant gene was used to compensate for unequal DNA-extraction efficiencies.

  12. A novel pipeline based FPGA implementation of a genetic algorithm

    Science.gov (United States)

    Thirer, Nonel

    2014-05-01

    To solve problems when an analytical solution is not available, more and more bio-inspired computation techniques have been applied in the last years. Thus, an efficient algorithm is the Genetic Algorithm (GA), which imitates the biological evolution process, finding the solution by the mechanism of "natural selection", where the strong has higher chances to survive. A genetic algorithm is an iterative procedure which operates on a population of individuals called "chromosomes" or "possible solutions" (usually represented by a binary code). GA performs several processes with the population individuals to produce a new population, like in the biological evolution. To provide a high speed solution, pipelined based FPGA hardware implementations are used, with a nstages pipeline for a n-phases genetic algorithm. The FPGA pipeline implementations are constraints by the different execution time of each stage and by the FPGA chip resources. To minimize these difficulties, we propose a bio-inspired technique to modify the crossover step by using non identical twins. Thus two of the chosen chromosomes (parents) will build up two new chromosomes (children) not only one as in classical GA. We analyze the contribution of this method to reduce the execution time in the asynchronous and synchronous pipelines and also the possibility to a cheaper FPGA implementation, by using smaller populations. The full hardware architecture for a FPGA implementation to our target ALTERA development card is presented and analyzed.

  13. Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Jimin; SHANG Chaoxuan; ZOU Minghu

    2007-01-01

    The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.

  14. Application layer multicast routing solution based on genetic algorithms

    Institute of Scientific and Technical Information of China (English)

    Peng CHENG; Qiufeng WU; Qionghai DAI

    2009-01-01

    Application layer multicast routing is a multi-objective optimization problem.Three routing con-straints,tree's cost,tree's balance and network layer load distribution are analyzed in this paper.The three fitness functions are used to evaluate a multicast tree on the three indexes respectively and one general fitness function is generated.A novel approach based on genetic algorithms is proposed.Numerical simulations show that,compared with geometrical routing rules,the proposed algorithm improve all three indexes,especially on cost and network layer load distribution indexes.

  15. Manipulator Neural Network Control Based on Fuzzy Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The three-layer forward neural networks are used to establish the inverse kinem a tics models of robot manipulators. The fuzzy genetic algorithm based on the line ar scaling of the fitness value is presented to update the weights of neural net works. To increase the search speed of the algorithm, the crossover probability and the mutation probability are adjusted through fuzzy control and the fitness is modified by the linear scaling method in FGA. Simulations show that the propo sed method improves considerably the precision of the inverse kinematics solutio ns for robot manipulators and guarantees a rapid global convergence and overcome s the drawbacks of SGA and the BP algorithm.

  16. Genetic-evolution-based optimization methods for engineering design

    Science.gov (United States)

    Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

    1990-01-01

    This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

  17. Improved Adaptive LSB Steganography Based on Chaos and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yu Lifang

    2010-01-01

    Full Text Available We propose a novel steganographic method in JPEG images with high performance. Firstly, we propose improved adaptive LSB steganography, which can achieve high capacity while preserving the first-order statistics. Secondly, in order to minimize visual degradation of the stego image, we shuffle bits-order of the message based on chaos whose parameters are selected by the genetic algorithm. Shuffling message's bits-order provides us with a new way to improve the performance of steganography. Experimental results show that our method outperforms classical steganographic methods in image quality, while preserving characteristics of histogram and providing high capacity.

  18. Genetic programming-based chaotic time series modeling

    Institute of Scientific and Technical Information of China (English)

    张伟; 吴智铭; 杨根科

    2004-01-01

    This paper proposes a Genetic Programming-Based Modeling(GPM)algorithm on chaotic time series. GP is used here to search for appropriate model structures in function space,and the Particle Swarm Optimization(PSO)algorithm is used for Nonlinear Parameter Estimation(NPE)of dynamic model structures. In addition,GPM integrates the results of Nonlinear Time Series Analysis(NTSA)to adjust the parameters and takes them as the criteria of established models.Experiments showed the effectiveness of such improvements on chaotic time series modeling.

  19. Genetic-evolution-based optimization methods for engineering design

    Science.gov (United States)

    Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

    1990-01-01

    This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

  20. Feature Selection for Image Retrieval based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Preeti Kushwaha

    2016-12-01

    Full Text Available This paper describes the development and implementation of feature selection for content based image retrieval. We are working on CBIR system with new efficient technique. In this system, we use multi feature extraction such as colour, texture and shape. The three techniques are used for feature extraction such as colour moment, gray level co- occurrence matrix and edge histogram descriptor. To reduce curse of dimensionality and find best optimal features from feature set using feature selection based on genetic algorithm. These features are divided into similar image classes using clustering for fast retrieval and improve the execution time. Clustering technique is done by k-means algorithm. The experimental result shows feature selection using GA reduces the time for retrieval and also increases the retrieval precision, thus it gives better and faster results as compared to normal image retrieval system. The result also shows precision and recall of proposed approach compared to previous approach for each image class. The CBIR system is more efficient and better performs using feature selection based on Genetic Algorithm.

  1. Genetic based optimization for multicast routing algorithm for MANET

    Indian Academy of Sciences (India)

    C Rajan; N Shanthi

    2015-12-01

    Mobile Ad hoc Network (MANET) is established for a limited period, for special extemporaneous services related to mobile applications. This ad hoc network is set up for a limited period, in environments that change with the application. While in Internet the TCP/IP protocol suite supports a wide range of application, in MANETs protocols are tuned to specific customer/application. Multicasting is emerging as a popular communication format where the same packet is sent to multiple nodes in a network. Routing in multicasting involves maintaining routes and finding new node locations in a group and is NP-complete due to the dynamic nature of the network. In this paper, a Hybrid Genetic Based Optimization for Multicast Routing algorithm is proposed. The proposed algorithm uses the best features of Genetic Algorithm (GA) and particle swarm optimization (PSO) to improve the solution. Simulations were conducted by varying number of mobile nodes and results compared with Multicast AODV (MAODV) protocol, PSO based and GA based solution. The proposed optimization improves jitter, end to end delay and Packet Delivery Ratio (PDR) with faster convergence.

  2. Estimating genetic correlations based on phenotypic data: a simulation-based method

    Indian Academy of Sciences (India)

    Elias Zintzaras

    2011-04-01

    Knowledge of genetic correlations is essential to understand the joint evolution of traits through correlated responses to selection, a difficult and seldom, very precise task even with easy-to-breed species. Here, a simulation-based method to estimate genetic correlations and genetic covariances that relies only on phenotypic measurements is proposed. The method does not require any degree of relatedness in the sampled individuals. Extensive numerical results suggest that the propose method may provide relatively efficient estimates regardless of sample sizes and contributions from common environmental effects.

  3. Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information

    Directory of Open Access Journals (Sweden)

    Wang S Alex

    2010-01-01

    Full Text Available Abstract Background The genetic contributions to human common disorders and mouse genetic models of disease are complex and often overlapping. In common human diseases, unlike classical Mendelian disorders, genetic factors generally have small effect sizes, are multifactorial, and are highly pleiotropic. Likewise, mouse genetic models of disease often have pleiotropic and overlapping phenotypes. Moreover, phenotypic descriptions in the literature in both human and mouse are often poorly characterized and difficult to compare directly. Methods In this report, human genetic association results from the literature are summarized with regard to replication, disease phenotype, and gene specific results; and organized in the context of a systematic disease ontology. Similarly summarized mouse genetic disease models are organized within the Mammalian Phenotype ontology. Human and mouse disease and phenotype based gene sets are identified. These disease gene sets are then compared individually and in large groups through dendrogram analysis and hierarchical clustering analysis. Results Human disease and mouse phenotype gene sets are shown to group into disease and phenotypically relevant groups at both a coarse and fine level based on gene sharing. Conclusion This analysis provides a systematic and global perspective on the genetics of common human disease as compared to itself and in the context of mouse genetic models of disease.

  4. Multi-objective Modeling and Assessment of Partition Properties: A GA-Based Quantitative Structure-Property Relationship Approach

    Institute of Scientific and Technical Information of China (English)

    印春生; 刘新会; 郭卫民; 刘树深; 韩朔暌; 王连生

    2003-01-01

    In this work a multi-objective quantitative structure-property relationship (QSPR) analysis approach was reported based on the study on three partition properties of 50 aromatic sulfur-containing carboxylates. Here multi-objectives ( properties )were taken as a vector for QSPR modeling. The quantitative correlations for partition properties were developed using a ge-netic algorithm-based variable-selection approach with quantum descriptors, derived from AM1-based calculations.With the QSPR models, the aqueous solubmty, octanol/water partition coefficients and reversed-phase HPLC capacity factors of sulfur-contalning compounds were estimated and predicted.Using GA-based multivariate linear regression with cross-vali-dation procedure, a set of the most promising descriptors was selegted from a pool of 28 quantum chemical semi-empirical de-scriptors, incloding steric and electronic types, to integrally build QSPR models. The selected molecular descriptors includ-ed the net charges on carboxyl group (Qoc), the 2nd power of net ehnrges on nitrogen atoms (QN2), the net atomic charge on the sulfur atoms (Qs), the van der Waals volume of molecule (V), the most positive net atomic charge on hydrogen atoms(QH) and the measure of polarity and polarizability (π),which were main factors affecting the distribution processes of the compounds under study. The statistically best QSPR models of six descriptors were simultaneously obtained by GA-based linear regression analysis. With the selected descriptors and the QSPR equations, mechanisms of partition action of the Sulfur-containing carboxylates were able to be investigated and inter-preted.

  5. From beavis to beak color: a simulation study to examine how much qtl mapping can reveal about the genetic architecture of quantitative traits.

    Science.gov (United States)

    Slate, Jon

    2013-05-01

    Quantitative trait locus (QTL) mapping is frequently used in evolutionary studies to understand the genetic architecture of continuously varying traits. The majority of studies have been conducted in specially created crosses, in which genetic differences between parental lines are identified by linkage analysis. Detecting QTL segregating within populations is more problematic, especially in wild populations, because these populations typically have complicated and unbalanced multigenerational pedigrees. However, QTL mapping can still be conducted in such populations using a variance components mixed model approach, and the advent of appropriate statistical frameworks and better genotyping methods mean that the approach is gaining popularity. In this study it is shown that all studies described to date report evidence of QTL of major effect on trait variation, but that these findings are probably caused by inflated estimates of QTL effect sizes due to the Beavis effect. Using simulations I show that even the most powerful studies conducted to date are likely to give misleading descriptions of the genetic architecture of a trait. I show that an interpretation of a mapping study of beak color in the zebra finch (Taeniopygia guttata), that suggested genetic variation was determined by a small number of loci of large effect, which are possibly maintained by antagonistic pleiotropy, is likely to be incorrect. More generally, recommendations are made to how QTL mapping can be combined with other approaches to provide more accurate descriptions of a trait's genetic architecture.

  6. Quantitative Assessment of a Field-Based Course on Integrative Geology, Ecology and Cultural History

    Science.gov (United States)

    Sheppard, Paul R.; Donaldson, Brad A.; Huckleberry, Gary

    2010-01-01

    A field-based course at the University of Arizona called Sense of Place (SOP) covers the geology, ecology and cultural history of the Tucson area. SOP was quantitatively assessed for pedagogical effectiveness. Students of the Spring 2008 course were given pre- and post-course word association surveys in order to assess awareness and comprehension…

  7. Experiencing Teaching and Learning Quantitative Reasoning in a Project-Based Context

    Science.gov (United States)

    Muir, Tracey; Beswick, Kim; Callingham, Rosemary; Jade, Katara

    2016-01-01

    This paper presents the findings of a small-scale study that investigated the issues and challenges of teaching and learning about quantitative reasoning (QR) within a project-based learning (PjBL) context. Students and teachers were surveyed and interviewed about their experiences of learning and teaching QR in that context in contrast to…

  8. A Quantitative Comparative Study Measuring Consumer Satisfaction Based on Health Record Format

    Science.gov (United States)

    Moore, Vivianne E.

    2013-01-01

    This research study used a quantitative comparative method to investigate the relationship between consumer satisfaction and communication based on the format of health record. The central problem investigated in this research study related to the format of health record used and consumer satisfaction with care provided and effect on communication…

  9. Poem Generator: A Comparative Quantitative Evaluation of a Microworlds-Based Learning Approach for Teaching English

    Science.gov (United States)

    Jenkins, Craig

    2015-01-01

    This paper is a comparative quantitative evaluation of an approach to teaching poetry in the subject domain of English that employs a "guided discovery" pedagogy using computer-based microworlds. It uses a quasi-experimental design in order to measure performance gains in computational thinking and poetic thinking following a…

  10. Quantitative Assessment of a Field-Based Course on Integrative Geology, Ecology and Cultural History

    Science.gov (United States)

    Sheppard, Paul R.; Donaldson, Brad A.; Huckleberry, Gary

    2010-01-01

    A field-based course at the University of Arizona called Sense of Place (SOP) covers the geology, ecology and cultural history of the Tucson area. SOP was quantitatively assessed for pedagogical effectiveness. Students of the Spring 2008 course were given pre- and post-course word association surveys in order to assess awareness and comprehension…

  11. Application of genetic algorithm to hexagon-based motion estimation.

    Science.gov (United States)

    Kung, Chih-Ming; Cheng, Wan-Shu; Jeng, Jyh-Horng

    2014-01-01

    With the improvement of science and technology, the development of the network, and the exploitation of the HDTV, the demands of audio and video become more and more important. Depending on the video coding technology would be the solution for achieving these requirements. Motion estimation, which removes the redundancy in video frames, plays an important role in the video coding. Therefore, many experts devote themselves to the issues. The existing fast algorithms rely on the assumption that the matching error decreases monotonically as the searched point moves closer to the global optimum. However, genetic algorithm is not fundamentally limited to this restriction. The character would help the proposed scheme to search the mean square error closer to the algorithm of full search than those fast algorithms. The aim of this paper is to propose a new technique which focuses on combing the hexagon-based search algorithm, which is faster than diamond search, and genetic algorithm. Experiments are performed to demonstrate the encoding speed and accuracy of hexagon-based search pattern method and proposed method.

  12. Cognitive heterogeneity in genetically based prosopagnosia: a family study.

    Science.gov (United States)

    Schmalzl, Laura; Palermo, Romina; Coltheart, Max

    2008-03-01

    Congenital prosopagnosia (CP) is a selective difficulty in recognizing familiar faces that is present from birth. There is mounting evidence for a familial factor in CP, possibly due to a simple autosomal inheritance pattern. However, potential candidate genes remain to be established, and the question whether genetically based CP is a single trait, or a cluster of related subtypes differing in the pattern of impairments to specific components of the face-processing system, remains unanswered. In addition, since the great majority of so far described cases with CP were adult at the time of investigation, it remains unknown which specific aspects of face processing are impaired in small children with CP. Here we present the first study that specifically addresses these questions by elucidating the specific mechanisms underlying face-recognition impairments in seven individuals with CP (aged 4-87 years) belonging to four generations of the same family. Our results indicate that genetically based CP is not a single trait but a cluster of related subtypes, since the pattern of impairments to specific components of the face-processing system varies in individuals belonging to the same family. In addition, we show that the heterogeneity of the cognitive profile in CP with respect to specific aspects of face processing is apparent from early childhood.

  13. Family genetic algorithms based on gene exchange and its application

    Institute of Scientific and Technical Information of China (English)

    Li Jianhua; Ding Xiangqian; Wang Sunan; Yu Qing

    2006-01-01

    Genetic Algorithms (GA) are a search techniques based on mechanics of nature selection and have already been successfully applied in many diverse areas. However, increasing samples show that GA's performance is not as good as it was expected to be. Criticism of this algorithm includes the slow speed and premature result during convergence procedure. In order to improve the performance, the population size and individuals' space is emphatically described. The influence of individuals' space and population size on the operators is analyzed. And a novel family genetic algorithm (FGA) is put forward based on this analysis. In this novel algorithm, the optimum solution families closed to quality individuals is constructed, which is exchanged found by a search in the world space. Search will be done in this microspace. The family that can search better genes in a limited period of time would win a new life. At the same time, the best gene of this micro space with the basic population in the world space is exchanged. Finally, the FGA is applied to the function optimization and image matching through several experiments. The results show that the FGA possessed high performance.

  14. Quantitative evaluation on the characteristics of activated sludge granules and flocs using a fuzzy entropy-based approach

    Science.gov (United States)

    Fang, Fang; Qiao, Li-Li; Ni, Bing-Jie; Cao, Jia-Shun; Yu, Han-Qing

    2017-02-01

    Activated sludge granules and flocs have their inherent advantages and disadvantages for wastewater treatment due to their different characteristics. So far quantitative information on their evaluation is still lacking. This work provides a quantitative and comparative evaluation on the characteristics and pollutant removal capacity of granules and flocs by using a new methodology through integrating fuzzy analytic hierarchy process, accelerating genetic algorithm and entropy weight method. Evaluation results show a higher overall score of granules, indicating that granules had more favorable characteristics than flocs. Although large sized granules might suffer from more mass transfer limitation and is prone to operating instability, they also enable a higher level of biomass retention, greater settling velocity and lower sludge volume index compared to flocs. Thus, optimized control of granule size is essential for achieving good pollutant removal performance and simultaneously sustaining long-term stable operation of granule-based reactors. This new integrated approach is effective to quantify and differentiate the characteristics of activated sludge granules and flocs. The evaluation results also provide useful information for the application of activated sludge granules in full-scale wastewater treatment plants.

  15. Quantitative evaluation on the characteristics of activated sludge granules and flocs using a fuzzy entropy-based approach

    Science.gov (United States)

    Fang, Fang; Qiao, Li-Li; Ni, Bing-Jie; Cao, Jia-Shun; Yu, Han-Qing

    2017-01-01

    Activated sludge granules and flocs have their inherent advantages and disadvantages for wastewater treatment due to their different characteristics. So far quantitative information on their evaluation is still lacking. This work provides a quantitative and comparative evaluation on the characteristics and pollutant removal capacity of granules and flocs by using a new methodology through integrating fuzzy analytic hierarchy process, accelerating genetic algorithm and entropy weight method. Evaluation results show a higher overall score of granules, indicating that granules had more favorable characteristics than flocs. Although large sized granules might suffer from more mass transfer limitation and is prone to operating instability, they also enable a higher level of biomass retention, greater settling velocity and lower sludge volume index compared to flocs. Thus, optimized control of granule size is essential for achieving good pollutant removal performance and simultaneously sustaining long-term stable operation of granule-based reactors. This new integrated approach is effective to quantify and differentiate the characteristics of activated sludge granules and flocs. The evaluation results also provide useful information for the application of activated sludge granules in full-scale wastewater treatment plants. PMID:28211540

  16. Global wild annual Lens collection: a potential resource for lentil genetic base broadening and yield enhancement.

    Directory of Open Access Journals (Sweden)

    Mohar Singh

    Full Text Available Crop wild relatives (CWRs are invaluable gene sources for various traits of interest, yet these potential resources are themselves increasingly threatened by the impact of climate change as well as other anthropogenic and socio-economic factors. The prime goal of our research was to cover all aspects of wild Lens genetic resource management like species characterization, agro-morphological evaluation, diversity assessment, and development of representative sets for its enhanced utilization in lentil base broadening and yield improvement initiatives. We characterized and evaluated extensively, the global wild annual Lens taxa, originating from twenty seven counties under two agro-climatic conditions of India consecutively for three cropping seasons. Results on various qualitative and quantitative characters including two foliar diseases showed wide variations for almost all yield attributing traits including multiple disease resistance in the wild species, L. nigricans and L. ervoides accessions. The core set developed from the entire Lens taxa had maximum representation from Turkey and Syria, indicating rich diversity in accessions originating from these regions. Diversity analysis also indicated wide geographical variations across genepool as was reflected in the core set. Potential use of core set, as an initial starting material, for genetic base broadening of cultivated lentil was also suggested.

  17. A new automatic alignment technology for single mode fiber-waveguide based on improved genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHENG Yu; CHEN Zhuang-zhuang; LI Ya-juan; DUAN Jian

    2009-01-01

    A novel automatic alignment algorithm of single mode fiber-waveguide based on improved genetic algorithm is proposed. The genetic searching is based on the dynamic crossover operator and the adaptive mutation operator to solve the premature convergence of simple genetic algorithm The improved genetic algorithm combines with hill-climbing method and pattern searching algorithm, to solve low precision of simple genetic algorithm in later searching. The simulation results indicate that the improved genetic algorithm can rise the alignment precision and reach the coupling loss of 0.01 dB when platform moves near 207 space points averagely.

  18. QUANTITATIVE EVALUATION METHOD OF ELEMENTS PRIORITY OF CARTOGRAPHIC GENERALIZATION BASED ON TAXI TRAJECTORY DATA

    Directory of Open Access Journals (Sweden)

    Z. Long

    2017-09-01

    Full Text Available Considering the lack of quantitative criteria for the selection of elements in cartographic generalization, this study divided the hotspot areas of passengers into parts at three levels, gave them different weights, and then classified the elements from the different hotspots. On this basis, a method was proposed to quantify the priority of elements selection. Subsequently, the quantitative priority of different cartographic elements was summarized based on this method. In cartographic generalization, the method can be preferred to select the significant elements and discard those that are relatively non-significant.

  19. Genetic Dissection and Molecular Dissection of Quantitative Traits%数量性状的遗传剖析和分子剖析

    Institute of Scientific and Technical Information of China (English)

    吴为人; 唐定中; 李维明

    2000-01-01

    生物的大多数重要性状都是数量性状,遗传基础复杂,遗传研究非常困难。近20年来,由于分子生物技术飞速发展,特别是分子标记技术和大片段DNA克隆和分析技术的出现,使遗传学开始向阐明人类和一些模式动植物整个基因组的宏伟目标进军,也使得数量性状的遗传剖析(即系统地对各个数量性状基因或QTL的遗传定位和效应分析)和分子剖析(即对QTL的克隆分离)成为可能,并在短短的10余年内取得了重大的进展。该领域的研究将使我们能精确地分析QTL的效应,可靠地对QTL进行标记辅助选择以及实现对数量性状的基因工程,从而使现代分子生物技术在动植物遗传改良和人类遗传病治疗方面发挥更大的作用。本文综述了近年来在数量性状遗传剖析和分子剖析的方法方面的研究进展。%Most of the important characters in living beings are quantitative traits,which have complicated genetic basis and are very difficult for genetic research.Due to the rapid progress of molecular biological technology in the last two decades,especially dne to the advent of molecularmarker techniques and the techniques for the analysis and clonning of large DNA fragments,genetics has begun to march towards the great goal of elncidating the whole genomes of human and some model animals and plants,and the genetic and molecular dissection of quantitative traits(mapping and cloning of individual quantitative trait loci orQTL)has therefore becomepossible,and great progress has been achieved since late 1980's.Studies in this will enable us to perfirm precise analysis of QTL's effects and reliable marker-assisted selection of QTL and to realize genetic engineering of quantitative traits so as to make modern molecular biotechnologyplay even greater role in the genetic improvement of animals and plants d in the terapy of human's genetic diseases.In this paper

  20. The Effective Clustering Partition Algorithm Based on the Genetic Evolution

    Institute of Scientific and Technical Information of China (English)

    LIAO Qin; LI Xi-wen

    2006-01-01

    To the problem that it is hard to determine the clustering number and the abnormal points by using the clustering validity function, an effective clustering partition model based on the genetic algorithm is built in this paper. The solution to the problem is formed by the combination of the clustering partition and the encoding samples, and the fitness function is defined by the distances among and within clusters. The clustering number and the samples in each cluster are determined and the abnormal points are distinguished by implementing the triple random crossover operator and the mutation. Based on the known sample data, the results of the novel method and the clustering validity function are compared. Numerical experiments are given and the results show that the novel method is more effective.

  1. Using quantitative mass spectrometry to better understand the influence of genetics and nutritional perturbations on the virulence potential of Staphylococcus aureus.

    Science.gov (United States)

    Chapman, Jessica R; Balasubramanian, Divya; Tam, Kayan; Askenazi, Manor; Copin, Richard; Shopsin, Bo; Torres, Victor J; Ueberheide, Beatrix

    2017-02-14

    Staphylococcus aureus (Sa) is the leading cause of a variety of bacterial infections ranging from superficial skin infections to invasive and life threatening diseases such as septic bacteremia, necrotizing pneumonia, and endocarditis. The success of Sa as a human pathogen is due to its ability to adapt to the environment by changing expression, production, or secretion of virulence factors. Although Sa immune evasion is well-studied, the regulation of virulence factors under different nutrient and growth conditions is still not well understood. Here, we used label-free quantitative mass spectrometry to quantify and compare the secreted Sa proteins (i.e. exoproteomes) of master regulator mutants or established reference strains. Different environmental conditions were addressed by growing the bacteria in rich or minimal media at different phases of growth. We observed clear differences in the composition of the exoproteomes depending on the genetic background or growth conditions. The relative abundance of cytotoxins determined in our study correlated well with differences in cytotoxicity measured by lysis of human neutrophils. Our findings demonstrate that label-free quantitative mass spectrometry is a versatile tool for predicting the virulence of bacterial strains and highlights the importance of the experimental design for in vitro studies. Furthermore, the results indicate that label-free proteomics can be used to cluster isolates into groups with similar virulence properties and genetic lineages, highlighting the power of label-free quantitative mass spectrometry to distinguish Sa strains.

  2. Quantitative genetic analysis of brain size variation in sticklebacks: support for the mosaic model of brain evolution.

    Science.gov (United States)

    Noreikiene, Kristina; Herczeg, Gábor; Gonda, Abigél; Balázs, Gergely; Husby, Arild; Merilä, Juha

    2015-07-07

    The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback (Gasterosteus aculeatus). We found that heritabilities were low (average h(2) = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average rG = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high (rG = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks.

  3. A gold nanoparticle-based semi-quantitative and quantitative ultrasensitive paper sensor for the detection of twenty mycotoxins

    Science.gov (United States)

    Kong, Dezhao; Liu, Liqiang; Song, Shanshan; Suryoprabowo, Steven; Li, Aike; Kuang, Hua; Wang, Libing; Xu, Chuanlai

    2016-02-01

    A semi-quantitative and quantitative multi-immunochromatographic (ICA) strip detection assay was developed for the simultaneous detection of twenty types of mycotoxins from five classes, including zearalenones (ZEAs), deoxynivalenols (DONs), T-2 toxins (T-2s), aflatoxins (AFs), and fumonisins (FBs), in cereal food samples. Sensitive and specific monoclonal antibodies were selected for this assay. The semi-quantitative results were obtained within 20 min by the naked eye, with visual limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.1-0.5, 2.5-250, 0.5-1, 0.25-1 and 2.5-10 μg kg-1, and cut-off values of 0.25-1, 5-500, 1-10, 0.5-2.5 and 5-25 μg kg-1, respectively. The quantitative results were obtained using a hand-held strip scan reader, with the calculated limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.04-0.17, 0.06-49, 0.15-0.22, 0.056-0.49 and 0.53-1.05 μg kg-1, respectively. The analytical results of spiked samples were in accordance with the accurate content in the simultaneous detection analysis. This newly developed ICA strip assay is suitable for the on-site detection and rapid initial screening of mycotoxins in cereal samples, facilitating both semi-quantitative and quantitative determination.A semi-quantitative and quantitative multi-immunochromatographic (ICA) strip detection assay was developed for the simultaneous detection of twenty types of mycotoxins from five classes, including zearalenones (ZEAs), deoxynivalenols (DONs), T-2 toxins (T-2s), aflatoxins (AFs), and fumonisins (FBs), in cereal food samples. Sensitive and specific monoclonal antibodies were selected for this assay. The semi-quantitative results were obtained within 20 min by the naked eye, with visual limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.1-0.5, 2.5-250, 0.5-1, 0.25-1 and 2.5-10 μg kg-1, and cut-off values of 0.25-1, 5-500, 1-10, 0.5-2.5 and 5-25 μg kg-1, respectively. The quantitative results were obtained using a hand-held strip scan

  4. Quantitative study on crack of meso-damage and fracture concrete based on CT technique

    Indian Academy of Sciences (India)

    Wei Tian; Faning Dang; Yongli Xie

    2015-02-01

    The meso-mechanics experiment of concrete specimen is carried out by means of CT technology, the whole degradation deformation process of meso-cracks generation, propagation, coalescence and failure is obtained under uniaxial compression condition. Based on CT image of concrete meso-damage evolution, the recognition and extraction of meso-cracks are realized by means of the digital imageprocessing (DIP) technique, and the basic geometrical characteristics of meso-crack patterns are statistically analysed from length, width and area. The quantitative analysis of the meso-fracture process of concrete materials is performed. The results demonstrate that the quantitative analysis of the internal meso-crack of concrete can be taken as a quantitative index to reflect the damage and fracture process thereby the meso-fracture mechanism of concrete material is thoroughly investigated. So it has brought forth some new ideas to the study of damage evolution law of concrete under uniaxial compression condition.

  5. Modelling and genetic algorithm based optimisation of inverse supply chain

    Science.gov (United States)

    Bányai, T.

    2009-04-01

    (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a

  6. [MapDraw: a microsoft excel macro for drawing genetic linkage maps based on given genetic linkage data].

    Science.gov (United States)

    Liu, Ren-Hu; Meng, Jin-Ling

    2003-05-01

    MAPMAKER is one of the most widely used computer software package for constructing genetic linkage maps.However, the PC version, MAPMAKER 3.0 for PC, could not draw the genetic linkage maps that its Macintosh version, MAPMAKER 3.0 for Macintosh,was able to do. Especially in recent years, Macintosh computer is much less popular than PC. Most of the geneticists use PC to analyze their genetic linkage data. So a new computer software to draw the same genetic linkage maps on PC as the MAPMAKER for Macintosh to do on Macintosh has been crying for. Microsoft Excel,one component of Microsoft Office package, is one of the most popular software in laboratory data processing. Microsoft Visual Basic for Applications (VBA) is one of the most powerful functions of Microsoft Excel. Using this program language, we can take creative control of Excel, including genetic linkage map construction, automatic data processing and more. In this paper, a Microsoft Excel macro called MapDraw is constructed to draw genetic linkage maps on PC computer based on given genetic linkage data. Use this software,you can freely construct beautiful genetic linkage map in Excel and freely edit and copy it to Word or other application. This software is just an Excel format file. You can freely copy it from ftp://211.69.140.177 or ftp://brassica.hzau.edu.cn and the source code can be found in Excel's Visual Basic Editor.

  7. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats

    Science.gov (United States)

    Baud, Amelie; Hermsen, Roel; Guryev, Victor; Stridh, Pernilla; Graham, Delyth; McBride, Martin W.; Foroud, Tatiana; Calderari, Sophie; Diez, Margarita; Ockinger, Johan; Beyeen, Amennai D.; Gillett, Alan; Abdelmagid, Nada; Guerreiro-Cacais, Andre Ortlieb; Jagodic, Maja; Tuncel, Jonatan; Norin, Ulrika; Beattie, Elisabeth; Huynh, Ngan; Miller, William H.; Koller, Daniel L.; Alam, Imranul; Falak, Samreen; Osborne-Pellegrin, Mary; Martinez-Membrives, Esther; Canete, Toni; Blazquez, Gloria; Vicens-Costa, Elia; Mont-Cardona, Carme; Diaz-Moran, Sira; Tobena, Adolf; Hummel, Oliver; Zelenika, Diana; Saar, Kathrin; Patone, Giannino; Bauerfeind, Anja; Bihoreau, Marie-Therese; Heinig, Matthias; Lee, Young-Ae; Rintisch, Carola; Schulz, Herbert; Wheeler, David A.; Worley, Kim C.; Muzny, Donna M.; Gibbs, Richard A.; Lathrop, Mark; Lansu, Nico; Toonen, Pim; Ruzius, Frans Paul; de Bruijn, Ewart; Hauser, Heidi; Adams, David J.; Keane, Thomas; Atanur, Santosh S.; Aitman, Tim J.; Flicek, Paul; Malinauskas, Tomas; Jones, E. Yvonne; Ekman, Diana; Lopez-Aumatell, Regina; Dominiczak, Anna F; Johannesson, Martina; Holmdahl, Rikard; Olsson, Tomas; Gauguier, Dominique; Hubner, Norbert; Fernandez-Teruel, Alberto; Cuppen, Edwin; Mott, Richard; Flint, Jonathan

    2013-01-01

    Genetic mapping on fully sequenced individuals is transforming our understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating novel genes in models of anxiety, heart disease and multiple sclerosis. The relation between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show the extent and spatial pattern of variation in inbred rats differ significantly from those of inbred mice, and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species. PMID:23708188

  8. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats.

    Science.gov (United States)

    Baud, Amelie; Hermsen, Roel; Guryev, Victor; Stridh, Pernilla; Graham, Delyth; McBride, Martin W; Foroud, Tatiana; Calderari, Sophie; Diez, Margarita; Ockinger, Johan; Beyeen, Amennai D; Gillett, Alan; Abdelmagid, Nada; Guerreiro-Cacais, Andre Ortlieb; Jagodic, Maja; Tuncel, Jonatan; Norin, Ulrika; Beattie, Elisabeth; Huynh, Ngan; Miller, William H; Koller, Daniel L; Alam, Imranul; Falak, Samreen; Osborne-Pellegrin, Mary; Martinez-Membrives, Esther; Canete, Toni; Blazquez, Gloria; Vicens-Costa, Elia; Mont-Cardona, Carme; Diaz-Moran, Sira; Tobena, Adolf; Hummel, Oliver; Zelenika, Diana; Saar, Kathrin; Patone, Giannino; Bauerfeind, Anja; Bihoreau, Marie-Therese; Heinig, Matthias; Lee, Young-Ae; Rintisch, Carola; Schulz, Herbert; Wheeler, David A; Worley, Kim C; Muzny, Donna M; Gibbs, Richard A; Lathrop, Mark; Lansu, Nico; Toonen, Pim; Ruzius, Frans Paul; de Bruijn, Ewart; Hauser, Heidi; Adams, David J; Keane, Thomas; Atanur, Santosh S; Aitman, Tim J; Flicek, Paul; Malinauskas, Tomas; Jones, E Yvonne; Ekman, Diana; Lopez-Aumatell, Regina; Dominiczak, Anna F; Johannesson, Martina; Holmdahl, Rikard; Olsson, Tomas; Gauguier, Dominique; Hubner, Norbert; Fernandez-Teruel, Alberto; Cuppen, Edwin; Mott, Richard; Flint, Jonathan

    2013-07-01

    Genetic mapping on fully sequenced individuals is transforming understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating new genes in models of anxiety, heart disease and multiple sclerosis. The relationship between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci, a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show that the extent and spatial pattern of variation in inbred rats differ substantially from those of inbred mice and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species.

  9. Probe-based Real-time PCR Approaches for Quantitative Measurement of microRNAs

    Science.gov (United States)

    Wong, Wilson; Farr, Ryan; Joglekar, Mugdha; Januszewski, Andrzej; Hardikar, Anandwardhan

    2015-01-01

    Probe-based quantitative PCR (qPCR) is a favoured method for measuring transcript abundance, since it is one of the most sensitive detection methods that provides an accurate and reproducible analysis. Probe-based chemistry offers the least background fluorescence as compared to other (dye-based) chemistries. Presently, there are several platforms available that use probe-based chemistry to quantitate transcript abundance. qPCR in a 96 well plate is the most routinely used method, however only a maximum of 96 samples or miRNAs can be tested in a single run. This is time-consuming and tedious if a large number of samples/miRNAs are to be analyzed. High-throughput probe-based platforms such as microfluidics (e.g. TaqMan Array Card) and nanofluidics arrays (e.g. OpenArray) offer ease to reproducibly and efficiently detect the abundance of multiple microRNAs in a large number of samples in a short time. Here, we demonstrate the experimental setup and protocol for miRNA quantitation from serum or plasma-EDTA samples, using probe-based chemistry and three different platforms (96 well plate, microfluidics and nanofluidics arrays) offering increasing levels of throughput. PMID:25938938

  10. The quantitative Morse theorem

    OpenAIRE

    Loi, Ta Le; Phien, Phan

    2013-01-01

    In this paper, we give a proof of the quantitative Morse theorem stated by {Y. Yomdin} in \\cite{Y1}. The proof is based on the quantitative Sard theorem, the quantitative inverse function theorem and the quantitative Morse lemma.

  11. Genetic and physiological bases for phenological responses to current and predicted climates

    OpenAIRE

    Wilczek, A. M.; Burghardt, L. T.; Cobb, A. R.; Cooper, M D; Welch, S. M.; Schmitt, J

    2010-01-01

    We are now reaching the stage at which specific genetic factors with known physiological effects can be tied directly and quantitatively to variation in phenology. With such a mechanistic understanding, scientists can better predict phenological responses to novel seasonal climates. Using the widespread model species Arabidopsis thaliana, we explore how variation in different genetic pathways can be linked to phenology and life-history variation across geographical regions and seasons. We sho...

  12. Identification of Hammerstein Model Based on Quantum Genetic Algorithm

    OpenAIRE

    Zhang Hai Li

    2013-01-01

    Nonlinear system identification is a main topic of modern identification. A new method for nonlinear system identification is presented by using Quantum Genetic Algorithm(QGA).The problems of nonlinear system identification are cast as function optimization overprameter space,and the Quantum Genetic Algorithm is adopted to solve the optimization problem. Simulation experiments show that: compared with the genetic algorithm, quantum genetic algorithm is an effective swarm intelligence algorith...

  13. A New Genetic Algorithm Methodology for Design Optimization of Truss Structures: Bipopulation-Based Genetic Algorithm with Enhanced Interval Search

    Directory of Open Access Journals (Sweden)

    Tugrul Talaslioglu

    2009-01-01

    Full Text Available A new genetic algorithm (GA methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS, is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA utilizing a single population, a multipopulation-based genetic algorithm (MPGA proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature.

  14. Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-lin; MA Jie; GUI Wei-hua; YANG Chun-hua; ZHANG Chuan-fu

    2006-01-01

    A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0 %, which effectively stabilizes the agglomerate compositions and the permeability.

  15. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  16. Optimization of unit commitment based on genetic algorithms

    Institute of Scientific and Technical Information of China (English)

    蔡兴国; 初壮

    2002-01-01

    How to solve unit commitment and load dispatch of power system by genetic algorithms is discussed in this paper. A combination encoding scheme of binary encoding and floating number encoding and corresponding genetic operators are developed. Meanwhile a contract mapping genetic algorithm is used to enhance traditional GA' s convergence. The result of a practical example shows that this algorithm is effective.

  17. A Novel Quantitative Analysis Model for Information System Survivability Based on Conflict Analysis

    Institute of Scientific and Technical Information of China (English)

    WANG Jian; WANG Huiqiang; ZHAO Guosheng

    2007-01-01

    This paper describes a novel quantitative analysis model for system survivability based on conflict analysis, which provides a direct-viewing survivable situation. Based on the three-dimensional state space of conflict, each player's efficiency matrix on its credible motion set can be obtained. The player whose desire is the strongest in all initiates the moving and the overall state transition matrix of information system may be achieved. In addition, the process of modeling and stability analysis of conflict can be converted into a Markov analysis process, thus the obtained results with occurring probability of each feasible situation will help the players to quantitatively judge the probability of their pursuing situations in conflict. Compared with the existing methods which are limited to post-explanation of system's survivable situation, the proposed model is relatively suitable for quantitatively analyzing and forecasting the future development situation of system survivability. The experimental results show that the model may be effectively applied to quantitative analysis for survivability. Moreover, there will be a good application prospect in practice.

  18. Personality endophenotypes for bipolar affective disorder: a family-based genetic association analysis.

    Science.gov (United States)

    Savitz, J; van der Merwe, L; Ramesar, R

    2008-11-01

    Genetic analyses of complex conditions such as bipolar disorder (BD) may be facilitated by the use of intermediate phenotypes. Various personality traits are overrepresented in people with BD and their unaffected relatives, and may constitute genetically transmitted risk factors or endophenotypes of the illness. In this study, we administered a battery of seven different personality questionnaires comprising 19 subscales to 31 Caucasian BD families (n = 241). Ten of these personality traits showed significant evidence of heritability and were therefore selected as candidate endophenotypes. In addition, a principal components analysis produced two heritable components (negative affect and appetitive drive), which accounted for a considerable proportion of the variance (29% + 12%) and were also used in the analysis. A family-based quantitative association study was carried out using the orthogonal model from the quantitative transmission disequilibrium tests (QTDT) program. Monte Carlo permutations (M = 500), which allow for non-normal data and provide a global P value, corrected for multiple testing, were used to calculate empirical P values for the within-family component of association. The 3' untranslated region repeat polymorphism of the dopamine transporter gene (SLC6A3) was associated with self-directedness (P personality traits, 'Spirituality' (P = 0.040) and irritable temperament (P = 0.022). Furthermore, the met allele of the brain-derived neurotrophic factor val66met polymorphism was associated with higher hyperthymic temperament scores. We raise the possibility that the 10R allele of the SLC6A3 repeat polymorphism and the short allele of the SLC6A4 promoter variant constitute risk factors for irritable-aggressive and anxious-dysthymic subtypes of BD, respectively.

  19. Haplotyping a single triploid individual based on genetic algorithm.

    Science.gov (United States)

    Wu, Jingli; Chen, Xixi; Li, Xianchen

    2014-01-01

    The minimum error correction model is an important combinatorial model for haplotyping a single individual. In this article, triploid individual haplotype reconstruction problem is studied by using the model. A genetic algorithm based method GTIHR is presented for reconstructing the triploid individual haplotype. A novel coding method and an effectual hill-climbing operator are introduced for the GTIHR algorithm. This relatively short chromosome code can lead to a smaller solution space, which plays a positive role in speeding up the convergence process. The hill-climbing operator ensures algorithm GTIHR converge at a good solution quickly, and prevents premature convergence simultaneously. The experimental results prove that algorithm GTIHR can be implemented efficiently, and can get higher reconstruction rate than previous algorithms.

  20. Voidage measurement based on genetic algorithm and electrical capacitance tomography

    Institute of Scientific and Technical Information of China (English)

    WANG Wei-wei; WANG Bao-liang; HUANG Zhi-yao; LI Hai-qing

    2005-01-01

    A new voidage measurement method based on electrical capacitance tomography (ECT) technique, Genetic Algorithm (GA) and Partial Least Square (PLS) method was proposed. The voidage measurement model, linear capacitance combination, was developed to measure on-line voidage. GA and PLS method were used to determine the coefficients of the voidage measurement model. GA was used to explore the optimal capacitance combination which gave significant contribution to the voidage measurement. PLS method was applied to determine the weight coefficient of the contribution of each capacitance to the voidage measurement. Flow pattern identification result was introduced to improve the voidage measurement accuracy. Experimental results showed that the proposed voidage measurement method is effective and that the measurement accuracy is satisfactory.

  1. FRACTIONAL ORDER SYSTEM IDENTIFICATION BASED ON GENETIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    MAZIN Z. OTHMAN

    2013-12-01

    Full Text Available System identification deals with estimating the plant parameters under control using input-output measuring data. Most of practical plants have fractional order dynamic properties which are based on integration and differentiation of noninteger order. In this work the structure and the parameters of fractional order unknown transfer function are estimated using input-output data. Integer order Least Squares identification is used first to confirm the structure (order of the unknown transfer function. Then, Genetic Algorithms (GAs is followed to find the most accurate fractional order estimate that represents the system. Illustrative examples are presented in which fractional order transfer functions are identified in a way that faithfully estimates the dynamics of the unknown plants.

  2. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  3. GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

    Directory of Open Access Journals (Sweden)

    Ashish Jain

    2012-07-01

    Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

  4. Extended Range Guided Munition Parameter Optimization Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Many factors influencing range of extended range guided munition (ERGM) are analyzed. The definition domain of the most important three parameters are ascertained by preparatory mathematical simulation, the optimized mathematical model of ERGM maximum range with boundary conditions is created, and parameter optimization based on genetic algorithm (GA) is adopted. In the GA design, three-point crossover is used and the best chromosome is kept so that the convergence speed becomes rapid. Simulation result shows that GA is feasible, the result is good and it can be easy to attain global optimization solution, especially when the objective function is not the convex one for independent variables and it is a multi-parameter problem.

  5. Fuzzy Genetic Algorithm Based on Principal Operation and Inequity Degree

    Science.gov (United States)

    Li, Fachao; Jin, Chenxia

    In this paper, starting from the structure of fuzzy information, by distinguishing principal indexes and assistant indexes, give comparison of fuzzy information on synthesizing effect and operation of fuzzy optimization on principal indexes transformation, further, propose axiom system of fuzzy inequity degree from essence of constraint, and give an instructive metric method; Then, combining genetic algorithm, give fuzzy optimization methods based on principal operation and inequity degree (denoted by BPO&ID-FGA, for short); Finally, consider its convergence using Markov chain theory and analyze its performance through an example. All these indicate, BPO&ID-FGA can not only effectively merge decision consciousness into the optimization process, but possess better global convergence, so it can be applied to many fuzzy optimization problems.

  6. Optimization of transmission system design based on genetic algorithm

    Directory of Open Access Journals (Sweden)

    Xianbing Chen

    2016-05-01

    Full Text Available Transmission system is a crucial precision mechanism for twin-screw chemi-mechanical pulping equipment. The structure of the system designed by traditional method is not optimal because the structure designed by the traditional methods is easy to fall into the local optimum. To achieve the global optimum, this article applies the genetic algorithm which has grown in recent years in the field of structure optimization. The article uses the volume of transmission system as the objective function to optimize the structure designed by traditional method. Compared to the simulation results, the original structure is not optimal, and the optimized structure is tighter and more reasonable. Based on the optimized results, the transmission shafts in the transmission system are designed and checked, and the parameters of the twin screw are selected and calculated. The article provided an effective method to design the structure of transmission system.

  7. Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Mohammed Alkhawlani

    2008-01-01

    Full Text Available In the next generation of heterogeneous wireless networks (HWNs, a large number of different radio access technologies (RATs will be integrated into a common network. In this type of networks, selecting the most optimal and promising access network (AN is an important consideration for overall networks stability, resource utilization, user satisfaction, and quality of service (QoS provisioning. This paper proposes a general scheme to solve the access network selection (ANS problem in the HWN. The proposed scheme has been used to present and design a general multicriteria software assistant (SA that can consider the user, operator, and/or the QoS view points. Combined fuzzy logic (FL and genetic algorithms (GAs have been used to give the proposed scheme the required scalability, flexibility, and simplicity. The simulation results show that the proposed scheme and SA have better and more robust performance over the random-based selection.

  8. Family-Based Genetic Association for Molar-Incisor Hypomineralization.

    Science.gov (United States)

    Jeremias, Fabiano; Pierri, Ricardo A G; Souza, Juliana F; Fragelli, Camila Maria B; Restrepo, Manuel; Finoti, Livia S; Bussaneli, Diego G; Cordeiro, Rita C L; Secolin, Rodrigo; Maurer-Morelli, Claudia V; Scarel-Caminaga, Raquel M; Santos-Pinto, Lourdes

    2016-01-01

    Despite some evidence of genetic and environmental factors on molar-incisor hypomineralization (MIH), its aetiology remains unclear. This family-based genetic association study aimed more comprehensively to investigate the genetic carriage potentially involved in MIH development. DNA was obtained from buccal cells of 391 individuals who were birth family members of 101 Brazilian nuclear families. Sixty-three single nucleotide polymorphisms (SNPs) were investigated in 21 candidate genes related to amelogenesis using the TaqMan™ OpenArray™ Genotyping platform. All SNPs were genotyped in 165 birth family members unaffected by MIH, 96 with unknown MIH status and 130 affected individuals (50.7% with severe MIH). Association analysis was performed by the transmission/disequilibrium test (TDT), and statistical results were corrected using the false discovery rate. Significant results were obtained for SNPs rs7821494 (FAM83H gene, OR = 3.7; 95% CI = 1.75-7.78), rs34367704 (AMBN gene, OR = 2.7; 95% CI = 1.16-6.58), rs3789334 (BMP2 gene, OR = 2.9; 95% CI = 1.34-6.35), rs6099486 (BMP7 gene, OR = 2.2; 95% CI = 1.14-4.38), rs762642 (BMP4 gene, OR = 2.3; 95% CI = 1.38-3.65), rs7664896 (ENAM gene, OR = 2.1; 95% CI = 1.19-3.51), rs1711399 (MMP20 gene, OR = 0.4; 95% CI = 0.20-0.72), rs1711423 (MMP20 gene, OR = 2.1; 95% CI = 1.18-3.61), rs2278163 (DLX3 gene, OR = 2.8; 95% CI = 1.26-6.41), rs6996321 (FGFR1 gene, OR = 2.7; 95% CI = 1.20-5.88), and rs5979395 (AMELX gene, OR = 11.7; 95% CI = 1.63-84.74). Through this family-based association study, we concluded that variations in genes related to amelogenesis were associated with the susceptibility to develop MIH. This result is in agreement with the multifactorial idea of the MIH aetiology, but further studies are necessary to investigate more thoroughly the factors that could influence MIH.

  9. Practice-based competencies for accreditation of and training in graduate programs in genetic counseling.

    Science.gov (United States)

    Fine, B A; Baker, D L; Fiddler, M B

    1996-09-01

    In January 1996, the American Board of Genetic Counseling (ABGC) adopted 27 practice-based competencies as a standard for assessing the training of graduate students in genetic counseling. These competencies were identified and refined through a collective, narrative process that took place from January through November 1994, and included directors of graduate programs in genetic counseling, ABGC board members and expert consultants. These competencies now form the basis of the document "Requirements for Graduate Programs in Genetic Counseling Seeking Accreditation by the American Board of Genetic Counseling" (American Board of Genetic Counseling, 1996). The competencies are organized into four domains and are presented and discussed in this article.

  10. Multilocus association testing of quantitative traits based on partial least-squares analysis.

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    Full Text Available Because of combining the genetic information of multiple loci, multilocus association studies (MLAS are expected to be more powerful than single locus association studies (SLAS in disease genes mapping. However, some researchers found that MLAS had similar or reduced power relative to SLAS, which was partly attributed to the increased degrees of freedom (dfs in MLAS. Based on partial least-squares (PLS analysis, we develop a MLAS approach, while avoiding large dfs in MLAS. In this approach, genotypes are first decomposed into the PLS components that not only capture majority of the genetic information of multiple loci, but also are relevant for target traits. The extracted PLS components are then regressed on target traits to detect association under multilinear regression. Simulation study based on real data from the HapMap project were used to assess the performance of our PLS-based MLAS as well as other popular multilinear regression-based MLAS approaches under various scenarios, considering genetic effects and linkage disequilibrium structure of candidate genetic regions. Using PLS-based MLAS approach, we conducted a genome-wide MLAS of lean body mass, and compared it with our previous genome-wide SLAS of lean body mass. Simulations and real data analyses results support the improved power of our PLS-based MLAS in disease genes mapping relative to other three MLAS approaches investigated in this study. We aim to provide an effective and powerful MLAS approach, which may help to overcome the limitations of SLAS in disease genes mapping.

  11. Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

    Directory of Open Access Journals (Sweden)

    Hyo Seon Park

    2014-01-01

    Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

  12. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Directory of Open Access Journals (Sweden)

    Ulrike Ober

    Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  13. Impact of implementation choices on quantitative predictions of cell-based computational models

    Science.gov (United States)

    Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

    2017-09-01

    'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

  14. Naked-eye quantitative aptamer-based assay on paper device.

    Science.gov (United States)

    Zhang, Yun; Gao, Dong; Fan, Jinlong; Nie, Jinfang; Le, Shangwang; Zhu, Wenyuan; Yang, Jiani; Li, Jianping

    2016-04-15

    This work initially describes the design of low-cost, naked-eye quantitative aptamer-based assays by using microfluidic paper-based analytical device (μPAD). Two new detection motifs are proposed for quantitative μPAD measurement without using external electronic readers, which depend on the length of colored region in a strip-like μPAD and the number of colorless detection microzones in a multi-zone μPAD. The length measuring method is based on selective color change of paper from colorless to blue-black via formation of iodine-starch complex. The counting method is conducted on the basis of oxidation-reduction reaction between hydrogen peroxide and potassium permanganate. Their utility is well demonstrated with sensitive, specific detection of adenosine as a model analyte with the naked eye in buffer samples and undiluted human serum. These equipment-free quantitative methods proposed thus hold great potential for the development of more aptamer-based assays that are simple, cost-efficient, portable, and user-friendly for various point-of-care applications particularly in resource-constrained environments.

  15. Genetic Programming Based Ensemble System for Microarray Data Classification

    Directory of Open Access Journals (Sweden)

    Kun-Hong Liu

    2015-01-01

    Full Text Available Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP based new ensemble system (named GPES, which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

  16. Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition

    Directory of Open Access Journals (Sweden)

    Yuxing Mao

    2014-06-01

    Full Text Available Shape recognition is a classically difficult problem because of the affine transformation between two shapes. The current study proposes an affine parameter estimation method for shape recognition based on a genetic algorithm (GA. The contributions of this study are focused on the extraction of affine-invariant features, the individual encoding scheme, and the fitness function construction policy for a GA. First, the affine-invariant characteristics of the centroid distance ratios (CDRs of any two opposite contour points to the barycentre are analysed. Using different intervals along the azimuth angle, the different numbers of CDRs of two candidate shapes are computed as representations of the shapes, respectively. Then, the CDRs are selected based on predesigned affine parameters to construct the fitness function. After that, a GA is used to search for the affine parameters with optimal matching between candidate shapes, which serve as actual descriptions of the affine transformation between the shapes. Finally, the CDRs are resampled based on the estimated parameters to evaluate the similarity of the shapes for classification. The experimental results demonstrate the robust performance of the proposed method in shape recognition with translation, scaling, rotation and distortion.

  17. Quantitative interferometric microscopy with two dimensional Hilbert transform based phase retrieval method

    Science.gov (United States)

    Wang, Shouyu; Yan, Keding; Xue, Liang

    2017-01-01

    In order to obtain high contrast images and detailed descriptions of label free samples, quantitative interferometric microscopy combining with phase retrieval is designed to obtain sample phase distributions from fringes. As accuracy and efficiency of recovered phases are affected by phase retrieval methods, thus approaches owning higher precision and faster processing speed are still in demand. Here, two dimensional Hilbert transform based phase retrieval method is adopted in cellular phase imaging, it not only reserves more sample specifics compared to classical fast Fourier transform based method, but also overcomes disadvantages of traditional algorithm according to Hilbert transform which is a one dimensional processing causing phase ambiguities. Both simulations and experiments are provided, proving the proposed phase retrieval approach can acquire quantitative sample phases with high accuracy and fast speed.

  18. A statistical framework for protein quantitation in bottom-up MS-based proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas; Huang, Jianhua; Adkins, Joshua N.; Ansong, Charles; Heffron, Fred; Metz, Thomas O.; Qian, Weijun; Yoon, Hyunjin; Smith, Richard D.; Dabney, Alan R.

    2009-08-15

    ABSTRACT Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and confidence measures. Challenges include the presence of low-quality or incorrectly identified peptides and widespread, informative, missing data. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model for protein abundance in terms of peptide peak intensities, applicable to both label-based and label-free quantitation experiments. The model allows for both random and censoring missingness mechanisms and provides naturally for protein-level estimates and confidence measures. The model is also used to derive automated filtering and imputation routines. Three LC-MS datasets are used to illustrate the methods. Availability: The software has been made available in the open-source proteomics platform DAnTE (Polpitiya et al. (2008)) (http://omics.pnl.gov/software/). Contact: adabney@stat.tamu.edu

  19. Quantitative Verification of a Force-based Model for Pedestrian Dynamics

    CERN Document Server

    Chraibi, Mohcine; Schadschneider, Andreas; Mackens, Wolfgang

    2009-01-01

    This paper introduces a spatially continuous force-based model for simulating pedestrian dynamics. The main intention of this work is the quantitative description of pedestrian movement through bottlenecks and in corridors. Measurements of flow and density at bottlenecks will be presented and compared with empirical data. Furthermore the fundamental diagram for the movement in a corridor is reproduced. The results of the proposed model show a good agreement with empirical data.

  20. A quantitative model of human DNA base excision repair. I. mechanistic insights

    OpenAIRE

    Sokhansanj, Bahrad A.; Rodrigue, Garry R.; Fitch, J. Patrick; David M Wilson

    2002-01-01

    Base excision repair (BER) is a multistep process involving the sequential activity of several proteins that cope with spontaneous and environmentally induced mutagenic and cytotoxic DNA damage. Quantitative kinetic data on single proteins of BER have been used here to develop a mathematical model of the BER pathway. This model was then employed to evaluate mechanistic issues and to determine the sensitivity of pathway throughput to altered enzyme kinetics. Notably, the model predicts conside...

  1. Music-based interventions in palliative cancer care: a review of quantitative studies and neurobiological literature

    OpenAIRE

    Archie, Patrick; Bruera, Eduardo; Cohen, Lorenzo

    2013-01-01

    Purpose This study aimed to review quantitative literature pertaining to studies of music-based interventions in palliative cancer care and to review the neurobiological literature that may bare relevance to the findings from these studies. Methods A narrative review was performed, with particular emphasis on RCTs, meta-analyses, and systematic reviews. The Cochrane Library, Ovid, PubMed, CINAHL Plus, PsycINFO, and ProQuest were searched for the subject headings music, music therapy, cancer, ...

  2. Quantitative analysis of multiple components based on liquid chromatography with mass spectrometry in full scan mode.

    Science.gov (United States)

    Xu, Min Li; Li, Bao Qiong; Wang, Xue; Chen, Jing; Zhai, Hong Lin

    2016-08-01

    Although liquid chromatography with mass spectrometry in full scan mode can obtain all the signals simultaneously in a large range and low cost, it is rarely used in quantitative analysis due to several problems such as chromatographic drifts and peak overlap. In this paper, we propose a Tchebichef moment method for the simultaneous quantitative analysis of three active compounds in Qingrejiedu oral liquid based on three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry. After the Tchebichef moments were calculated directly from the spectra, the quantitative linear models for three active compounds were established by stepwise regression. All the correlation coefficients were more than 0.9978. The limits of detection and limits of quantitation were less than 0.11 and 0.49 μg/mL, respectively. The intra- and interday precisions were less than 6.54 and 9.47%, while the recovery ranged from 102.56 to 112.15%. Owing to the advantages of multi-resolution and inherent invariance properties, Tchebichef moments could provide favorable results even in the situation of peaks shifting and overlapping, unknown interferences and noise signals, so it could be applied to the analysis of three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry.

  3. A Quantitative Reasoning Approach to Algebra Using Inquiry-Based Learning

    Directory of Open Access Journals (Sweden)

    Victor I. Piercey

    2017-07-01

    Full Text Available In this paper, I share a hybrid quantitative reasoning/algebra two-course sequence that challenges the common assumption that quantitative literacy and reasoning are less rigorous mathematics alternatives to algebra and illustrates that a quantitative reasoning framework can be used to teach traditional algebra. The presentation is made in two parts. In the first part, which is somewhat philosophical and theoretical, I explain my personal perspective of what I mean by “algebra” and “doing algebra.” I contend that algebra is a form of communication whose value is precision, which allows us to perform algebraic manipulations in the form of simplification and solving moves. A quantitative reasoning approach to traditional algebraic manipulations rests on intentional and purposeful use of simplification and solving moves within contextual situations. In part 2, I describe a 6-week instructional module intended for undergraduate business students that was delivered to students who had placed into beginning algebra. The perspective described in part 1 heavily informed the design of this module. The course materials, which involve the use of Excel in multiple authentic contexts, are built around the use of inquiry-based learning. Upon completion of this module, the percentage of students who successfully complete model problems in an assessment is in the same range as surveyed students in precalculus and calculus, approximately two “grade levels” ahead of their placement.

  4. Genetic mapping and confirmation of quantitative trait loci for seed protein and oil contents and seed weight in soybean

    Science.gov (United States)

    Demand for soybean [Glycine max (L.) Merr.] meal has increased worldwide and soybean importers often offer premiums for soybean containing higher contents of protein and oil. Objectives were to detect quantitative trait loci (QTL) associated with soybean seed protein, oil, and seed weight in a soyb...

  5. Genetic network properties of the human cortex based on regional thickness and surface area measures

    Directory of Open Access Journals (Sweden)

    Anna R. Docherty

    2015-08-01

    Full Text Available We examined network properties of genetic covariance between average cortical thickness (CT and surface area (SA within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques—biometrical genetic modeling, cluster analysis, and graph theory—to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.

  6. Genetic network properties of the human cortex based on regional thickness and surface area measures

    Science.gov (United States)

    Docherty, Anna R.; Sawyers, Chelsea K.; Panizzon, Matthew S.; Neale, Michael C.; Eyler, Lisa T.; Fennema-Notestine, Christine; Franz, Carol E.; Chen, Chi-Hua; McEvoy, Linda K.; Verhulst, Brad; Tsuang, Ming T.; Kremen, William S.

    2015-01-01

    We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques—biometrical genetic modeling, cluster analysis, and graph theory—to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function. PMID:26347632

  7. MilQuant: a free, generic software tool for isobaric tagging-based quantitation.

    Science.gov (United States)

    Zou, Xiao; Zhao, Minzhi; Shen, Hongyan; Zhao, Xuyang; Tong, Yuanpeng; Wang, Qingsong; Wei, Shicheng; Ji, Jianguo

    2012-09-18

    Isobaric tagging techniques such as iTRAQ and TMT are widely used in quantitative proteomics and especially useful for samples that demand in vitro labeling. Due to diversity in choices of MS acquisition approaches, identification algorithms, and relative abundance deduction strategies, researchers are faced with a plethora of possibilities when it comes to data analysis. However, the lack of generic and flexible software tool often makes it cumbersome for researchers to perform the analysis entirely as desired. In this paper, we present MilQuant, mzXML-based isobaric labeling quantitator, a pipeline of freely available programs that supports native acquisition files produced by all mass spectrometer types and collection approaches currently used in isobaric tagging based MS data collection. Moreover, aside from effective normalization and abundance ratio deduction algorithms, MilQuant exports various intermediate results along each step of the pipeline, making it easy for researchers to customize the analysis. The functionality of MilQuant was demonstrated by four distinct datasets from different laboratories. The compatibility and extendibility of MilQuant makes it a generic and flexible tool that can serve as a full solution to data analysis of isobaric tagging-based quantitation.

  8. Genetic linkage maps of Pinus koraiensis Sieb. et Zucc. based on ...

    African Journals Online (AJOL)

    USER

    2010-08-30

    Aug 30, 2010 ... Genetic linkage maps provide essential information for molecular breeding. ... to plants are: (1) basic knowledge of genomic structure, ... quantitative trait expression. ... 11. A-6. GAA. CTC. 126. 27. 20. A-7. GAA. CTG. 113. 19. 13. A-3 .... combinations) code (the first three letters correspond to the selective ...

  9. Genetic mapping of quantitative trait loci affecting susceptibility in chicken to develop the Pulmonary Hypertension Syndrome (PHS)

    NARCIS (Netherlands)

    Rabie, T.S.K.M.; Crooijmans, R.P.M.A.; Bovenhuis, H.; Vereijken, A.L.J.; Veenendaal, A.; Poel, van der J.J.; Arendonk, van J.A.M.; Pakdel, A.; Groenen, M.A.M.

    2005-01-01

    Pulmonary hypertension syndrome (PHS), also referred to as ascites syndrome, is a growth-related disorder of chickens frequently observed in fast-growing broilers with insufficient pulmonary vascular capacity at low temperature and/or at high altitude. A cross between two genetically different

  10. Quantitative-genetic analysis of wing form and bilateral asymmetry in isochromosomal lines of Drosophila subobscura using Procrustes methods

    Indian Academy of Sciences (India)

    Pedro Fernández Iriarte; Walkiria Céspedes; Mauro Santos

    2003-12-01

    Fluctuating asymmetry (FA) is often used as a measure of underlying developmental instability (DI), motivated by the idea that morphological variance is maladaptive. Whether or not DI has evolutionary potential is a highly disputed topic, marred by methodological problems and fuzzy prejudices. We report here some results from an ongoing study of the effects of karyotype, homozygosity and temperature on wing form and bilateral asymmetry using isochromosomal lines of Drosophila subobscura. Our approach uses the recently developed methodologies in geometric morphometrics to analyse shape configurations of landmarks within the standard statistical framework employed in studies of bilateral asymmetries, and we have extended these methods to partition the individual variation and the variation in asymmetries into genetic and environmental causal components. The analyses revealed temperature-dependent expression of genetic variation for wing size and wing shape, directional asymmetry (DA) of wing size, increased asymmetries at suboptimal temperature, and a transition from FA to DA in males as a result of increase in the rearing temperature. No genetic variation was generally detected for FA in our samples, but these are preliminary results because no crosses between lines were carried out and, therefore, the contribution of dominance was not taken into account. In addition, only a subset of the standing genetic variation was represented in the experiments.

  11. Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes

    NARCIS (Netherlands)

    Pillai, S. G.; Tang, Y.; van den Oord, E.; Klotsman, M.; Barnes, K.; Carlsen, K.; Gerritsen, J.; Lenney, W.; Silverman, M.; Sly, P.; Sundy, J.; Tsanakas, J.; von Berg, A.; Whyte, M.; Ortega, H. G.; Anderson, W. H.; Helms, P. J.

    2008-01-01

    Background Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the

  12. An ultra-high-density map as a community resource for discerning the genetic basis of quantitative traits in maize

    Science.gov (United States)

    In this study, we generated a linkage map containing 1,151,856 high quality SNPs between Mo17 and B73, which were verified in the maize intermated B73'×'Mo17 (IBM) Syn10 population. This resource is an excellent complement to existing maize genetic maps available in an online database (iPlant, http:...

  13. Quantitation of Bt-176 maize genomic sequences by surface plasmon resonance-based biospecific interaction analysis of multiplex polymerase chain reaction (PCR).

    Science.gov (United States)

    Feriotto, Giordana; Gardenghi, Sara; Bianchi, Nicoletta; Gambari, Roberto

    2003-07-30

    Surface plasmon resonance (SPR) based biosensors have been described for the identification of genetically modified organisms (GMO) by biospecific interaction analysis (BIA). This paper describes the design and testing of an SPR-based BIA protocol for quantitative determinations of GMOs. Biotinylated multiplex Polymerase Chain Reaction (PCR) products from nontransgenic maize as well as maize powders containing 0.5 and 2% genetically modified Bt-176 sequences were immobilized on different flow cells of a sensor chip. After immobilization, different oligonucleotide probes recognizing maize zein and Bt-176 sequences were injected. The results obtained were compared with Southern blot analysis and with quantitative real-time PCR assays. It was demonstrated that sequential injections of Bt-176 and zein probes to sensor chip flow cells containing multiplex PCR products allow discrimination between PCR performed using maize genomic DNA containing 0.5% Bt-176 sequences and that performed using maize genomic DNA containing 2% Bt-176 sequences. The efficiency of SPR-based BIA in discriminating material containing different amounts of Bt-176 maize is comparable to real-time quantitative PCR and much more reliable than Southern blotting, which in the past has been used for semiquantitative purposes. Furthermore, the approach allows the BIA assay to be repeated several times on the same multiplex PCR product immobilized on the sensor chip, after washing and regeneration of the flow cell. Finally, it is emphasized that the presented strategy to quantify GMOs could be proposed for all of the SPR-based, commercially available biosensors. Some of these optical SPR-based biosensors use, instead of flow-based sensor chips, stirred microcuvettes, reducing the costs of the experimentation.

  14. International collaborative study of the endogenous reference gene, sucrose phosphate synthase (SPS), used for qualitative and quantitative analysis of genetically modified rice.

    Science.gov (United States)

    Jiang, Lingxi; Yang, Litao; Zhang, Haibo; Guo, Jinchao; Mazzara, Marco; Van den Eede, Guy; Zhang, Dabing

    2009-05-13

    One rice ( Oryza sativa ) gene, sucrose phosphate synthase (SPS), has been proven to be a suitable endogenous reference gene for genetically modified (GM) rice detection in a previous study. Herein are the reported results of an international collaborative ring trial for validation of the SPS gene as an endogenous reference gene and its optimized qualitative and quantitative polymerase chain reaction (PCR) systems. A total of 12 genetically modified organism (GMO) detection laboratories from seven countries participated in the ring trial and returned their results. The validated results confirmed the species specificity of the method through testing 10 plant genomic DNAs, low heterogeneity, and a stable single-copy number of the rice SPS gene among 7 indica varieties and 5 japonica varieties. The SPS qualitative PCR assay was validated with a limit of detection (LOD) of 0.1%, which corresponded to about 230 copies of haploid rice genomic DNA, while the limit of quantification (LOQ) for the quantitative PCR system was about 23 copies of haploid rice genomic DNA, with acceptable PCR efficiency and linearity. Furthermore, the bias between the test and true values of eight blind samples ranged from 5.22 to 26.53%. Thus, we believe that the SPS gene is suitable for use as an endogenous reference gene for the identification and quantification of GM rice and its derivates.

  15. Population-based resequencing of experimentally evolved populations reveals the genetic basis of body size variation in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Thomas L Turner

    2011-03-01

    Full Text Available Body size is a classic quantitative trait with evolutionarily significant variation within many species. Locating the alleles responsible for this variation would help understand the maintenance of variation in body size in particular, as well as quantitative traits in general. However, successful genome-wide association of genotype and phenotype may require very large sample sizes if alleles have low population frequencies or modest effects. As a complementary approach, we propose that population-based resequencing of experimentally evolved populations allows for considerable power to map functional variation. Here, we use this technique to investigate the genetic basis of natural variation in body size in Drosophila melanogaster. Significant differentiation of hundreds of loci in replicate selection populations supports the hypothesis that the genetic basis of body size variation is very polygenic in D. melanogaster. Significantly differentiated variants are limited to single genes at some loci, allowing precise hypotheses to be formed regarding causal polymorphisms, while other significant regions are large and contain many genes. By using significantly associated polymorphisms as a priori candidates in follow-up studies, these data are expected to provide considerable power to determine the genetic basis of natural variation in body size.

  16. Research on Modeling of Genetic Networks Based on Information Measurement

    Institute of Scientific and Technical Information of China (English)

    ZHANG Guo-wei; SHAO Shi-huang; ZHANG Ying; LI Hai-ying

    2006-01-01

    As the basis of network of biology organism, the genetic network is concerned by many researchers.Current modeling methods to genetic network, especially the Boolean networks modeling method are analyzed. For modeling the genetic network, the information theory is proposed to mining the relations between elements in network. Through calculating the values of information entropy and mutual entropy in a case, the effectiveness of the method is verified.

  17. Key Frames Extraction Based on the Improved Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHOU Dong-sheng; JIANG Wei; YI Peng-fei; LIURui

    2014-01-01

    In order toovercomethe poor local search ability of genetic algorithm, resulting in the basic genetic algorithm is time-consuming, and low search abilityin the late evolutionary, we use thegray coding instead ofbinary codingatthebeginning of the coding;we use multi-point crossoverto replace the originalsingle-point crossoveroperation.Finally, theexperimentshows that the improved genetic algorithmnot only has a strong search capability, but also thestability has been effectively improved.

  18. Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.

    Science.gov (United States)

    Schmitt, J Eric; Lenroot, Rhoshel K; Ordaz, Sarah E; Wallace, Gregory L; Lerch, Jason P; Evans, Alan C; Prom, Elizabeth C; Kendler, Kenneth S; Neale, Michael C; Giedd, Jay N

    2009-08-01

    The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.

  19. NOVEL QUANTUM-INSPIRED GENETIC ALGORITHM BASED ON IMMUNITY

    Institute of Scientific and Technical Information of China (English)

    Li Ying; Zhao Rongchun; Zhang Yanning; Jiao Licheng

    2005-01-01

    A novel algorithm, the Immune Quantum-inspired Genetic Algorithm (IQGA), is proposed by introducing immune concepts and methods into Quantum-inspired Genetic Algorithm (QGA). With the condition of preserving QGA's advantages, IQGA utilizes the characteristics and knowledge in the pending problems for restraining the repeated and ineffective operations during evolution, so as to improve the algorithm efficiency. The experimental results of the knapsack problem show that the performance of IQGA is superior to the Conventional Genetic Algorithm (CGA), the Immune Genetic Algorithm (IGA) and QGA.

  20. Identification of Hammerstein Model Based on Quantum Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Zhang Hai Li

    2013-07-01

    Full Text Available Nonlinear system identification is a main topic of modern identification. A new method for nonlinear system identification is presented by using Quantum Genetic Algorithm(QGA.The problems of nonlinear system identification are cast as function optimization overprameter space,and the Quantum Genetic Algorithm is adopted to solve the optimization problem. Simulation experiments show that: compared with the genetic algorithm, quantum genetic algorithm is an effective swarm intelligence algorithm, its salient features of the algorithm parameters, small population size, and the use of Quantum gate update populations, greatly improving the recognition in the optimization of speed and accuracy. Simulation results show the effectiveness of the proposed method.

  1. Annotated genetic linkage maps of Pinus pinaster Ait. from a Central Spain population using microsatellite and gene based markers

    Directory of Open Access Journals (Sweden)

    de Miguel Marina

    2012-10-01

    Full Text Available Abstract Background Pinus pinaster Ait. is a major resin producing species in Spain. Genetic linkage mapping can facilitate marker-assisted selection (MAS through the identification of Quantitative Trait Loci and selection of allelic variants of interest in breeding populations. In this study, we report annotated genetic linkage maps for two individuals (C14 and C15 belonging to a breeding program aiming to increase resin production. We use different types of DNA markers, including last-generation molecular markers. Results We obtained 13 and 14 linkage groups for C14 and C15 maps, respectively. A total of 211 and 215 markers were positioned on each map and estimated genome length was between 1,870 and 2,166 cM respectively, which represents near 65% of genome coverage. Comparative mapping with previously developed genetic linkage maps for P. pinaster based on about 60 common markers enabled aligning linkage groups to this reference map. The comparison of our annotated linkage maps and linkage maps reporting QTL information revealed 11 annotated SNPs in candidate genes that co-localized with previously reported QTLs for wood properties and water use efficiency. Conclusions This study provides genetic linkage maps from a Spanish population that shows high levels of genetic divergence with French populations from which segregating progenies have been previously mapped. These genetic maps will be of interest to construct a reliable consensus linkage map for the species. The importance of developing functional genetic linkage maps is highlighted, especially when working with breeding populations for its future application in MAS for traits of interest.

  2. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  3. A Gene-Pool Based Genetic Algorithm for TSP

    Institute of Scientific and Technical Information of China (English)

    Yang Hui; Kang Li-shan; Chen Yu-ping

    2003-01-01

    Based on the analysis of previous genetic algo rithms (GAs) for TSP, a novel method called Ge GA is proposed. It combines gene pool and GA so as to direct the evo lution of the whole population. The core of Ge GA is the construction of gene pool and how to apply it to GA. Different from standard GAs, Ge-GA aims to enhance the ability of exploration and exploitation by incorporating global search with local search. On one hand a local search called Ge LocalSearch operator is proposed to improve the solution quality, on the other hand the modified Inver-Over operator called Ge InverOver is considered as a global search mechanism to expand solution space of local minimal. Both of these operators are based on the gene pool. Our algorithm is applied to 11 well-known traveling salesman problems whose numbers of cities are from 70 to 1577 cities. The experiments results indicate that Ge GA has great robustness for TSP. For each test instance, the average value of solution quality, found in accepted time, stays within 0. 001 % from the optimum.

  4. Digital Image Encryption Algorithm Design Based on Genetic Hyperchaos

    Directory of Open Access Journals (Sweden)

    Jian Wang

    2016-01-01

    Full Text Available In view of the present chaotic image encryption algorithm based on scrambling (diffusion is vulnerable to choosing plaintext (ciphertext attack in the process of pixel position scrambling, we put forward a image encryption algorithm based on genetic super chaotic system. The algorithm, by introducing clear feedback to the process of scrambling, makes the scrambling effect related to the initial chaos sequence and the clear text itself; it has realized the image features and the organic fusion of encryption algorithm. By introduction in the process of diffusion to encrypt plaintext feedback mechanism, it improves sensitivity of plaintext, algorithm selection plaintext, and ciphertext attack resistance. At the same time, it also makes full use of the characteristics of image information. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist plaintext (ciphertext attack, statistical attack, and information entropy attack but also effectively improve the efficiency of image encryption, which is a relatively secure and effective way of image communication.

  5. Nanotechnology Based Treatments for Neurological Disorders from Genetics Perspective

    Directory of Open Access Journals (Sweden)

    Nicholas S. Kurek

    2013-02-01

    Full Text Available Nanotechology involves the application, analysis and manipulation of nanomaterials. These materials have unique and medically useful properties due to their nanoscale parameters. Nanotechnology based treatments and diagnostics might eventually bring great relief to people suffering from neurological disorders including autism spectrum disorders, Alzheimer’s disease and Parkinson’s disorders. A large variety of nonmaterials such as viruses, carbon nanotubes, gold and silica nanoparticles, nanoshells, quantum dots, genetic material and proteins as well as hordes of other forms of nanotechnology have been researched in order to determine their potential in enhancing disease treatments and diagnostics. Nanotechnology has shown countless applications and might eventually be used in every biotech/health industry. Nevertheless, many nanomaterials may pose some safety risks and whether their benefits overweigh the risk is still being debated. Once the proper ethical and safety protocols are established and enough research is completed, nanotechnology is expected to benefit the mankind enormously. In this article, we will discuss and analyze many ways in which, nanotechnology based treatments and diagnostics will be used to help people with neurological disorders through the methods that we currently have at our disposal. [Archives Medical Review Journal 2013; 22(1.000: 12-32

  6. Genetics algorithm optimization of DWT-DCT based image Watermarking

    Science.gov (United States)

    Budiman, Gelar; Novamizanti, Ledya; Iwut, Iwan

    2017-01-01

    Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit “1” and –delta represents bit “0”. Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

  7. Scientifically Based Research in Quantitative Literacy: Guidelines for Building a Knowledge Base

    OpenAIRE

    Richard L. Scheaffer

    2008-01-01

    Research in quantitative literacy (QL) is in its infancy, so now is the time to begin a regimen for healthy growth into adulthood. As a new discipline still defining itself, QL has the opportunity to build a sound infrastructure for accumulating a solid body of interconnected research that will serve the discipline well in years to come. To that end, much can be learned from recent studies of the weaknesses of mathematics education research and recommendations on how to overcome them. Mathema...

  8. Gene-based multiple regression association testing for combined examination of common and low frequency variants in quantitative trait analysis

    Directory of Open Access Journals (Sweden)

    Yun Joo eYoo

    2013-11-01

    Full Text Available Multi-marker methods for genetic association analysis can be performed for common and low frequency SNPs to improve power. Regression models are an intuitive way to formulate multi-marker tests. In previous studies we evaluated regression-based multi-marker tests for common SNPs, and through identification of bins consisting of correlated SNPs, developed a multi-bin linear combination (MLC test that is a compromise between a 1df linear combination test and a multi-df global test. Bins of SNPs in high linkage disequilibrium (LD are identified, and a linear combination of individual SNP statistics is constructed within each bin. Then association with the phenotype is represented by an overall statistic with df as many or few as the number of bins. In this report we evaluate multi-marker tests for SNPs that occur at low frequencies. There are many linear and quadratic multi-marker tests that are suitable for common or low frequency variant analysis. We compared the performance of the MLC tests with various linear and quadratic statistics in joint or marginal regressions. For these comparisons, we performed a simulation study of genotypes and quantitative traits for 85 genes with many low frequency SNPs based on HapMap Phase III. We compared the tests using 1 set of all SNPs in a gene, 2 set of common SNPs in a gene (MAF≥5%, 3 set of low frequency SNPs (1%≤MAF

  9. A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry

    Science.gov (United States)

    Trompelt, Kerstin; Steinbeck, Janina; Terashima, Mia; Hippler, Michael

    2014-01-01

    The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex composition under different conditions. In this protocol the approach is demonstrated by comparing the composition of the protein complex responsible for cyclic electron flow (CEF) in Chlamydomonas reinhardtii, isolated from genetically different strains. The procedure comprises the isolation of thylakoid membranes, followed by their separation into multiprotein complexes by sucrose density gradient centrifugation, SDS-PAGE, immunodetection and comparative, quantitative mass spectrometry (MS) based on differential metabolic labeling (14N/15N) of the analyzed strains. Detergent solubilized thylakoid membranes are loaded on sucrose density gradients at equal chlorophyll concentration. After ultracentrifugation, the gradients are separated into fractions, which are analyzed by mass-spectrometry based on equal volume. This approach allows the investigation of the composition within the gradient fractions and moreover to analyze the migration behavior of different proteins, especially focusing on ANR1, CAS, and PGRL1. Furthermore, this method is demonstrated by confirming the results with immunoblotting and additionally by supporting the findings from previous studies (the identification and PSI-dependent migration of proteins that were previously described to be part of the CEF-supercomplex such as PGRL1, FNR, and cyt f). Notably, this approach is applicable to address a broad range of questions for which this protocol can be adopted and e.g. used for comparative analyses of multiprotein complex composition isolated from distinct environmental conditions. PMID:24686495

  10. Evaluation and selection of the ship collaborative design resources based on AHP and genetic and simulated annealing algorithm

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The characteristics of the design resources in the ship collaborative design is described and the hierarchical model for the evaluation of the design resources is established. The comprehensive evaluation of the co-designers for the collaborative design resources has been done from different aspects using Analytic Hierarchy Process (AHP),and according to the evaluation results,the candidates are determined. Meanwhile,based on the principle of minimum cost,and starting from the relations between the design tasks and the corresponding co-designers,the optimizing selection model of the collaborators is established and one novel genetic combined with simulated annealing algorithm is proposed to realize the optimization. It overcomes the defects of the genetic algorithm which may lead to the premature convergence and local optimization if used individually. Through the application of this method in the ship collaborative design system,it proves the feasibility and provides a quantitative method for the optimizing selection of the design resources.

  11. A novel quantitative imaging technique for material differentiation based on differential phase contrast CT

    Science.gov (United States)

    Qi, Zhihua; Zambelli, Joseph; Bevins, Nicholas; Chen, Guang-Hong

    2010-04-01

    Compared to single energy CT, which provides information only about the x-ray linear attenuation coefficients, dual energy CT is able to obtain the electron density and effective atomic number for different materials in a quantitative way. In this study, as an alternative to dual energy CT, a novel quantitative imaging method based on phase contrast CT is described. Rather than requiring two scans with different x-ray photon energies, diffraction grating-based phase contrast CT is capable of reconstructing images of both the linear attenuation and refractive index decrement from a single scan. From the two images, quantitative information of both the electron density and effective atomic number can be extracted. Experimental results demonstrate that: (1) electron density can be accurately determined from refractive index decrement through a linear relationship; and (2) effective atomic number can be explicitly derived from the ratio of linear attenuation to refractive index decrement, using a simple function, i.e., a power function plus a constant. The presented method will shed insight into the field of material separation and find its use in medical and non-medical applications.

  12. A remote quantitative Fugl-Meyer assessment framework for stroke patients based on wearable sensor networks.

    Science.gov (United States)

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-05-01

    To extend the use of wearable sensor networks for stroke patients training and assessment in non-clinical settings, this paper proposes a novel remote quantitative Fugl-Meyer assessment (FMA) framework, in which two accelerometer and seven flex sensors were used to monitoring the movement function of upper limb, wrist and fingers. The extreme learning machine based ensemble regression model was established to map the sensor data to clinical FMA scores while the RRelief algorithm was applied to find the optimal features subset. Considering the FMA scale is time-consuming and complicated, seven training exercises were designed to replace the upper limb related 33 items in FMA scale. 24 stroke inpatients participated in the experiments in clinical settings and 5 of them were involved in the experiments in home settings after they left the hospital. Both the experimental results in clinical and home settings showed that the proposed quantitative FMA model can precisely predict the FMA scores based on wearable sensor data, the coefficient of determination can reach as high as 0.917. It also indicated that the proposed framework can provide a potential approach to the remote quantitative rehabilitation training and evaluation.

  13. Genetic programming-based approach to elucidate biochemical interaction networks from data.

    Science.gov (United States)

    Kandpal, Manoj; Kalyan, Chakravarthy Mynampati; Samavedham, Lakshminarayanan

    2013-02-01

    Biochemical systems are characterised by cyclic/reversible reciprocal actions, non-linear interactions and a mixed relationship structures (linear and non-linear; static and dynamic). Deciphering the architecture of such systems using measured data to provide quantitative information regarding the nature of relationships that exist between the measured variables is a challenging proposition. Causality detection is one of the methodologies that are applied to elucidate biochemical networks from such data. Autoregressive-based modelling approach such as granger causality, partial directed coherence, directed transfer function and canonical variate analysis have been applied on different systems for deciphering such interactions, but with limited success. In this study, the authors propose a genetic programming-based causality detection (GPCD) methodology which blends evolutionary computation-based procedures along with parameter estimation methods to derive a mathematical model of the system. Application of the GPCD methodology on five data sets that contained the different challenges mentioned above indicated that GPCD performs better than the other methods in uncovering the exact structure with less false positives. On a glycolysis data set, GPCD was able to fill the 'interaction gaps' which were missed by other methods.

  14. Psychiatrists' views of the genetic bases of mental disorders and behavioral traits and their use of genetic tests.

    Science.gov (United States)

    Klitzman, Robert; Abbate, Kristopher J; Chung, Wendy K; Marder, Karen; Ottman, Ruth; Taber, Katherine Johansen; Leu, Cheng-Shiun; Appelbaum, Paul S

    2014-07-01

    We examined how 372 psychiatrists view genetic aspects of mental disorders and behaviors and use genetic tests (GTs). Most thought that the genetic contribution was moderate/high for bipolar disorder, schizophrenia, depression, Alzheimer's, intelligence, creativity, anxiety, and suicidality. In the past 6 months, 14.1% ordered GTs, 18.3% discussed prenatal testing with patients, 36.0% initiated discussions about other GTs, 41.6% had patients ask about GTs, and 5.3% excluded GT results from patient records. Many thought that GTs; were available for schizophrenia (24.3%) and major depression (19.6%). Women were more likely to report that patients asked about GTs; and were less certain about the degree of genetic contribution to several disorders. Psychiatrists perceive strong genetic bases for numerous disorders and traits, and many have discussed and ordered tests for GTs, but have relatively limited knowledge about available tests. These data suggest possible sex differences in psychiatrists' beliefs about genetic contributions to disorders and have implications for future research, education, policy, and care.

  15. Quantitative detection of defects based on Markov-PCA-BP algorithm using pulsed infrared thermography technology

    Science.gov (United States)

    Tang, Qingju; Dai, Jingmin; Liu, Junyan; Liu, Chunsheng; Liu, Yuanlin; Ren, Chunping

    2016-07-01

    Quantitative detection of debonding defects' diameter and depth in TBCs has been carried out using pulsed infrared thermography technology. By combining principal component analysis with neural network theory, the Markov-PCA-BP algorithm was proposed. The principle and realization process of the proposed algorithm was described. In the prediction model, the principal components which can reflect most characteristics of the thermal wave signal were set as the input, and the defect depth and diameter was set as the output. The experimental data from pulsed infrared thermography tests of TBCs with flat bottom hole defects was selected as the training and testing sample. Markov-PCA-BP predictive system was arrived, based on which both the defect depth and diameter were identified accurately, which proved the effectiveness of the proposed method for quantitative detection of debonding defects in TBCs.

  16. [Quantitative specific detection of Staphylococcus aureus based on recombinant lysostaphin and ATP bioluminescence].

    Science.gov (United States)

    Li, Yuyuan; Mi, Zhiqiang; An, Xiaoping; Zhou, Yusen; Tong, Yigang

    2014-08-01

    Quantitative specific detection of Staphylococcus aureus is based on recombinant lysostaphin and ATP bioluminescence. To produce recombinant lysostaphin, the lysostaphin gene was chemically synthesized and inserted it into prokaryotic expression vector pQE30, and the resulting expression plasmid pQE30-Lys was transformed into E. coli M15 for expressing lysostaphin with IPTG induction. The recombinant protein was purified by Ni(2+)-NTA affinity chromatography. Staphylococcus aureus was detected by the recombinant lysostaphin with ATP bioluminescence, and plate count method. The results of the two methods were compared. The recombinant lysostaphin was successfully expressed, and a method of quantitative specific detection of S. aureus has been established, which showed a significant linear correlation with the colony counting. The detection method developed has good perspective to quantify S. aureus.

  17. Quantitative Profiling of Long-Chain Bases by Mass Tagging and Parallel Reaction Monitoring

    DEFF Research Database (Denmark)

    Ejsing, Christer S; Bilgin, Mesut; Fabregat, Andreu

    2015-01-01

    Long-chain bases (LCBs) are both intermediates in sphingolipid metabolism and potent signaling molecules that control cellular processes. To understand how regulation of sphingolipid metabolism and levels of individual LCB species impinge upon physiological and pathophysiological processes requires...... sensitive and specific assays for monitoring these molecules. Here we describe a shotgun lipidomics method for quantitative profiling of LCB molecules. The method employs a "mass-tag" strategy where LCBs are chemically derivatized with deuterated methyliodide (CD3I) to produce trimethylated derivatives...... having a positively charged quaternary amine group. This chemical derivatization minimizes unwanted in-source fragmentation of LCB analytes and prompts a characteristic trimethylaminium fragment ion that enables sensitive and quantitative profiling of LCB molecules by parallel reaction monitoring...

  18. Primer design using Primer Express® for SYBR Green-based quantitative PCR.

    Science.gov (United States)

    Singh, Amarjeet; Pandey, Girdhar K

    2015-01-01

    To quantitate the gene expression, real-time RT-PCR or quantitative PCR (qPCR) is one of the most sensitive, reliable, and commonly used methods in molecular biology. The reliability and success of a real-time PCR assay depend on the optimal experiment design. Primers are the most important constituents of real-time PCR experiments such as in SYBR Green-based detection assays. Designing of an appropriate and specific primer pair is extremely crucial for correct estimation of transcript abundance of any gene in a given sample. Here, we are presenting a quick, easy, and reliable method for designing target-specific primers using Primer Express(®) software for real-time PCR (qPCR) experiments.

  19. A new quantitative model of ecological compensation based on ecosystem capital in Zhejiang Province, China.

    Science.gov (United States)

    Jin, Yan; Huang, Jing-feng; Peng, Dai-liang

    2009-04-01

    Ecological compensation is becoming one of key and multidiscipline issues in the field of resources and environmental management. Considering the change relation between gross domestic product (GDP) and ecological capital (EC) based on remote sensing estimation, we construct a new quantitative estimate model for ecological compensation, using county as study unit, and determine standard value so as to evaluate ecological compensation from 2001 to 2004 in Zhejiang Province, China. Spatial differences of the ecological compensation were significant among all the counties or districts. This model fills up the gap in the field of quantitative evaluation of regional ecological compensation and provides a feasible way to reconcile the conflicts among benefits in the economic, social, and ecological sectors.

  20. Estimation of genetic parameters and detection of quantitative trait loci for minerals in Danish Holstein and Danish Jersey milk

    DEFF Research Database (Denmark)

    Buitenhuis, Albert Johannes; Poulsen, Nina Aagaard; Sehested, Jakob

    2015-01-01

    Background Bovine milk provides important minerals, essential for human nutrition and dairy product quality. For changing the mineral composition of the milk to improve dietary needs in human nutrition and technological properties of milk, a thorough understanding of the genetics underlying milk...... mineral contents is important. Therefore the aim of this study was to 1) estimate the genetic parameters for individual minerals in Danish Holstein (DH) (n = 371) and Danish Jersey (DJ) (n = 321) milk, and 2) detect genomic regions associated with mineral content in the milk using a genome...... The results show that Ca, Zn, P and Mg show high heritabilities. In combination with the GWAS results this opens up possibilities to select for specific minerals in bovine milk....

  1. Multiple Query Evaluation Based on an Enhanced Genetic Algorithm.

    Science.gov (United States)

    Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand

    2003-01-01

    Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…

  2. AMOVA-based clustering of population genetic data

    NARCIS (Netherlands)

    Meirmans, P.G.

    2012-01-01

    Determining the genetic structure of populations is becoming an increasingly important aspect of genetic studies. One of the most frequently used methods is the calculation of F-statistics using an Analysis of Molecular Variance (AMOVA). However, this has the drawback that the population hierarchy

  3. Simulation based virtual learning environment in medical genetics counseling

    DEFF Research Database (Denmark)

    Makransky, Guido; Bonde, Mads T; Wulff, Julie S G;

    2016-01-01

    understanding of medical genetics, 82 % thought that medical genetics was more interesting, 93 % indicated that they were more interested and motivated, and had gained confidence by having experienced working on a case story that resembled the real working situation of a doctor, and 78 % indicated...

  4. Genetic Algorithm Based Proportional Integral Controller Design for Induction Motor

    Directory of Open Access Journals (Sweden)

    Mohanasundaram Kuppusamy

    2011-01-01

    Full Text Available Problem statement: This study has expounded the application of evolutionary computation method namely Genetic Algorithm (GA for estimation of feedback controller parameters for induction motor. GA offers certain advantages such as simple computational steps, derivative free optimization, reduced number of iterations and assured near global optima. The development of the method is well documented and computed and measured results are presented. Approach: The design of PI controller parameter for three phase induction motor drives was done using Genetic Algorithm. The objective function of motor current reduction, using PI controller, at starting is formulated as an optimization problem and solved with Genetic Algorithm. Results: The results showed the selected values of PI controller parameter using genetic algorithm approach, with objective of induction motor starting current reduction. Conclusions/Recommendation: The results proved the robustness and easy implementation of genetic algorithm selection of PI parameters for induction motor starting.

  5. Construction of a High-Density Genetic Map and Quantitative Trait Locus Mapping in the Sea Cucumber Apostichopus japonicus.

    Science.gov (United States)

    Tian, Meilin; Li, Yangping; Jing, Jing; Mu, Chuang; Du, Huixia; Dou, Jinzhuang; Mao, Junxia; Li, Xue; Jiao, Wenqian; Wang, Yangfan; Hu, Xiaoli; Wang, Shi; Wang, Ruijia; Bao, Zhenmin

    2015-10-06

    Genetic linkage maps are critical and indispensable tools in a wide range of genetic and genomic research. With the advancement of genotyping-by-sequencing (GBS) methods, the construction of a high-density and high-resolution linkage maps has become achievable in marine organisms lacking sufficient genomic resources, such as echinoderms. In this study, high-density, high-resolution genetic map was constructed for a sea cucumber species, Apostichopus japonicus, utilizing the 2b-restriction site-associated DNA (2b-RAD) method. A total of 7839 markers were anchored to the linkage map with the map coverage of 99.57%, to our knowledge, this is the highest marker density among echinoderm species. QTL mapping and association analysis consistently captured one growth-related QTL located in a 5 cM region of linkage group (LG) 5. An annotated candidate gene, retinoblastoma-binding protein 5 (RbBP5), which has been reported to be an important regulator of cell proliferation, was recognized in the QTL region. This linkage map represents a powerful tool for research involving both fine-scale QTL mapping and marker assisted selection (MAS), and will facilitate chromosome assignment and improve the whole-genome assembly of sea cucumber in the future.

  6. Contrasting patterns of quantitative and neutral genetic variation in locally adapted populations of the natterjack toad, Bufo calamita.

    Science.gov (United States)

    Gomez-Mestre, Ivan; Tejedo, Miguel

    2004-10-01

    The relative importance of natural selection and genetic drift in determining patterns of phenotypic diversity observed in nature is still unclear. The natterjack toad (Bufo calamita) is one of a few amphibian species capable of breeding in saline ponds, even though water salinity represents a considerable stress for them. Results from two common-garden experiments showed a pattern of geographic variation in embryonic salinity tolerance among populations from either fresh or brackish environments, consistent with the hypothesis of local adaptation. Full-sib analysis showed increased variation in survival among sibships within population for all populations as osmotic stress was increased (broad-sense heritability increased as salinity raised). Nevertheless, toads native to the brackish water environment had the highest overall survival under brackish conditions. Levels of population genetic differentiation for salinity tolerance were higher than those of neutral genetic differentiation, the latter obtained through the analysis of eight microsatellite loci. Microsatellite markers also revealed little population differentiation, lack of an isolation-by-distance pattern, and moderate gene flow connecting the populations. Therefore, environmental stress tolerance appears to have evolved in absence of geographic isolation, and consequently we reject the null hypothesis of neutral differentiation.

  7. Assessing the performance capabilities of LRE-based assays for absolute quantitative real-time PCR.

    Directory of Open Access Journals (Sweden)

    Robert G Rutledge

    Full Text Available BACKGROUND: Linear regression of efficiency or LRE introduced a new paradigm for conducting absolute quantification, which does not require standard curves, can generate absolute accuracies of +/-25% and has single molecule sensitivity. Derived from adapting the classic Boltzmann sigmoidal function to PCR, target quantity is calculated directly from the fluorescence readings within the central region of an amplification profile, generating 4-8 determinations from each amplification reaction. FINDINGS: Based on generating a linear representation of PCR amplification, the highly visual nature of LRE analysis is illustrated by varying reaction volume and amplification efficiency, which also demonstrates how LRE can be used to model PCR. Examining the dynamic range of LRE further demonstrates that quantitative accuracy can be maintained down to a single target molecule, and that target quantification below ten molecules conforms to that predicted by Poisson distribution. Essential to the universality of optical calibration, the fluorescence intensity generated by SYBR Green I (FU/bp is shown to be independent of GC content and amplicon size, further verifying that absolute scale can be established using a single quantitative standard. Two high-performance lambda amplicons are also introduced that in addition to producing highly precise optical calibrations, can be used as benchmarks for performance testing. The utility of limiting dilution assay for conducting platform-independent absolute quantification is also discussed, along with the utility of defining assay performance in terms of absolute accuracy. CONCLUSIONS: Founded on the ability to exploit lambda gDNA as a universal quantitative standard, LRE provides the ability to conduct absolute quantification using few resources beyond those needed for sample preparation and amplification. Combined with the quantitative and quality control capabilities of LRE, this kinetic-based approach has the

  8. [Current methods in genetic analysis : an approach for genetics-based preventive medicine].

    Science.gov (United States)

    Klein, Hans-Georg; Rost, Imma

    2015-02-01

    Modern genetic analysis methods such as DNA arrays (gene chips) or high-throughput DNA sequencing of the next generation (Next Generation Sequencing, NGS) have once again accelerated the pace of innovation that has been powered by genome research over the past 10 years of the "post-genomic era". The present paper introduces array and NGS methods as two important innovation driving methods and provides examples for their application in large-scale scientific projects. However, a broad application of these very powerful technologies for genetic screening for the purpose of disease prevention is currently not yet in sight. The complexity of the interaction of genes, gene products and the environment has so far exceeded all expectations, suggesting that reliable statements about the medical relevance of common genetic variants can presently only be made in a few areas such as pharmacogenetics and oncology. We also discuss ethical issues raised by genetic population screening. The aim of this paper is to provide a brief outline of the development of methods in molecular genetics to the now dominant modern technologies and present their applications in research, in the diagnosis of rare diseases, and in terms of screening approaches.

  9. [Application of case-based method in genetics and eugenics teaching].

    Science.gov (United States)

    Li, Ya-Xuan; Zhao, Xin; Zhang, Fei-Xiong; Hu, Ying-Kao; Yan, Yue-Ming; Cai, Min-Hua; Li, Xiao-Hui

    2012-05-01

    Genetics and Eugenics is a cross-discipline between genetics and eugenics. It is a common curriculum in many Chinese universities. In order to increase the learning interest, we introduced case teaching method and got a better teaching effect. Based on our teaching practices, we summarized some experiences about this subject. In this article, the main problem of case-based method applied in Genetics and Eugenics teaching was discussed.

  10. Linkage Map Construction and Quantitative Trait Loci Analysis for Bolting Based on a Double Haploid Population of Brassica rapa

    Institute of Scientific and Technical Information of China (English)

    Xu Yang; Yang-Jun Yu; Feng-Lan Zhang; Zhi-Rong Zou; Xiu-Yun Zhao; De-Shuang Zhang; Jia-Bing Xu

    2007-01-01

    Early bolting of Chinese cabbage (Brassica rapa L.) during spring cultivation often has detrimental effects on the yield and quality of the harvested products. Breeding late bolting varieties is a major objective of Chinese cabbage breeding programs. in order to analyze the genetic basis of bolting traits, a genetic map of B. rapa was constructed based on amplified fragment-length polymorphism (AFLP), sequence-related amplified polymorphism (SRAP), simple sequence repeat (SSR), random amplification of polymorphic DNA (RAPD), and isozyme markers. Marker analysis was carried out on 81 double haploid (DH) lines obtained by mlcrospore culture from F1 progeny of two homozygous parents: B. rapa L. ssp. pekinensis (BY) (an extra-early bolting Chinese cabbage line) and B. rapa L. ssp. rapifera (MM) (an extra-late bolting European turnip line). A total of 326 markers including 130 AFLPs, 123 SRAPs, 16 SSRs, 43RAPDs and 14 isozymes were used to construct a linkage map with 10 linkage groups covering 882 cM with an average distance of 2.71 cM between loci. The bolting trait of each DH line was evaluated by the bolting index under controlled conditions. Quantitative trait loci (QTL) analysis was conducted using multiple QTL model mapping with MapQTL5.0 software. Eight QTLs controlling bolting resistance were identified. These QTLs, accounting for 14.1% to 25.2% of the phenotyplc variation with positive additive effects, were distributed into three linkage groups. These results provide useful information for molecular marker-assisted selection of late bolting traits in Chinese cabbage breeding programs.

  11. Genetic relationships among Heliconia (Heliconiaceae) species based on RAPD markers.

    Science.gov (United States)

    Marouelli, L P; Inglis, P W; Ferreira, M A; Buso, G S C

    2010-07-13

    The family Heliconiaceae contains a single genus, Heliconia, with approximately 180 species of Neotropical origin. This genus was formerly allocated to the family Musaceae, but today forms its own family, in the order Zingiberales. The combination of inverted flowers, a single staminode and drupe fruits is an exclusive characteristic of Heliconia. Heliconias are cultivated as ornamental garden plants, and are of increasing importance as cut flowers. However, there are taxonomic confusions and uncertainties about the number of species and the relationships among them. Molecular studies are therefore necessary for better understanding of the species boundaries of these plants. We examined the genetic variability and the phylogenetic relationships of 124 accessions of the genus Heliconia based on RAPD markers. Phenetic and cladistic analyses, using 231 polymorphic RAPD markers, demonstrated that the genus Heliconia is monophyletic. Groupings corresponding to currently recognized species and some subgenera were found, and cultivars and hybrids were found to cluster with their parents. RAPD analysis generally agreed with morphological species classification, except for the position of the subgenus Stenochlamys, which was found to be polyphyletic.

  12. Genetic Algorithm (GA)-Based Inclinometer Layout Optimization.

    Science.gov (United States)

    Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo

    2015-04-17

    This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors.

  13. Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Zu Yun-Xiao; Zhou Jie

    2012-01-01

    Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm is proposed,and a fitness function is provided.Simulations are conducted using the adaptive niche immune genetic algorithm,the simulated annealing algorithm,the quantum genetic algorithm and the simple genetic algorithm,respectively.The results show that the adaptive niche immune genetic algorithm performs better than the other three algorithms in terms of the multi-user cognitive radio network resource allocation,and has quick convergence speed and strong global searching capability,which effectively reduces the system power consumption and bit error rate.

  14. A New Genetic Algorithm Based on Niche Technique and Local Search Method

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The genetic algorithm has been widely used in many fields as an easy robust global search and optimization method. In this paper, a new genetic algorithm based on niche technique and local search method is presented under the consideration of inadequacies of the simple genetic algorithm. In order to prove the adaptability and validity of the improved genetic algorithm, optimization problems of multimodal functions with equal peaks, unequal peaks and complicated peak distribution are discussed. The simulation results show that compared to other niching methods, this improved genetic algorithm has obvious potential on many respects, such as convergence speed, solution accuracy, ability of global optimization, etc.

  15. Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm

    Science.gov (United States)

    Zu, Yun-Xiao; Zhou, Jie

    2012-01-01

    Multi-user cognitive radio network resource allocation based on the adaptive niche immune genetic algorithm is proposed, and a fitness function is provided. Simulations are conducted using the adaptive niche immune genetic algorithm, the simulated annealing algorithm, the quantum genetic algorithm and the simple genetic algorithm, respectively. The results show that the adaptive niche immune genetic algorithm performs better than the other three algorithms in terms of the multi-user cognitive radio network resource allocation, and has quick convergence speed and strong global searching capability, which effectively reduces the system power consumption and bit error rate.

  16. Rapid and quantitative detection of C-reactive protein based on quantum dots and immunofiltration assay

    Directory of Open Access Journals (Sweden)

    Zhang PF

    2015-09-01

    Full Text Available Pengfei Zhang,1,* Yan Bao,1,* Mohamed Shehata Draz,2,3,* Huiqi Lu,1 Chang Liu,1 Huanxing Han11Center for Translational Medicine, Changzheng Hospital, Second Military Medical University, Shanghai, People’s Republic of China; 2Zhejiang-California International Nanosystems Institute, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 3Faculty of Science, Tanta University, Tanta, Egypt*These authors contributed equally to this workAbstract: Convenient and rapid immunofiltration assays (IFAs enable on-site “yes” or “no” determination of disease markers. However, traditional IFAs are commonly qualitative or semi-quantitative and are very limited for the efficient testing of samples in field diagnostics. Here, we overcome these limitations by developing a quantum dots (QDs-based fluorescent IFA for the quantitative detection of C-reactive proteins (CRP. CRP, the well-known diagnostic marker for acute viral and bacterial infections, was used as a model analyte to demonstrate performance and sensitivity of our developed QDs-based IFA. QDs capped with both polyethylene glycol (PEG and glutathione were used as fluorescent labels for our IFAs. The presence of the surface PEG layer, which reduced the non-specific protein interactions, in conjunction with the inherent optical properties of QDs, resulted in lower background signal, increased sensitivity, and ability to detect CRP down to 0.79 mg/L with only 5 µL serum sample. In addition, the developed assay is simple, fast and can quantitatively detect CRP with a detection limit up to 200 mg/L. Clinical test results of our QD-based IFA are well correlated with the traditional latex enhance immune-agglutination aggregation. The proposed QD-based fluorescent IFA is very promising, and potentially will be adopted for multiplexed immunoassay and in field point-of-care test.Keywords: C-reactive proteins, point-of-care test, Glutathione capped QDs, PEGylation

  17. Reliability Based Spare Parts Management Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Rahul Upadhyay

    2015-08-01

    Full Text Available Effective and efficient inventory management is the key to the economic sustainability of capital intensive modern industries. Inventory grows exponentially with complexity and size of the equipment fleet. Substantial amount of capital is required for maintaining an inventory and therefore its optimization is beneficial for smooth operation of the project at minimum cost of inventory. The size and hence the cost of the inventory is influenced by a large no of factors. This makes the optimization problem complex. This work presents a model to solve the problem of optimization of spare parts inventory. The novelty of this study lies with the fact that the developed method could tackle not only the artificial test case but also a real-world industrial problem. Various investigators developed several methods and semi-analytical tools for obtaining optimum solutions for this problem. In this study non-traditional optimization tool namely genetic algorithms GA are utilized. Apart from this Coxs regression analysis is also used to incorporate the effect of some environmental factors on the demand of spares. It shows the efficacy of the applicability of non-traditional optimization tool like GA to solve these problems. This research illustrates the proposed model with the analysis of data taken from a fleet of dumper operated in a large surface coal mine. The optimum time schedules so suggested by this GA-based model are found to be cost effective. A sensitivity analysis is also conducted for this industrial problem. Objective function is developed and the factors like the effect of season and production pressure overloading towards financial year-ending is included in the equations. Statistical analysis of the collected operational and performance data were carried out with the help of Easy-Fit Ver-5.5.The analysis gives the shape and scale parameter of theoretical Weibull distribution. The Coxs regression coefficient corresponding to excessive loading

  18. Quantitative Safety: Linking Proof-Based Verification with Model Checking for Probabilistic Systems

    CERN Document Server

    Ndukwu, Ukachukwu

    2009-01-01

    This paper presents a novel approach for augmenting proof-based verification with performance-style analysis of the kind employed in state-of-the-art model checking tools for probabilistic systems. Quantitative safety properties usually specified as probabilistic system invariants and modeled in proof-based environments are evaluated using bounded model checking techniques. Our specific contributions include the statement of a theorem that is central to model checking safety properties of proof-based systems, the establishment of a procedure; and its full implementation in a prototype system (YAGA) which readily transforms a probabilistic model specified in a proof-based environment to its equivalent verifiable PRISM model equipped with reward structures. The reward structures capture the exact interpretation of the probabilistic invariants and can reveal succinct information about the model during experimental investigations. Finally, we demonstrate the novelty of the technique on a probabilistic library cas...

  19. A review on mass spectrometry-based quantitative proteomics: Targeted and data independent acquisition.

    Science.gov (United States)

    Vidova, Veronika; Spacil, Zdenek

    2017-04-29

    Mass spectrometry (MS) based proteomics have achieved a near-complete proteome coverage in humans and in several other organisms, producing a wealth of information stored in databases and bioinformatics resources. Recent implementation of selected/multiple reaction monitoring (SRM/MRM) technology in targeted proteomics introduced the possibility of quantitatively follow-up specific protein targets in a hypothesis-driven experiment. In contrast to immunoaffinity-based workflows typically used in biological and clinical research for protein quantification, SRM/MRM is characterized by high selectivity, large capacity for multiplexing (approx. 200 proteins per analysis) and rapid, cost-effective transition from assay development to deployment. The concept of SRM/MRM utilizes triple quadrupole (QqQ) mass analyzer to provide inherent reproducibility, unparalleled sensitivity and selectivity to efficiently differentiate isoforms, post-translational modifications and mutated forms of proteins. SRM-like targeted acquisitions such as parallel reaction monitoring (PRM) are pioneered on high resolution/accurate mass (HR/AM) platforms based on the quadrupole-orbitrap (Q-orbitrap) mass spectrometer. The expansion of HR/AM also caused development in data independent acquisition (DIA). This review presents a step-by-step tutorial on development of SRM/MRM protein assay intended for researchers without prior experience in proteomics. We discus practical aspects of SRM-based quantitative proteomics workflow, summarize milestones in basic biological and medical research as well as recent trends and emerging techniques. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. A Statistical Framework for Protein Quantitation in Bottom-Up MS-Based Proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Karpievitch, Yuliya; Stanley, Jeffrey R.; Taverner, Thomas; Huang, Jianhua; Adkins, Joshua N.; Ansong, Charles; Heffron, Fred; Metz, Thomas O.; Qian, Weijun; Yoon, Hyunjin; Smith, Richard D.; Dabney, Alan R.

    2009-08-15

    Motivation: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate the methods. In simulation studies, our methods are shown to achieve sub