Behavior genetics: Bees as model

International Nuclear Information System (INIS)

Nates Parra, Guiomar

2011-01-01

The honeybee Apis mellifera (Apidae) is a model widely used in behavior because of its elaborate social life requiring coordinate actions among the members of the society. Within a colony, division of labor, the performance of tasks by different individuals, follows genetically determined physiological changes that go along with aging. Modern advances in tools of molecular biology and genomics, as well as the sequentiation of A. mellifera genome, have enabled a better understanding of honeybee behavior, in particular social behavior. Numerous studies show that aspects of worker behavior are genetically determined, including defensive, hygienic, reproductive and foraging behavior. For example, genetic diversity is associated with specialization to collect water, nectar and pollen. Also, control of worker reproduction is associated with genetic differences. In this paper, I review the methods and the main results from the study of the genetic and genomic basis of some behaviors in bees.

Authentic, Original, and Valuable

DEFF Research Database (Denmark)

Tupasela, Aaro Mikael; Tamminen, Sakari

2015-01-01

The idea of genetic authenticity and origin has been an important issue within genetics for decades for scientific, political, and economic reasons. The question of where species and populations come from, as well as the linking of genetic traits to particular geographical locations, has resurfaced....... Using the case of human and non-human genetics to compare and contrast the various facets associated with genetic identity, we seek to develop a broader picture of the ways in which genetics plays an important role in stabilizing categories of origin....

Challenging and valuable

NARCIS (Netherlands)

Van Hal, J.D.M.

2008-01-01

Challenging and valuable Inaugural speech given on May 7th 2008 at the occasion of the acceptance of the position of Professor Sustainable Housing Transformation at the faculty of Architeeture of the Delft University of Technology by Prof. J.D.M. van Hal MSc PhD.

Testing the Structure of Hydrological Models using Genetic Programming

Science.gov (United States)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Recovery and utilization of valuable metals from spent nuclear fuel. 3: Mutual separation of valuable metals

International Nuclear Information System (INIS)

Kirishima, K.; Shibayama, H.; Nakahira, H.; Shimauchi, H.; Myochin, M.; Wada, Y.; Kawase, K.; Kishimoto, Y.

1993-01-01

In the project ''Recovery and Utilization of Valuable Metals from Spent Fuel,'' mutual separation process of valuable metals recovered from spent fuel has been studied by using the simulated solution contained Pb, Ru, Rh, Pd and Mo. Pd was separated successfully by DHS (di-hexyl sulfide) solvent extraction method, while Pb was recovered selectively from the raffinate by neutralization precipitation of other elements. On the other hand, Rh was roughly separated by washing the precipitate with alkaline solution, so that Rh was refined by chelate resin CS-346. Outline of the mutual separation process flow sheet has been established of the combination of these techniques. The experimental results and the process flow sheet of mutual separation of valuable metals are presented in this paper

'HoneySweet' plum - a valuable genetically engineered fruit-tree cultivar and germplasm resource

Science.gov (United States)

‘HoneySweet’ is a plum variety developed through genetic engineering to be highly resistant to plum pox potyvirus (PPV), the causal agent of sharka disease, that threatens stone-fruit industries world-wide and most specifically, in Europe. Field testing for over 15 years in Europe has demonstrated ...

Introduction to genetic algorithms as a modeling tool

International Nuclear Information System (INIS)

Wildberger, A.M.; Hickok, K.A.

1990-01-01

Genetic algorithms are search and classification techniques modeled on natural adaptive systems. This is an introduction to their use as a modeling tool with emphasis on prospects for their application in the power industry. It is intended to provide enough background information for its audience to begin to follow technical developments in genetic algorithms and to recognize those which might impact on electric power engineering. Beginning with a discussion of genetic algorithms and their origin as a model of biological adaptation, their advantages and disadvantages are described in comparison with other modeling tools such as simulation and neural networks in order to provide guidance in selecting appropriate applications. In particular, their use is described for improving expert systems from actual data and they are suggested as an aid in building mathematical models. Using the Thermal Performance Advisor as an example, it is suggested how genetic algorithms might be used to make a conventional expert system and mathematical model of a power plant adapt automatically to changes in the plant's characteristics

Comparing estimates of genetic variance across different relationship models.

Science.gov (United States)

Legarra, Andres

2016-02-01

Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

Field Trips as Valuable Learning Experiences in Geography Courses

Science.gov (United States)

Krakowka, Amy Richmond

2012-01-01

Field trips have been acknowledged as valuable learning experiences in geography. This article uses Kolb's (1984) experiential learning model to discuss how students learn and how field trips can help enhance learning. Using Kolb's experiential learning theory as a guide in the design of field trips helps ensure that field trips contribute to…

Testing the structure of a hydrological model using Genetic Programming

Science.gov (United States)

Selle, Benny; Muttil, Nitin

2011-01-01

SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

Science.gov (United States)

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Fischer 344 and Lewis rat strains as a model of genetic vulnerability to drug addiction

Directory of Open Access Journals (Sweden)

Cristina eCadoni

2016-02-01

Full Text Available Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60 % of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis to differences in mesolimbic dopamine (DA transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neurons functionality.Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigations, results from the reviewed studies might open new vistas in

Fischer 344 and Lewis Rat Strains as a Model of Genetic Vulnerability to Drug Addiction.

Science.gov (United States)

Cadoni, Cristina

2016-01-01

Today it is well acknowledged that both nature and nurture play important roles in the genesis of psychopathologies, including drug addiction. Increasing evidence suggests that genetic factors contribute for at least 40-60% of the variation in liability to drug dependence. Human genetic studies suggest that multiple genes of small effect, rather than single genes, contribute to the genesis of behavioral psychopathologies. Therefore, the use of inbred rat strains might provide a valuable tool to identify differences, linked to genotype, important in liability to addiction and related disorders. In this regard, Lewis and Fischer 344 inbred rats have been proposed as a model of genetic vulnerability to drug addiction, given their innate differences in sensitivity to the reinforcing and rewarding effects of drugs of abuse, as well their different responsiveness to stressful stimuli. This review will provide evidence in support of this model for the study of the genetic influence on addiction vulnerability, with particular emphasis on differences in mesolimbic dopamine (DA) transmission, rewarding and emotional function. It will be highlighted that Lewis and Fischer 344 rats differ not only in several indices of DA transmission and adaptive changes following repeated drug exposure, but also in hypothalamic-pituitary-adrenal (HPA) axis responsiveness, influencing not only the ability of the individual to cope with stressful events, but also interfering with rewarding and motivational processes, given the influence of corticosteroids on dopamine neuron functionality. Further differences between the two strains, as impulsivity or anxiousness, might contribute to their different proneness to addiction, and likely these features might be linked to their different DA neurotransmission plasticity. Although differences in other neurotransmitter systems might deserve further investigation, results from the reviewed studies might open new vistas in understanding aberrant

Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

Science.gov (United States)

Dechow, C D; Rogers, G W

2018-05-01

Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetic and non-genetic animal models for autism spectrum disorders (ASD).

Science.gov (United States)

Ergaz, Zivanit; Weinstein-Fudim, Liza; Ornoy, Asher

2016-09-01

Autism spectrum disorder (ASD) is associated, in addition to complex genetic factors, with a variety of prenatal, perinatal and postnatal etiologies. We discuss the known animal models, mostly in mice and rats, of ASD that helps us to understand the etiology, pathogenesis and treatment of human ASD. We describe only models where behavioral testing has shown autistic like behaviors. Some genetic models mimic known human syndromes like fragile X where ASD is part of the clinical picture, and others are without defined human syndromes. Among the environmentally induced ASD models in rodents, the most common model is the one induced by valproic acid (VPA) either prenatally or early postnatally. VPA induces autism-like behaviors following single exposure during different phases of brain development, implying that the mechanism of action is via a general biological mechanism like epigenetic changes. Maternal infection and inflammation are also associated with ASD in man and animal models. Copyright © 2016 Elsevier Inc. All rights reserved.

Developing robotic behavior using a genetic programming model

International Nuclear Information System (INIS)

Pryor, R.J.

1998-01-01

This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

Science.gov (United States)

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; Hudziak, James J; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2013-09-01

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Beyond genetics. Influence of dietary factors and gut microbiota on type 1 diabetes

DEFF Research Database (Denmark)

Nielsen, Dennis Sandris; Krych, Lukasz; Buschard, Karsten

2014-01-01

Type 1 diabetes (T1D) is an autoimmune disease ultimately leading to destruction of insulin secreting β-cells in the pancreas. Genetic susceptibility plays an important role in T1D etiology, but even mono-zygotic twins only have a concordance rate of around 50%, underlining that other factors than...... purely genetic are involved in disease development. Here we review the influence of dietary and environmental factors on T1D development in humans as well as animal models. Even though data are still inconclusive, there are strong indications that gut microbiota dysbiosis plays an important role in T1D...... development and evidence from animal models suggests that gut microbiota manipulation might prove valuable in future prevention of T1D in genetically susceptible individuals....

CMCpy: Genetic Code-Message Coevolution Models in Python

Science.gov (United States)

Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

2013-01-01

Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

Evolutionary genetics: the Drosophila model

Indian Academy of Sciences (India)

Unknown

Evolutionary genetics straddles the two fundamental processes of life, ... of the genus Drosophila have been used extensively as model systems in experimental ... issue will prove interesting, informative and thought-provoking for both estab-.

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2014-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

DEFF Research Database (Denmark)

Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

2013-01-01

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

[The emphases and basic procedures of genetic counseling in psychotherapeutic model].

Science.gov (United States)

Zhang, Yuan-Zhi; Zhong, Nanbert

2006-11-01

The emphases and basic procedures of genetic counseling are all different with those in old models. In the psychotherapeutic model, genetic counseling will not only focus on counselees' genetic disorders and birth defects, but also their psychological problems. "Client-centered therapy" termed by Carl Rogers plays an important role in genetic counseling process. The basic procedures of psychotherapeutic model of genetic counseling include 7 steps: initial contact, introduction, agendas, inquiry of family history, presenting information, closing the session and follow-up.

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication

Directory of Open Access Journals (Sweden)

Madsen Per

2007-07-01

Full Text Available Abstract In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

Population genetics of Setaria viridis, a new model system.

Science.gov (United States)

Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

2014-10-01

An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. © 2014 John Wiley & Sons Ltd.

The historical role of species from the Solanaceae plant family in genetic research.

Science.gov (United States)

Gebhardt, Christiane

2016-12-01

This article evaluates the main contributions of tomato, tobacco, petunia, potato, pepper and eggplant to classical and molecular plant genetics and genomics since the beginning of the twentieth century. Species from the Solanaceae family form integral parts of human civilizations as food sources and drugs since thousands of years, and, more recently, as ornamentals. Some Solanaceous species were subjects of classical and molecular genetic research over the last 100 years. The tomato was one of the principal models in twentieth century classical genetics and a pacemaker of genome analysis in plants including molecular linkage maps, positional cloning of disease resistance genes and quantitative trait loci (QTL). Besides that, tomato is the model for the genetics of fruit development and composition. Tobacco was the major model used to establish the principals and methods of plant somatic cell genetics including in vitro propagation of cells and tissues, totipotency of somatic cells, doubled haploid production and genetic transformation. Petunia was a model for elucidating the biochemical and genetic basis of flower color and development. The cultivated potato is the economically most important Solanaceous plant and ranks third after wheat and rice as one of the world's great food crops. Potato is the model for studying the genetic basis of tuber development. Molecular genetics and genomics of potato, in particular association genetics, made valuable contributions to the genetic dissection of complex agronomic traits and the development of diagnostic markers for breeding applications. Pepper and eggplant are horticultural crops of worldwide relevance. Genetic and genomic research in pepper and eggplant mostly followed the tomato model. Comparative genome analysis of tomato, potato, pepper and eggplant contributed to the understanding of plant genome evolution.

Shaping asteroid models using genetic evolution (SAGE)

Science.gov (United States)

Bartczak, P.; Dudziński, G.

2018-02-01

In this work, we present SAGE (shaping asteroid models using genetic evolution), an asteroid modelling algorithm based solely on photometric lightcurve data. It produces non-convex shapes, orientations of the rotation axes and rotational periods of asteroids. The main concept behind a genetic evolution algorithm is to produce random populations of shapes and spin-axis orientations by mutating a seed shape and iterating the process until it converges to a stable global minimum. We tested SAGE on five artificial shapes. We also modelled asteroids 433 Eros and 9 Metis, since ground truth observations for them exist, allowing us to validate the models. We compared the derived shape of Eros with the NEAR Shoemaker model and that of Metis with adaptive optics and stellar occultation observations since other models from various inversion methods were available for Metis.

Genetic parameters of calving ease using sire-maternal grandsire model in Korean Holsteins

Directory of Open Access Journals (Sweden)

Mahboob Alam

2017-09-01

Full Text Available Objective Calving ease (CE is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea. Methods A total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo, gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE and daughter calving ease (DCE evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving. A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5 and 100% (CE1. A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package. Results The estimated direct heritability (h2 from SCE and DCE evaluations were 0.11±0.01 and 0.08±0.01, respectively. Maternal h2 estimates were 0.05±0.02 and 0.04±0.01 from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were −0.68±0.09 (SCE and −0.71±0.09 (DCE. The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA was desirable and increasing over time, but the maternal PTA was undesirable and decreasing. Conclusion The evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of

Numeral eddy current sensor modelling based on genetic neural network

International Nuclear Information System (INIS)

Yu Along

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

Genetic demographic networks: Mathematical model and applications.

Science.gov (United States)

Kimmel, Marek; Wojdyła, Tomasz

2016-10-01

Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise

Hierarchical linear modeling of longitudinal pedigree data for genetic association analysis

DEFF Research Database (Denmark)

Tan, Qihua; B Hjelmborg, Jacob V; Thomassen, Mads

2014-01-01

-effect models to explicitly model the genetic relationship. These have proved to be an efficient way of dealing with sample clustering in pedigree data. Although current algorithms implemented in popular statistical packages are useful for adjusting relatedness in the mixed modeling of genetic effects...... associated with blood pressure with estimated inflation factors of 0.99, suggesting that our modeling of random effects efficiently handles the genetic relatedness in pedigrees. Application to simulated data captures important variants specified in the simulation. Our results show that the method is useful......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees, which could affect statistical assessment of the genetic effects. Approaches have been proposed to integrate kinship correlation into the mixed...

Genetic screens in Caenorhabditis elegans models for neurodegenerative diseases

NARCIS (Netherlands)

Alvarenga Fernandes Sin, Olga; Michels, Helen; Nollen, Ellen A. A.

2014-01-01

Caenorhabditis elegans comprises unique features that make it an attractive model organism in diverse fields of biology. Genetic screens are powerful to identify genes and C. elegans can be customized to forward or reverse genetic screens and to establish gene function. These genetic screens can be

Genetic testing in congenital heart disease:A clinical approach

Institute of Scientific and Technical Information of China (English)

Marie A Chaix; Gregor Andelfinger; Paul Khairy

2016-01-01

Congenital heart disease(CHD) is the most common type of birth defect. Traditionally, a polygenic model defined by the interaction of multiple genes and environmental factors was hypothesized to account for different forms of CHD. It is now understood that the contribution of genetics to CHD extends beyond a single unified paradigm. For example, monogenic models and chromosomal abnormalities have been associated with various syndromic and non-syndromic forms of CHD. In such instances, genetic investigation and testing may potentially play an important role in clinical care. A family tree with a detailed phenotypic description serves as the initial screening tool to identify potentially inherited defects and to guide further genetic investigation. The selection of a genetic test is contingent upon the particular diagnostic hypothesis generated by clinical examination. Genetic investigation in CHD may carry the potential to improve prognosis by yielding valuable information with regards to personalized medical care, confidence in the clinical diagnosis, and/or targeted patient followup. Moreover, genetic assessment may serve as a tool to predict recurrence risk, define the pattern of inheritance within a family, and evaluate the need for further family screening. In some circumstances, prenatal or preimplantation genetic screening could identify fetuses or embryos at high risk for CHD. Although genetics may appear to constitute a highly specialized sector of cardiology, basic knowledge regarding inheritance patterns, recurrence risks, and available screening and diagnostic tools, including their strengths and limitations, could assist the treating physician in providing sound counsel.

Animal models for human genetic diseases | Sharif | African Journal ...

African Journals Online (AJOL)

The study of human genetic diseases can be greatly aided by animal models because of their similarity to humans in terms of genetics. In addition to understand diverse aspects of basic biology, model organisms are extensively used in applied research in agriculture, industry, and also in medicine, where they are used to ...

Genetic basis of type 2 diabetes mellitus: implications for therapy

DEFF Research Database (Denmark)

Wolford, Johanna K; de Courten, Barbora

2004-01-01

influenced by the relatively recent changes in diet and physical activity levels. There is also strong evidence supporting a genetic component to type 2 diabetes susceptibility and several genes underlying monogenic forms of diabetes have already been identified. However, common type 2 diabetes is likely...... and in the responsiveness to pharmacologic therapies, identification and characterization of the genetic variants underlying type 2 diabetes susceptibility will be important in the development of individualized treatment. Findings from linkage analyses, candidate gene studies, and animal models will be valuable...... in the identification of novel pathways involved in the regulation of glucose homeostasis, and will augment our understanding of the gene-gene and gene-environment interactions, which impact on type 2 diabetes etiology and pathogenesis. In addition, identification of genetic variants that determine differences...

Vulnerability of particularly valuable areas. Summary

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-07-01

This report is part of the scientific basis for the management plan for the North Sea and Skagerrak. The report focuses on the vulnerability of particularly valuable areas to petroleum activities, maritime transport, fisheries, land-based and coastal activities and long-range transboundary pollution. A working group with representatives from many different government agencies, headed by the Institute of Marine Research and the Directorate for Nature Management, has been responsible for drawing up the present report on behalf of the Expert Group for the North Sea and Skagerrak. The present report considers the 12 areas that were identified as particularly valuable during an earlier stage of the management plan process on the environment, natural resources and pollution. There are nine areas along the coast and three open sea areas in the North Sea that were identified according to the same predefined criteria as used for the management plans for the Barents Sea: Lofoten area and the Norwegian Sea. The most important criteria for particularly valuable areas are importance for biological production and importance for biodiversity.(Author)

Vulnerability of particularly valuable areas. Summary

International Nuclear Information System (INIS)

2012-01-01

This report is part of the scientific basis for the management plan for the North Sea and Skagerrak. The report focuses on the vulnerability of particularly valuable areas to petroleum activities, maritime transport, fisheries, land-based and coastal activities and long-range transboundary pollution. A working group with representatives from many different government agencies, headed by the Institute of Marine Research and the Directorate for Nature Management, has been responsible for drawing up the present report on behalf of the Expert Group for the North Sea and Skagerrak. The present report considers the 12 areas that were identified as particularly valuable during an earlier stage of the management plan process on the environment, natural resources and pollution. There are nine areas along the coast and three open sea areas in the North Sea that were identified according to the same predefined criteria as used for the management plans for the Barents Sea: Lofoten area and the Norwegian Sea. The most important criteria for particularly valuable areas are importance for biological production and importance for biodiversity.(Author)

Modelling the co-evolution of indirect genetic effects and inherited variability.

Science.gov (United States)

Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

2018-03-28

When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of

ENU mutagenesis to generate genetically modified rat models.

Science.gov (United States)

van Boxtel, Ruben; Gould, Michael N; Cuppen, Edwin; Smits, Bart M G

2010-01-01

The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach for generating genetically modified rats has been the target-selected N-ethyl-N-nitrosourea (ENU) mutagenesis-based technology. Here, we describe the detailed protocols for ENU mutagenesis and mutant retrieval in the rat model organism.

Heterozygous CDKL5 Knockout Female Mice Are a Valuable Animal Model for CDKL5 Disorder

Directory of Open Access Journals (Sweden)

Claudia Fuchs

2018-01-01

Full Text Available CDKL5 disorder is a severe neurodevelopmental disorder caused by mutations in the X-linked CDKL5 (cyclin-dependent kinase-like five gene. CDKL5 disorder primarily affects girls and is characterized by early-onset epileptic seizures, gross motor impairment, intellectual disability, and autistic features. Although all CDKL5 female patients are heterozygous, the most valid disease-related model, the heterozygous female Cdkl5 knockout (Cdkl5 +/− mouse, has been little characterized. The lack of detailed behavioral profiling of this model remains a crucial gap that must be addressed in order to advance preclinical studies. Here, we provide a behavioral and molecular characterization of heterozygous Cdkl5 +/− mice. We found that Cdkl5 +/− mice reliably recapitulate several aspects of CDKL5 disorder, including autistic-like behaviors, defects in motor coordination and memory performance, and breathing abnormalities. These defects are associated with neuroanatomical alterations, such as reduced dendritic arborization and spine density of hippocampal neurons. Interestingly, Cdkl5 +/− mice show age-related alterations in protein kinase B (AKT and extracellular signal-regulated kinase (ERK signaling, two crucial signaling pathways involved in many neurodevelopmental processes. In conclusion, our study provides a comprehensive overview of neurobehavioral phenotypes of heterozygous female Cdkl5 +/− mice and demonstrates that the heterozygous female might be a valuable animal model in preclinical studies on CDKL5 disorder.

Teaching Genetic Counseling Skills: Incorporating a Genetic Counseling Adaptation Continuum Model to Address Psychosocial Complexity.

Science.gov (United States)

Shugar, Andrea

2017-04-01

Genetic counselors are trained health care professionals who effectively integrate both psychosocial counseling and information-giving into their practice. Preparing genetic counseling students for clinical practice is a challenging task, particularly when helping them develop effective and active counseling skills. Resistance to incorporating these skills may stem from decreased confidence, fear of causing harm or a lack of clarity of psycho-social goals. The author reflects on the personal challenges experienced in teaching genetic counselling students to work with psychological and social complexity, and proposes a Genetic Counseling Adaptation Continuum model and methodology to guide students in the use of advanced counseling skills.

THE ALLOMETRIC-AUTOREGRESSIVE MODEL IN GENETIC ...

African Journals Online (AJOL)

The application of an allometric-autoregressive model for the quantification of growth and efficiency of feed utilization for purposes of selection for ... be of value in genetic studies. ... mass) gives a fair indication of the cumulative preweaning.

Animal models for human genetic diseases

African Journals Online (AJOL)

Sharif Sons

The study of human genetic diseases can be greatly aided by animal models because of their similarity .... and gene targeting in embryonic stem cells) has been a powerful tool in .... endonucleases that are designed to make a doublestrand.

Genetic testing in congenital heart disease: A clinical approach

Science.gov (United States)

Chaix, Marie A; Andelfinger, Gregor; Khairy, Paul

2016-01-01

Congenital heart disease (CHD) is the most common type of birth defect. Traditionally, a polygenic model defined by the interaction of multiple genes and environmental factors was hypothesized to account for different forms of CHD. It is now understood that the contribution of genetics to CHD extends beyond a single unified paradigm. For example, monogenic models and chromosomal abnormalities have been associated with various syndromic and non-syndromic forms of CHD. In such instances, genetic investigation and testing may potentially play an important role in clinical care. A family tree with a detailed phenotypic description serves as the initial screening tool to identify potentially inherited defects and to guide further genetic investigation. The selection of a genetic test is contingent upon the particular diagnostic hypothesis generated by clinical examination. Genetic investigation in CHD may carry the potential to improve prognosis by yielding valuable information with regards to personalized medical care, confidence in the clinical diagnosis, and/or targeted patient follow-up. Moreover, genetic assessment may serve as a tool to predict recurrence risk, define the pattern of inheritance within a family, and evaluate the need for further family screening. In some circumstances, prenatal or preimplantation genetic screening could identify fetuses or embryos at high risk for CHD. Although genetics may appear to constitute a highly specialized sector of cardiology, basic knowledge regarding inheritance patterns, recurrence risks, and available screening and diagnostic tools, including their strengths and limitations, could assist the treating physician in providing sound counsel. PMID:26981213

Recovering valuable shale oils, etc

Energy Technology Data Exchange (ETDEWEB)

Engler, C

1922-09-26

A process is described for the recovery of valuable shale oils or tars, characterized in that the oil shale is heated to about 300/sup 0/C or a temperature not exceeding this essentially and then is treated with a solvent with utilization of this heat.

Neuregulin 1: a prime candidate for research into gene-environment interactions in schizophrenia? Insights from genetic rodent models

Directory of Open Access Journals (Sweden)

Tim eKarl

2013-08-01

Full Text Available Schizophrenia is a multi-factorial disease characterized by a high heritability and environmental risk factors. In recent years, an increasing number of researchers worldwide have started investigating the ‘two-hit hypothesis’ of schizophrenia predicting that genetic and environmental risk factors (GxE interactively cause the development of the disorder. This work is starting to produce valuable new animal models and reveal novel insights into the pathophysiology of schizophrenia. This mini review will focus on recent advancements in the field made by challenging mutant and transgenic rodent models for the schizophrenia candidate gene neuregulin 1 (NRG1 with particular environmental factors. It will outline results obtained from mouse and rat models for various Nrg1 isoforms/isoform types (e.g. transmembrane domain Nrg1, Type II Nrg1, which have been exposed to different forms of stress (acute versus chronic, restraint versus social and housing conditions (standard laboratory versus minimally enriched housing. These studies suggest Nrg1 as a prime candidate for GxE interactions in schizophrenia rodent models and that the use of rodent models will enable a better understanding of GxE interactions and the underlying mechanisms.

Controversies in Cardiovascular Research: Induced pluripotent stem cell-derived cardiomyocytes – boutique science or valuable arrhythmia model?

Science.gov (United States)

Knollmann, Björn C

2013-01-01

As part of the series on Controversies in Cardiovascular Research, the article reviews the strengths and limitations of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) as models of cardiac arrhythmias. Specifically, the article attempts to answer the following questions: Which clinical arrhythmias can be modeled by iPSC-CM? How well can iPSC-CM model adult ventricular myocytes? What are the strengths and limitations of published iPSC-CM arrhythmia models? What new mechanistic insight has been gained? What is the evidence that would support using iPSC-CM to personalize anti-arrhythmic drug therapy? The review also discusses the pros and cons of using the iPSC-CM technology for modeling specific genetic arrhythmia disorders such as long QT syndrome, Brugada Syndrome or Catecholaminergic Polymorphic Ventricular Tachycardia. PMID:23569106

Alternate service delivery models in cancer genetic counseling: a mini-review

Directory of Open Access Journals (Sweden)

Adam Hudson Buchanan

2016-05-01

Full Text Available Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models such as telephone counseling, telegenetics and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

Estimation and interpretation of genetic effects with epistasis using the NOIA model.

Science.gov (United States)

Alvarez-Castro, José M; Carlborg, Orjan; Rönnegård, Lars

2012-01-01

We introduce this communication with a brief outline of the historical landmarks in genetic modeling, especially concerning epistasis. Then, we present methods for the use of genetic modeling in QTL analyses. In particular, we summarize the essential expressions of the natural and orthogonal interactions (NOIA) model of genetic effects. Our motivation for reviewing that theory here is twofold. First, this review presents a digest of the expressions for the application of the NOIA model, which are often mixed with intermediate and additional formulae in the original articles. Second, we make the required theory handy for the reader to relate the genetic concepts to the particular mathematical expressions underlying them. We illustrate those relations by providing graphical interpretations and a diagram summarizing the key features for applying genetic modeling with epistasis in comprehensive QTL analyses. Finally, we briefly review some examples of the application of NOIA to real data and the way it improves the interpretability of the results.

Genetic engineering in nonhuman primates for human disease modeling.

Science.gov (United States)

Sato, Kenya; Sasaki, Erika

2018-02-01

Nonhuman primate (NHP) experimental models have contributed greatly to human health research by assessing the safety and efficacy of newly developed drugs, due to their physiological and anatomical similarities to humans. To generate NHP disease models, drug-inducible methods, and surgical treatment methods have been employed. Recent developments in genetic and developmental engineering in NHPs offer new options for producing genetically modified disease models. Moreover, in recent years, genome-editing technology has emerged to further promote this trend and the generation of disease model NHPs has entered a new era. In this review, we summarize the generation of conventional disease model NHPs and discuss new solutions to the problem of mosaicism in genome-editing technology.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

Science.gov (United States)

Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan

2017-11-02

Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Adaptive genetic potential of coniferous forest tree species under climate change: implications for sustainable forest management

Science.gov (United States)

Mihai, Georgeta; Birsan, Marius-Victor; Teodosiu, Maria; Dumitrescu, Alexandru; Daia, Mihai; Mirancea, Ionel; Ivanov, Paula; Alin, Alexandru

2017-04-01

Mountain ecosystems are extremely vulnerable to climate change. The real potential for adaptation depends upon the existence of a wide genetic diversity in trees populations, upon the adaptive genetic variation, respectively. Genetic diversity offers the guarantee that forest species can survive, adapt and evolve under the influence of changing environmental conditions. The aim of this study is to evaluate the genetic diversity and adaptive genetic potential of two local species - Norway spruce and European silver fir - in the context of regional climate change. Based on data from a long-term provenance experiments network and climate variables spanning over more than 50 years, we have investigated the impact of climatic factors on growth performance and adaptation of tree species. Our results indicate that climatic and geographic factors significantly affect forest site productivity. Mean annual temperature and annual precipitation amount were found to be statistically significant explanatory variables. Combining the additive genetic model with the analysis of nuclear markers we obtained different images of the genetic structure of tree populations. As genetic indicators we used: gene frequencies, genetic diversity, genetic differentiation, genetic variance, plasticity. Spatial genetic analyses have allowed identifying the genetic centers holding high genetic diversity which will be valuable sources of gene able to buffer the negative effects of future climate change. Correlations between the marginal populations and in the optimal vegetation, between the level of genetic diversity and ecosystem stability, will allow the assessment of future risks arising from current genetic structure. Therefore, the strategies for sustainable forest management have to rely on the adaptive genetic variation and local adaptation of the valuable genetic resources. This work was realized within the framework of the project GENCLIM (Evaluating the adaptive potential of the main

Sleep and Development in Genetically Tractable Model Organisms.

Science.gov (United States)

Kayser, Matthew S; Biron, David

2016-05-01

Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. Copyright © 2016 by the Genetics Society of America.

A simple algorithm to estimate genetic variance in an animal threshold model using Bayesian inference Genetics Selection Evolution 2010, 42:29

DEFF Research Database (Denmark)

Ødegård, Jørgen; Meuwissen, Theo HE; Heringstad, Bjørg

2010-01-01

Background In the genetic analysis of binary traits with one observation per animal, animal threshold models frequently give biased heritability estimates. In some cases, this problem can be circumvented by fitting sire- or sire-dam models. However, these models are not appropriate in cases where...... records exist for the parents). Furthermore, the new algorithm showed much faster Markov chain mixing properties for genetic parameters (similar to the sire-dam model). Conclusions The new algorithm to estimate genetic parameters via Gibbs sampling solves the bias problems typically occurring in animal...... individual records exist on parents. Therefore, the aim of our study was to develop a new Gibbs sampling algorithm for a proper estimation of genetic (co)variance components within an animal threshold model framework. Methods In the proposed algorithm, individuals are classified as either "informative...

Potential uses of genetic geological modelling to identify new uranium provinces

International Nuclear Information System (INIS)

Finch, W.I.

1982-01-01

Genetic-geological modelling is the placing of the various processes of the development of a uranium province into distinct stages that are ordered chronologically and made part of a matrix with corresponding geologic evidence. The models can be applied to a given region by using one of several methods to determine a numerical favorability rating. Two of the possible methods, geologic decision analysis and an oil-and-gas type of play analysis, are briefly described. Simplified genetic models are given for environments of the quartz-pebble conglomerate, unconformity-related vein, and sandstone types of deposits. Comparison of the genetic models of these three sedimentary-related environments reveals several common attributes that may define a general uranium province environment

Phenomics, Genomics and Genetics in Plasmodium vinckei

KAUST Repository

Ramaprasad, Abhinay

2017-11-01

Rodent malaria parasites (RMPs) serve as tractable models for experimental genetics, and as valuable tools to study malaria parasite biology and host-parasitevector interactions. Plasmodium vinckei, one of four RMPs adapted to laboratory mice, is the most geographically widespread species and displays considerable phenotypic and genotypic diversity amongst its subspecies and strains. The phenotypes and genotypes of P. vinckei isolates have been relatively less characterized compared to other RMPs, hampering its use as an experimental model for malaria. Here, we have studied the phenotypes and sequenced the genomes and transcriptomes of ten P. vinckei isolates including representatives of all five subspecies, all of which were collected from wild thicket rats (Thamnomys rutilans) in sub-Saharan Central Africa between the late 1940s and mid 1960s. We have generated a comprehensive resource for P. vinckei comprising of five high-quality reference genomes, growth profiles and genotypes of P. vinckei isolates, and expression profiles of genes across the intra-erythrocytic developmental stages of the parasite. We observe significant phenotypic and genotypic diversity among P. vinckei isolates, making them particularly suitable for classical genetics and genomics-driven studies on malaria parasite biology. As part of a proof of concept study, we have shown that experimental genetic crosses can be performed between P. vinckei parasites to potentially identify genotype-phenotype relationships. We have also shown that they are amenable to genetic manipulation in the laboratory.

Characterization of PV panel and global optimization of its model parameters using genetic algorithm

International Nuclear Information System (INIS)

Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.

2013-01-01

Highlights: • Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model. • Effect of solar radiation and temperature variations was taken into account in fitness function evaluation. • We used Matlab-Simulink to simulate operation of the PV-panel to validate results. • Different cases were analyzed to ascertain which of them gives more accurate results. • Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated. - Abstract: This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer’s Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab–Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules

Semantic Document Image Classification Based on Valuable Text Pattern

Directory of Open Access Journals (Sweden)

Hossein Pourghassem

2011-01-01

Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

Portfolio optimization by using linear programing models based on genetic algorithm

Science.gov (United States)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

Valuable Internet Advertising and Customer Satisfaction Cycle(VIACSC)

OpenAIRE

Muhammad Awais; Tanzila Samin; Muhammad Bilal

2012-01-01

Now-a-days it is very important for the business persons to attract their target customers towards their products through valuable mode of promotion and communication. Increasing use of World Wide Web has completely changed the scenario of business sector. Customized products and services, customers preferences, @ and dot com craze have elevated the importance of internet advertising. This research paper investigates valuable internet advertising which will help to enhance the value of intern...

Two-level mixed modeling of longitudinal pedigree data for genetic association analysis

DEFF Research Database (Denmark)

Tan, Q.

2013-01-01

of follow-up. Approaches have been proposed to integrate kinship correlation into the mixed effect models to explicitly model the genetic relationship which have been proven as an efficient way for dealing with sample clustering in pedigree data. Although useful for adjusting relatedness in the mixed...... assess the genetic associations with the mean level and the rate of change in a phenotype both with kinship correlation integrated in the mixed effect models. We apply our method to longitudinal pedigree data to estimate the genetic effects on systolic blood pressure measured over time in large pedigrees......Genetic association analysis on complex phenotypes under a longitudinal design involving pedigrees encounters the problem of correlation within pedigrees which could affect statistical assessment of the genetic effects on both the mean level of the phenotype and its rate of change over the time...

Model comparisons and genetic and environmental parameter ...

African Journals Online (AJOL)

arc

Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.

Simulating pattern-process relationships to validate landscape genetic models

Science.gov (United States)

A. J. Shirk; S. A. Cushman; E. L. Landguth

2012-01-01

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all...

Characterization of a genetically engineered mouse model of hemophilia A with complete deletion of the F8 gene.

Science.gov (United States)

Chao, B N; Baldwin, W H; Healey, J F; Parker, E T; Shafer-Weaver, K; Cox, C; Jiang, P; Kanellopoulou, C; Lollar, P; Meeks, S L; Lenardo, M J

2016-02-01

ESSENTIALS: Anti-factor VIII (FVIII) inhibitory antibody formation is a severe complication in hemophilia A therapy. We genetically engineered and characterized a mouse model with complete deletion of the F8 coding region. F8(TKO) mice exhibit severe hemophilia, express no detectable F8 mRNA, and produce FVIII inhibitors. The defined background and lack of FVIII in F8(TKO) mice will aid in studying FVIII inhibitor formation. The most important complication in hemophilia A treatment is the development of inhibitory anti-Factor VIII (FVIII) antibodies in patients after FVIII therapy. Patients with severe hemophilia who express no endogenous FVIII (i.e. cross-reacting material, CRM) have the greatest incidence of inhibitor formation. However, current mouse models of severe hemophilia A produce low levels of truncated FVIII. The lack of a corresponding mouse model hampers the study of inhibitor formation in the complete absence of FVIII protein. We aimed to generate and characterize a novel mouse model of severe hemophilia A (designated the F8(TKO) strain) lacking the complete coding sequence of F8 and any FVIII CRM. Mice were created on a C57BL/6 background using Cre-Lox recombination and characterized using in vivo bleeding assays, measurement of FVIII activity by coagulation and chromogenic assays, and anti-FVIII antibody production using ELISA. All F8 exonic coding regions were deleted from the genome and no F8 mRNA was detected in F8(TKO) mice. The bleeding phenotype of F8(TKO) mice was comparable to E16 mice by measurements of factor activity and tail snip assay. Similar levels of anti-FVIII antibody titers after recombinant FVIII injections were observed between F8(TKO) and E16 mice. We describe a new C57BL/6 mouse model for severe hemophilia A patients lacking CRM. These mice can be directly bred to the many C57BL/6 strains of genetically engineered mice, which is valuable for studying the impact of a wide variety of genes on FVIII inhibitor formation on a

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

Science.gov (United States)

Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

Directory of Open Access Journals (Sweden)

Shiori Yabe

Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

Genetic variation and bottleneck in Japanese quail (Coturnix ...

African Journals Online (AJOL)

User

2011-05-16

May 16, 2011 ... The genetic structure of four strains of Japanese quail (Pharach, Panda, Tuxedo and Golden) was ... valuable laboratory species because of its small body ..... quail and cross-species amplification in chicken and guinea fowl.

Recovering valuable liquid hydrocarbons

Energy Technology Data Exchange (ETDEWEB)

Pier, M

1931-06-11

A process for recovering valuable liquid hydrocarbons from coking coal, mineral coal, or oil shale through treatment with hydrogen under pressure at elevated temperature is described. Catalysts and grinding oil may be used in the process if necessary. The process provides for deashing the coal prior to hydrogenation and for preventing the coking and swelling of the deashed material. During the treatment with hydrogen, the coal is either mixed with coal low in bituminous material, such as lean coal or active coal, as a diluent or the bituminous constituents which cause the coking and swelling are removed by extraction with solvents. (BLM)

PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

African Journals Online (AJOL)

Adel

This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

The genetic analysis of repeated measures I: Simplex models

NARCIS (Netherlands)

Molenaar, P.C.M.; Boomsma, D.I.

1987-01-01

Extends the simplex model to a model that may be used for the genetic and environmental analysis of covariance (ANCOVA) structures. This "double" simplex structure can be specified as a linear structural relationships model. It is shown that data that give rise to a simplex correlation structure,

Ravens reconcile after aggressive conflicts with valuable partners.

Science.gov (United States)

Fraser, Orlaith N; Bugnyar, Thomas

2011-03-25

Reconciliation, a post-conflict affiliative interaction between former opponents, is an important mechanism for reducing the costs of aggressive conflict in primates and some other mammals as it may repair the opponents' relationship and reduce post-conflict distress. Opponents who share a valuable relationship are expected to be more likely to reconcile as for such partners the benefits of relationship repair should outweigh the risk of renewed aggression. In birds, however, post-conflict behavior has thus far been marked by an apparent absence of reconciliation, suggested to result either from differing avian and mammalian strategies or because birds may not share valuable relationships with partners with whom they engage in aggressive conflict. Here, we demonstrate the occurrence of reconciliation in a group of captive subadult ravens (Corvus corax) and show that it is more likely to occur after conflicts between partners who share a valuable relationship. Furthermore, former opponents were less likely to engage in renewed aggression following reconciliation, suggesting that reconciliation repairs damage caused to their relationship by the preceding conflict. Our findings suggest not only that primate-like valuable relationships exist outside the pair bond in birds, but that such partners may employ the same mechanisms in birds as in primates to ensure that the benefits afforded by their relationships are maintained even when conflicts of interest escalate into aggression. These results provide further support for a convergent evolution of social strategies in avian and mammalian species.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models.

Science.gov (United States)

Moran, Paula; Stokes, Jennifer; Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John; O'Tuathaigh, Colm

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

Science.gov (United States)

Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

Genetic demixing and evolution in linear stepping stone models

Science.gov (United States)

Korolev, K. S.; Avlund, Mikkel; Hallatschek, Oskar; Nelson, David R.

2010-04-01

Results for mutation, selection, genetic drift, and migration in a one-dimensional continuous population are reviewed and extended. The population is described by a continuous limit of the stepping stone model, which leads to the stochastic Fisher-Kolmogorov-Petrovsky-Piscounov equation with additional terms describing mutations. Although the stepping stone model was first proposed for population genetics, it is closely related to “voter models” of interest in nonequilibrium statistical mechanics. The stepping stone model can also be regarded as an approximation to the dynamics of a thin layer of actively growing pioneers at the frontier of a colony of micro-organisms undergoing a range expansion on a Petri dish. The population tends to segregate into monoallelic domains. This segregation slows down genetic drift and selection because these two evolutionary forces can only act at the boundaries between the domains; the effects of mutation, however, are not significantly affected by the segregation. Although fixation in the neutral well-mixed (or “zero-dimensional”) model occurs exponentially in time, it occurs only algebraically fast in the one-dimensional model. An unusual sublinear increase is also found in the variance of the spatially averaged allele frequency with time. If selection is weak, selective sweeps occur exponentially fast in both well-mixed and one-dimensional populations, but the time constants are different. The relatively unexplored problem of evolutionary dynamics at the edge of an expanding circular colony is studied as well. Also reviewed are how the observed patterns of genetic diversity can be used for statistical inference and the differences are highlighted between the well-mixed and one-dimensional models. Although the focus is on two alleles or variants, q -allele Potts-like models of gene segregation are considered as well. Most of the analytical results are checked with simulations and could be tested against recent spatial

Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

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Wafa Abdelmalek

2009-01-01

Full Text Available The volatility is a crucial variable in option pricing and hedging strategies. The aim of this paper is to provide some initial evidence of the empirical relevance of genetic programming to volatility's forecasting. By using real data from S&P500 index options, the genetic programming's ability to forecast Black and Scholes-implied volatility is compared between time series samples and moneyness-time to maturity classes. Total and out-of-sample mean squared errors are used as forecasting's performance measures. Comparisons reveal that the time series model seems to be more accurate in forecasting-implied volatility than moneyness time to maturity models. Overall, results are strongly encouraging and suggest that the genetic programming approach works well in solving financial problems.

Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma) in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

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Sánchez-de la Vega, Guillermo; Castellanos-Morales, Gabriela; Gámez, Niza; Hernández-Rosales, Helena S.; Vázquez-Lobo, Alejandra; Aguirre-Planter, Erika; Jaramillo-Correa, Juan P.; Montes-Hernández, Salvador; Lira-Saade, Rafael; Eguiarte, Luis E.

2018-01-01

Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene

Genetic Resources in the “Calabaza Pipiana” Squash (Cucurbita argyrosperma in Mexico: Genetic Diversity, Genetic Differentiation and Distribution Models

Directory of Open Access Journals (Sweden)

Guillermo Sánchez-de la Vega

2018-03-01

Full Text Available Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma. Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango. We detected low

An animal model of differential genetic risk for methamphetamine intake

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Tamara ePhillips

2015-09-01

Full Text Available The question of whether genetic factors contribute to risk for methamphetamine (MA use and dependence has not been intensively investigated. Compared to human populations, genetic animal models offer the advantages of control over genetic family history and drug exposure. Using selective breeding, we created lines of mice that differ in genetic risk for voluntary MA intake and identified the chromosomal addresses of contributory genes. A quantitative trait locus was identified on chromosome 10 that accounts for more than 50% of the genetic variance in MA intake in the selected mouse lines. In addition, behavioral and physiological screening identified differences corresponding with risk for MA intake that have generated hypotheses that are testable in humans. Heightened sensitivity to aversive and certain physiological effects of MA, such as MA-induced reduction in body temperature, are hallmarks of mice bred for low MA intake. Furthermore, unlike MA-avoiding mice, MA-preferring mice are sensitive to rewarding and reinforcing MA effects, and to MA-induced increases in brain extracellular dopamine levels. Gene expression analyses implicate the importance of a network enriched in transcription factor genes, some of which regulate the mu opioid receptor gene, Oprm1, in risk for MA use. Neuroimmune factors appear to play a role in differential response to MA between the mice bred for high and low intake. In addition, chromosome 10 candidate gene studies provide strong support for a trace amine associated receptor 1 gene, Taar1, polymorphism in risk for MA intake. MA is a trace amine-associated receptor 1 (TAAR1 agonist, and a non-functional Taar1 allele segregates with high MA consumption. Thus, reduced TAAR1 function has the potential to increase risk for MA use. Overall, existing findings support the MA drinking lines as a powerful model for identifying genetic factors involved in determining risk for harmful MA use. Future directions include the

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

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Paula Moran

2016-01-01

Full Text Available The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Next generation DNA sequencing technology delivers valuable genetic markers for the genomic orphan legume species, Bituminaria bituminosa

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Pazos-Navarro María

2011-12-01

Full Text Available Abstract Background Bituminaria bituminosa is a perennial legume species from the Canary Islands and Mediterranean region that has potential as a drought-tolerant pasture species and as a source of pharmaceutical compounds. Three botanical varieties have previously been identified in this species: albomarginata, bituminosa and crassiuscula. B. bituminosa can be considered a genomic 'orphan' species with very few genomic resources available. New DNA sequencing technologies provide an opportunity to develop high quality molecular markers for such orphan species. Results 432,306 mRNA molecules were sampled from a leaf transcriptome of a single B. bituminosa plant using Roche 454 pyrosequencing, resulting in an average read length of 345 bp (149.1 Mbp in total. Sequences were assembled into 3,838 isotigs/contigs representing putatively unique gene transcripts. Gene ontology descriptors were identified for 3,419 sequences. Raw sequence reads containing simple sequence repeat (SSR motifs were identified, and 240 primer pairs flanking these motifs were designed. Of 87 primer pairs developed this way, 75 (86.2% successfully amplified primarily single fragments by PCR. Fragment analysis using 20 primer pairs in 79 accessions of B. bituminosa detected 130 alleles at 21 SSR loci. Genetic diversity analyses confirmed that variation at these SSR loci accurately reflected known taxonomic relationships in original collections of B. bituminosa and provided additional evidence that a division of the botanical variety bituminosa into two according to geographical origin (Mediterranean region and Canary Islands may be appropriate. Evidence of cross-pollination was also found between botanical varieties within a B. bituminosa breeding programme. Conclusions B. bituminosa can no longer be considered a genomic orphan species, having now a large (albeit incomplete repertoire of expressed gene sequences that can serve as a resource for future genetic studies. This

A Rational Model In Theoretical Genetics

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Karl Javorszky

2008-07-01

Full Text Available This model connects information processing in biological organisms with methods and concepts used in classical, technical information processing. The central concept shows copying and regulatory interaction between a logical sequence consisting of triplets and the amount of constituents of a set. The basic mathematical model of information processing within a biological cell has been worked out. The cell in the model copies its present state into a sequence and reads it off the sequence. The sequence comes in triplets and is not one sequence but appears in two almost identical varieties. We treat consecutive and contemporary assemblies of information carrying media as equally suited to contain information. Methods used so far utilised the consecutive property of media, while in biology one observes the concurrent existence of specific realisations of possibilities. Genetics connects the two approaches by using an interplay between consecutively (sequentially ordered logical markers (the DNA and the state of the set engulfing the DNA. Several mathematical tools have been evolved to assemble an interface between sequentially ordered carriers and the same number of carriers if they arrive contemporaneously. Using linguistic theory and formal logic one concludes that measurement(s on a cell are a (set of logical sentence(s relating to an assembly of n objects with group structures among each other. We linearise and count all possible group relations on a set of n objects and introduce the concept of multidimensional partitions hitherto left undefined. We introduce the concept of a maximally structured set by establishing an upper limit to the information carrying capacity of n objects used commutatively and sequentially at the same time (like genetics does. The copying and re-copying mechanism which is the core matter with genetics appears in the model as differing transmission efficiency coefficients of media if the media are used once sequentially

Genetic variability of Cordia alliodora (R. and P.) Oken progenies

International Nuclear Information System (INIS)

Marulanda, Marta Leonor; Lopez, Ana Maria; Uribe, Marcela; Ospina, Carlos Mario

2011-01-01

Cordia alliodora is a well-known wood producer tree of tropical areas of Latin America and the Caribbean characterized for producing valuable wood and by its fast growth rate. In Colombia, it is frequent on agro-forestall systems with coffee. This species, like most forest species have biological problems for genetic improvement programs, such as long regeneration periods and high costs for supporting a population in a long term. The molecular assisted markers in plant breeding programs have had a great impact on genetic improvement, due to the fact they minimize their intervals of regeneration, increase the genetic gain by generation and allow the evaluation of the genetic information essential for the species. In this work, 60 genotypes of C. alliodora were characterized, belonging to the provenance and progenies tests established by the program of genetic improvement of Cenicafe. The characterization was carried out through micro satellite markers, after developing a genomic library enriched with micro satellites of the species. Finally, 24 specific micro satellites were evaluated, 20 of which allowed the detection of 28 polymorphic and multiallelic loci. These results provide a guide for orienting the policies of sustainable production and conservation of this valuable species; also, it provides a useful tool for the identification of clones with commercial interest.

Genetics of traffic assignment models for strategic transport planning

NARCIS (Netherlands)

Bliemer, M.C.J.; Raadsen, M.P.H.; Brederode, L.J.N.; Bell, M.G.H.; Wismans, Luc Johannes Josephus; Smith, M.J.

2016-01-01

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

Science.gov (United States)

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In

Timing of gene expression from different genetic systems in shaping ...

Indian Academy of Sciences (India)

2011-12-16

Dec 16, 2011 ... different genetic systems, nutrition quality traits were mainly controlled by the accumulative or net ... pable of providing valuable information on the expression of ...... protein, carbohydrates, and dietary fiber components.

Applicability of genetic algorithms to parameter estimation of economic models

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Marcel Ševela

2004-01-01

Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.

Genetic algorithms and experimental discrimination of SUSY models

International Nuclear Information System (INIS)

Allanach, B.C.; Quevedo, F.; Grellscheid, D.

2004-01-01

We introduce genetic algorithms as a means to estimate the accuracy required to discriminate among different models using experimental observables. We exemplify the technique in the context of the minimal supersymmetric standard model. If supersymmetric particles are discovered, models of supersymmetry breaking will be fit to the observed spectrum and it is beneficial to ask beforehand: what accuracy is required to always allow the discrimination of two particular models and which are the most important masses to observe? Each model predicts a bounded patch in the space of observables once unknown parameters are scanned over. The questions can be answered by minimising a 'distance' measure between the two hypersurfaces. We construct a distance measure that scales like a constant fraction of an observable, since that is how the experimental errors are expected to scale. Genetic algorithms, including concepts such as natural selection, fitness and mutations, provide a solution to the minimisation problem. We illustrate the efficiency of the method by comparing three different classes of string models for which the above questions could not be answered with previous techniques. The required accuracy is in the range accessible to the Large Hadron Collider (LHC) when combined with a future linear collider (LC) facility. The technique presented here can be applied to more general classes of models or observables. (author)

Initial assessment of a model relating intratumoral genetic heterogeneity to radiological morphology

Science.gov (United States)

Noterdaeme, O; Kelly, M; Friend, P; Soonowalla, Z; Steers, G; Brady, M

2010-01-01

Tumour heterogeneity has major implications for tumour development and response to therapy. Tumour heterogeneity results from mutations in the genes responsible for mismatch repair or maintenance of chromosomal stability. Cells with different genetic properties may grow at different rates and exhibit different resistance to therapeutic interventions. To date, there exists no approach to non-invasively assess tumour heterogeneity. Here we present a biologically inspired model of tumour growth, which relates intratumoral genetic heterogeneity to gross morphology visible on radiological images. The model represents the development of a tumour as a set of expanding spheres, each sphere representing a distinct clonal centre, with the sprouting of new spheres corresponding to new clonal centres. Each clonal centre may possess different characteristics relating to genetic composition, growth rate and response to treatment. We present a clinical example for which the model accurately tracks tumour growth and shows the correspondence to genetic variation (as determined by array comparative genomic hybridisation). One clinical implication of our work is that the assessment of heterogeneous tumours using Response Evaluation Criteria In Solid Tumours (RECIST) or volume measurements may not accurately reflect tumour growth, stability or the response to treatment. We believe that this is the first model linking the macro-scale appearance of tumours to their genetic composition. We anticipate that our model will provide a more informative way to assess the response of heterogeneous tumours to treatment, which is of increasing importance with the development of novel targeted anti-cancer treatments. PMID:19690073

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

Science.gov (United States)

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Different concepts and models of information for family-relevant genetic findings: comparison and ethical analysis.

Science.gov (United States)

Lenk, Christian; Frommeld, Debora

2015-08-01

Genetic predispositions often concern not only individual persons, but also other family members. Advances in the development of genetic tests lead to a growing number of genetic diagnoses in medical practice and to an increasing importance of genetic counseling. In the present article, a number of ethical foundations and preconditions for this issue are discussed. Four different models for the handling of genetic information are presented and analyzed including a discussion of practical implications. The different models' ranges of content reach from a strictly autonomous position over self-governed arrangements in the practice of genetic counseling up to the involvement of official bodies and committees. The different models show a number of elements which seem to be very useful for the handling of genetic data in families from an ethical perspective. In contrast, the limitations of the standard medical attempt regarding confidentiality and personal autonomy in the context of genetic information in the family are described. Finally, recommendations for further ethical research and the development of genetic counseling in families are given.

Population genetics models of local ancestry.

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Gravel, Simon

2012-06-01

Migrations have played an important role in shaping the genetic diversity of human populations. Understanding genomic data thus requires careful modeling of historical gene flow. Here we consider the effect of relatively recent population structure and gene flow and interpret genomes of individuals that have ancestry from multiple source populations as mosaics of segments originating from each population. This article describes general and tractable models for local ancestry patterns with a focus on the length distribution of continuous ancestry tracts and the variance in total ancestry proportions among individuals. The models offer improved agreement with Wright-Fisher simulation data when compared to the state-of-the art and can be used to infer time-dependent migration rates from multiple populations. Considering HapMap African-American (ASW) data, we find that a model with two distinct phases of "European" gene flow significantly improves the modeling of both tract lengths and ancestry variances.

Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

International Nuclear Information System (INIS)

D'Ambrosio, D.; Spataro, W.; Di Gregorio, S.; Calabria Univ., Cosenza; Crisci, G.M.; Rongo, R.; Calabria Univ., Cosenza

2005-01-01

Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

Genetics and neuropsychology: A merger whose time has come.

Science.gov (United States)

Kremen, William S; Panizzon, Matthew S; Cannon, Tyrone D

2016-01-01

Genetics and neuropsychology have historically been 2 rather distant and unrelated fields. With the very rapid advances that have been taking place in genetics, research and treatment of disorders of cognition in the 21st century are likely to be increasingly informed by individual differences in genetics and epigenetics. Although neuropsychologists are not expected to become geneticists, it is our view that increased training in genetics should become more central to training in neuropsychology. This relationship should not be unidirectional. Here we note ways in which an understanding of genetics and epigenetics can inform neuropsychology. On the other hand, given the complexity of cognitive phenotypes, neuropsychology can also play a valuable role in informing and refining genetic studies. Greater integration of the 2 should advance both fields. (c) 2015 APA, all rights reserved).

Genetic Algorithm Based Microscale Vehicle Emissions Modelling

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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.

Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

Science.gov (United States)

Sastry, Kumara Narasimha

2007-03-01

Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

Model parameters estimation and sensitivity by genetic algorithms

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

2003-01-01

In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

[The discussion of the infiltrative model of mathematical knowledge to genetics teaching].

Science.gov (United States)

Liu, Jun; Luo, Pei-Gao

2011-11-01

Genetics, the core course of biological field, is an importance major-basic course in curriculum of many majors related with biology. Due to strong theoretical and practical as well as abstract of genetics, it is too difficult to study on genetics for many students. At the same time, mathematics is one of the basic courses in curriculum of the major related natural science, which has close relationship with the establishment, development and modification of genetics. In this paper, to establish the intrinsic logistic relationship and construct the integral knowledge network and to help students improving the analytic, comprehensive and logistic abilities, we applied some mathematical infiltrative model genetic knowledge in genetics teaching, which could help students more deeply learn and understand genetic knowledge.

Research on interactive genetic-geological models to evaluate favourability for undiscovered uranium resources

International Nuclear Information System (INIS)

Finch, W.I.; Granger, H.C.; Lupe, R.; McCammon, R.B.

1980-01-01

Current methods of evaluating favourability for undiscovered uranium resources are unduly subjective, quite possibly inconsistent and, as a consequence, of questionable reliability. This research is aimed at reducing the subjectivity and increasing the reliability by designing an improved method that depends largely on geological data and their statistical frequency of occurrence. This progress report outlines a genetic approach to modelling the geological factors that controlled uranium mineralization in order to evaluate the favourability for the occurrence of undiscovered uranium deposits of the type modelled. A genetic model is constructed from all the factors that describe the processes, in chronological sequence, that formed uranium deposits thought to have a common origin. The field and laboratory evidence for the processes constitute a geologic-occurrence base that parallels the chronological sequence of events. The genetic model and the geologic-occurrence base are portrayed as two columns of an interactive matrix called the ''genetic-geologic model''. For each column, eight chronological stages are used to describe the overall formation of the uranium deposits. These stages consist of (1) precursor processes; (2) host-rock formation; (3) preparation of host-rock; (4) uranium-source development; (5) transport of uranium; (6) primary uranium deposition; (7) post-deposition modification; and (8) preservation. To apply the genetic-geological model to evaluate favourability, a question is posed that determines the presence or absence of each attribute listed under the geologic-occurrence base. By building a logic circuit of the attributes according to either their essential or non-essential nature, the resultant match between a well-documented control area and the test area may be determined. The degree of match is a measure of favourability for uranium occurrence as hypothesized in the genetic model

Genetic Process Mining: Alignment-based Process Model Mutation

NARCIS (Netherlands)

Eck, van M.L.; Buijs, J.C.A.M.; Dongen, van B.F.; Fournier, F.; Mendling, J.

2015-01-01

The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses

Estimation in a multiplicative mixed model involving a genetic relationship matrix

Directory of Open Access Journals (Sweden)

Eccleston John A

2009-04-01

Full Text Available Abstract Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Genetic search feature selection for affective modeling

DEFF Research Database (Denmark)

Martínez, Héctor P.; Yannakakis, Georgios N.

2010-01-01

Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

Emerging technologies to create inducible and genetically defined porcine cancer models

Directory of Open Access Journals (Sweden)

Lawrence B Schook

2016-02-01

Full Text Available There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models.

Science.gov (United States)

Schook, Lawrence B; Rund, Laurie; Begnini, Karine R; Remião, Mariana H; Seixas, Fabiana K; Collares, Tiago

2016-01-01

There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

Quantitative genetics of Taura syndrome resistance in Pacific (Penaeus vannamei): A cure model approach

DEFF Research Database (Denmark)

Ødegård, Jørgen; Gitterle, Thomas; Madsen, Per

2011-01-01

cure survival model using Gibbs sampling, treating susceptibility and endurance as separate genetic traits. Results: Overall mortality at the end of test was 28%, while 38% of the population was considered susceptible to the disease. The estimated underlying heritability was high for susceptibility (0....... However, genetic evaluation of susceptibility based on the cure model showed clear associations with standard genetic evaluations that ignore the cure fraction for these data. Using the current testing design, genetic variation in observed survival time and absolute survival at the end of test were most...

Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

Science.gov (United States)

José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

2011-07-01

Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

Biomarkers of brain function in psychosis and their genetic basis

OpenAIRE

Ranlund, S. M.

2016-01-01

Psychotic disorders, including schizophrenia and bipolar disorder, are amongst the most severe and enduring mental illnesses. Recent research has identified several genetic variants associated with an increased risk of developing psychosis; however, it remains largely unknown how these lead to the illness. This is where endophenotypes – heritable traits associated with the illness and observed in unaffected family members of patients – could be valuable. Endophenotypes are linked to the genet...

Effective elimination of chimeric tissue in transgenics for the stable genetic transformation of lesquerella fendleri

Science.gov (United States)

In order to improve the potential of Lesquerella fendleri as a valuable industrial oilseed crop, a stable genetic transformation system was developed. Genetic transformation was performed by inoculating leaf segments with an Agrobacterium tumefaciens strain AGL1 carrying binary vector pCAMBIA 1301.1...

Muscle MRI in pediatrics: clinical, pathological and genetic correlation

Energy Technology Data Exchange (ETDEWEB)

Cejas, Claudia P.; Serra, Maria M.; Galvez, David F.G. [Foundation for Neurological Research Dr. Raul Carrea (FLENI), Radiology Department, Buenos Aires (Argentina); Cavassa, Eliana A.; Vazquez, Gabriel A.; Massaro, Mario E.L.; Schteinschneider, Angeles V. [Foundation for Neurological Research Dr. Raul Carrea (FLENI), Department of Neuropediatrics, Buenos Aires (Argentina); Taratuto, Ana L. [Foundation for Neurological Research Dr. Raul Carrea (FLENI), Neuropathology Consultant, Buenos Aires (Argentina)

2017-05-15

Pediatric myopathies comprise a very heterogeneous group of disorders that may develop at different ages and affect different muscle groups. Its diagnosis is sometimes difficult and must be confirmed by muscle biopsy and/or genetic analysis. In recent years, muscle involvement patterns observed on MRI have become a valuable tool, aiding clinical diagnosis and enriching pathological and genetic assessments. We selected eight myopathy cases from our institutional database in which the pattern of muscle involvement observed on MRI was almost pathognomonic and could therefore contribute to establishing diagnosis. Muscle biopsy, genetic diagnosis or both confirmed all cases. (orig.)

Muscle MRI in pediatrics: clinical, pathological and genetic correlation

International Nuclear Information System (INIS)

Cejas, Claudia P.; Serra, Maria M.; Galvez, David F.G.; Cavassa, Eliana A.; Vazquez, Gabriel A.; Massaro, Mario E.L.; Schteinschneider, Angeles V.; Taratuto, Ana L.

2017-01-01

Pediatric myopathies comprise a very heterogeneous group of disorders that may develop at different ages and affect different muscle groups. Its diagnosis is sometimes difficult and must be confirmed by muscle biopsy and/or genetic analysis. In recent years, muscle involvement patterns observed on MRI have become a valuable tool, aiding clinical diagnosis and enriching pathological and genetic assessments. We selected eight myopathy cases from our institutional database in which the pattern of muscle involvement observed on MRI was almost pathognomonic and could therefore contribute to establishing diagnosis. Muscle biopsy, genetic diagnosis or both confirmed all cases. (orig.)

Medulloblastoma: Molecular Genetics and Animal Models

Directory of Open Access Journals (Sweden)

Corey Raffel

2004-07-01

Full Text Available Medulloblastoma is a primary brain tumor found in the cerebellum of children. The tumor occurs in association with two inherited cancer syndromes: Turcot syndrome and Gorlin syndrome. Insights into the molecular biology of the tumor have come from looking at alterations in the genes altered in these syndromes, PTC and APC, respectively. Murine models of medulloblastoma have been constructed based on these alterations. Additional murine models that, while mimicking the appearance of the human tumor, seem unrelated to the human tumor's molecular alterations have been made. In this review, the clinical picture, origin, molecular biology, murine models of medulloblastoma are discussed. Although a great deal has been discovered about this tumor, the genetic alterations responsible for tumor development in a majority of patients have yet to be described.

A symbiotic liaison between the genetic and epigenetic code

Directory of Open Access Journals (Sweden)

Holger eHeyn

2014-05-01

Full Text Available With rapid advances in sequencing technologies, we are undergoing a paradigm shift from hypothesis- to data-driven research. Genome-wide profiling efforts gave informative insights into biological processes; however, considering the wealth of variation, the major challenge remains their meaningful interpretation. In particular sequence variation in non-coding contexts is often challenging to interpret. Here, data integration approaches for the identification of functional genetic variability represent a likely solution. Exemplary, functional linkage analysis integrating genotype and expression data determined regulatory quantitative trait loci (QTL and proposed causal relationships. In addition to gene expression, epigenetic regulation and specifically DNA methylation was established as highly valuable surrogate mark for functional variance of the genetic code. Epigenetic modification served as powerful mediator trait to elucidate mechanisms forming phenotypes in health and disease. Particularly, integrative studies of genetic and DNA methylation data yet guided interpretation strategies of risk genotypes, but also proved their value for physiological traits, such as natural human variation and aging. This Perspective seeks to illustrate the power of data integration in the genomic era exemplified by DNA methylation quantitative trait loci (meQTLs. However, the model is further extendable to virtually all traceable molecular traits.

Precise and in situ genetic humanization of 6 Mb of mouse immunoglobulin genes.

Science.gov (United States)

Macdonald, Lynn E; Karow, Margaret; Stevens, Sean; Auerbach, Wojtek; Poueymirou, William T; Yasenchak, Jason; Frendewey, David; Valenzuela, David M; Giallourakis, Cosmas C; Alt, Frederick W; Yancopoulos, George D; Murphy, Andrew J

2014-04-08

Genetic humanization, which involves replacing mouse genes with their human counterparts, can create powerful animal models for the study of human genes and diseases. One important example of genetic humanization involves mice humanized for their Ig genes, allowing for human antibody responses within a mouse background (HumAb mice) and also providing a valuable platform for the generation of fully human antibodies as therapeutics. However, existing HumAb mice do not have fully functional immune systems, perhaps because of the manner in which they were genetically humanized. Heretofore, most genetic humanizations have involved disruption of the endogenous mouse gene with simultaneous introduction of a human transgene at a new and random location (so-called KO-plus-transgenic humanization). More recent efforts have attempted to replace mouse genes with their human counterparts at the same genetic location (in situ humanization), but such efforts involved laborious procedures and were limited in size and precision. We describe a general and efficient method for very large, in situ, and precise genetic humanization using large compound bacterial artificial chromosome-based targeting vectors introduced into mouse ES cells. We applied this method to genetically humanize 3-Mb segments of both the mouse heavy and κ light chain Ig loci, by far the largest genetic humanizations ever described. This paper provides a detailed description of our genetic humanization approach, and the companion paper reports that the humoral immune systems of mice bearing these genetically humanized loci function as efficiently as those of WT mice.

Switchgrass a valuable biomass crop for energy

CERN Document Server

2012-01-01

The demand of renewable energies is growing steadily both from policy and from industry which seeks environmentally friendly feed stocks. The recent policies enacted by the EU, USA and other industrialized countries foresee an increased interest in the cultivation of energy crops; there is clear evidence that switchgrass is one of the most promising biomass crop for energy production and bio-based economy and compounds. Switchgrass: A Valuable Biomass Crop for Energy provides a comprehensive guide to  switchgrass in terms of agricultural practices, potential use and markets, and environmental and social benefits. Considering this potential energy source from its biology, breed and crop physiology to its growth and management to the economical, social and environmental impacts, Switchgrass: A Valuable Biomass Crop for Energy brings together chapters from a range of experts in the field, including a foreword from Kenneth P. Vogel, to collect and present the environmental benefits and characteristics of this a ...

Genetic models of absence epilepsy: New concepts and insights

NARCIS (Netherlands)

Luijtelaar, E.L.J.M. van; Coenen, A.M.L.; Schwartzkroin, P.A.

2009-01-01

The discovery, development, and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures. A focal zone has been identified in the peri-oral region of the somatosensory cortex in WAG/Rij and GAERS – the two most commonly used models – from which

Dynamic modeling of genetic networks using genetic algorithm and S-system.

Science.gov (United States)

Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

2003-03-22

The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

Science.gov (United States)

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle

Directory of Open Access Journals (Sweden)

C. I. Cho

2016-05-01

Full Text Available The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs, and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK, fat yield (FAT, protein yield (PROT, and solids-not-fat yield (SNF. The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP of the third to fifth order (L3–L5, fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order. The residual variances in the models were either homogeneous (HOM or heterogeneous (15 classes, HET15; 60 classes, HET60. A total of nine models (3 orders of polynomials×3 types of residual variance including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC and/or Schwarz Bayesian information criteria (BIC statistics to identify the model(s of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF and L4-HET15 (FAT, which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first

Valuable human capital: the aging health care worker.

Science.gov (United States)

Collins, Sandra K; Collins, Kevin S

2006-01-01

With the workforce growing older and the supply of younger workers diminishing, it is critical for health care managers to understand the factors necessary to capitalize on their vintage employees. Retaining this segment of the workforce has a multitude of benefits including the preservation of valuable intellectual capital, which is necessary to ensure that health care organizations maintain their competitive advantage in the consumer-driven market. Retaining the aging employee is possible if health care managers learn the motivators and training differences associated with this category of the workforce. These employees should be considered a valuable resource of human capital because without their extensive expertise, intense loyalty and work ethic, and superior customer service skills, health care organizations could suffer severe economic repercussions in the near future.

ENU mutagenesis to generate genetically modified rat models

NARCIS (Netherlands)

van Boxtel, R.; Gould, M.; Cuppen, E.; Smits, B.M.

2010-01-01

The rat is one of the most preferred model organisms in biomedical research and has been extremely useful for linking physiology and pathology to the genome. However, approaches to genetically modify specific genes in the rat germ line remain relatively scarce. To date, the most efficient approach

A review of animal models used to evaluate potential allergenicity of genetically modified organisms (GMOs)

DEFF Research Database (Denmark)

Marsteller, Nathan; Bøgh, Katrine Lindholm; Goodman, Richard E.

2017-01-01

Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...... of genetically modified organisms (GMOs).......Food safety regulators request prediction of allergenicity for newly expressed proteins in genetically modified (GM) crops and in novel foods. Some have suggested using animal models to assess potential allergenicity. A variety of animal models have been used in research to evaluate sensitisation...

Applications of Systems Genetics and Biology for Obesity Using Pig Models

DEFF Research Database (Denmark)

Kogelman, Lisette; Kadarmideen, Haja N.

2016-01-01

approach, a branch of systems biology. In this chapter, we will describe the state of the art of genetic studies on human obesity, using pig populations. We will describe the features of using the pig as a model for human obesity and briefly discuss the genetics of obesity, and we will focus on systems...

Energy threat to valuable land

International Nuclear Information System (INIS)

Caufield, C.

1982-01-01

Having considered the varying estimates of future UK energy requirements which have been made, the impact on the environment arising from the use of valuable sites for energy production is examined. It is shown that energy installations of all kinds clash with areas of natural beauty or ecological importance. As an example, a recent investigation of potential sites for nuclear power stations found that most of them were on or next to sites of special scientific interest, and other areas officially designated to be regarded as special or to be protected in some way. (U.K.)

Forecasting tourist arrivals to balearic islands using genetic programming

Directory of Open Access Journals (Sweden)

Rosselló-Nadal, Jaume

2007-01-01

Full Text Available Traditionally, univariate time-series models have largely dominated forecasting for international tourism demand. In this paper, the ability of a Genetic Program (GP to predict monthly tourist arrivals from UK and Germany to Balearic Islands (Spain is explored. GP has already been employed satisfactorily in different scientific areas, including economics. The technique shows different advantages regarding to other forecasting methods. Firstly, it does not assume a priori a rigid functional form of the model. Secondly, it is more robust and easy-to-use than other non-parametric methods. Finally, it provides explicitly a mathematical equation which allows a simple ad hoc interpretation of the results. Comparing the performance of the proposed technique against other method commonly used in tourism forecasting (no-change model, Moving Average and ARIMA, the empirical results reveal that GP can be a valuable tool in this field.

Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy

Science.gov (United States)

2017-10-01

AWARD NUMBER: W81XWH-15-1-0681 TITLE: Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated with Radiotherapy PRINCIPAL...TITLE AND SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0681Genetic Modeling of Radiation Injury in Prostate Cancer Patients Treated...effects, urinary morbidity, rectal injury, sexual dysfunction 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF

Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches

OpenAIRE

Kramer, Koen; van der Werf, D. C.

2010-01-01

The environment is changing and so are forests, in their functioning, in species composition, and in the species’ genetic composition. Many empirical and process-based models exist to support forest management. However, most of these models do not consider the impact of environmental changes and forest management on genetic diversity nor on the rate of adaptation of critical plant processes. How genetic diversity and rates of adaptation depend on management actions is a crucial next step in m...

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Model-based problem solving through symbolic regression via pareto genetic programming

NARCIS (Netherlands)

Vladislavleva, E.

2008-01-01

Pareto genetic programming methodology is extended by additional generic model selection and generation strategies that (1) drive the modeling engine to creation of models of reduced non-linearity and increased generalization capabilities, and (2) improve the effectiveness of the search for robust

Genetics on the Fly: A Primer on the Drosophila Model System

Science.gov (United States)

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

Science.gov (United States)

Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

2017-01-01

Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

Genetic alterations in syndromes with oral manifestations

Directory of Open Access Journals (Sweden)

Krishnamurthy Anuthama

2013-01-01

Full Text Available Ever since Gregor Johan Mendel proposed the law of inheritance, genetics has transcended the field of health and has entered all walks of life in its application. Thus, the gene is the pivoting factor for all happenings revolving around it. Knowledge of gene mapping in various diseases would be a valuable tool in prenatally diagnosing the condition and averting the future disability and stigma for the posterity. This article includes an array of genetically determined conditions in patients seen at our college out-patient department with complete manifestation, partial manifestation and array of manifestations not fitting into a particular syndrome.

Genetic linkage map and comparative genome analysis for the estuarine Atlantic killifish (Fundulus heteroclitus)

Data.gov (United States)

U.S. Environmental Protection Agency — Genetic linkage maps are valuable tools in evolutionary biology; however, their availability for wild populations is extremely limited. Fundulus heteroclitus...

Conservation genetics of managed ungulate populations

Science.gov (United States)

Scribner, Kim T.

1993-01-01

Natural populations of many species are increasingly impacted by human activities. Perturbations are particularly pronunced for large ungulates due in part to sport and commercial harvest, to reductions and fragmentation of native habitat, and as the result of reintroductions. These perturbations affect population size, sex and age composition, and population breeding structure, and as a consequence affect the levels and partitioning of genetic variation. Three case histories highlighting long-term ecological genetic research on mule deer Odocoileus hemionus (Rafinesque, 1817), white-tailed deer O. virginianus (Zimmermann, 1780), and Alpine ibex Capra i. ibex Linnaeus, 1758 are presented. Joint examinations of population ecological and genetic data from several populations of each species reveal: (1) that populations are not in genetic equilibrium, but that allele frequencies and heterozygosity change dramatically over time and among cohorts produced in successive years, (2) populations are genetically structured over short and large geographic distances reflecting local breeding structure and patterns of gene flow, respectively; however, this structure is quite dynamic over time, due in part to population exploitation, and (3) restocking programs are often undertaken with small numbers of founding individuals resulting in dramatic declines in levels of genetic variability and increasing levels of genetic differentiation among populations due to genetic drift. Genetic characteristics have and will continue to provide valuable indirect sources of information relating enviromental and human perturbations to changes in population processes.

Genetic structure and signatures of selection in grey reef sharks (Carcharhinus amblyrhynchos).

Science.gov (United States)

Momigliano, P; Harcourt, R; Robbins, W D; Jaiteh, V; Mahardika, G N; Sembiring, A; Stow, A

2017-09-01

With overfishing reducing the abundance of marine predators in multiple marine ecosystems, knowledge of genetic structure and local adaptation may provide valuable information to assist sustainable management. Despite recent technological advances, most studies on sharks have used small sets of neutral markers to describe their genetic structure. We used 5517 nuclear single-nucleotide polymorphisms (SNPs) and a mitochondrial DNA (mtDNA) gene to characterize patterns of genetic structure and detect signatures of selection in grey reef sharks (Carcharhinus amblyrhynchos). Using samples from Australia, Indonesia and oceanic reefs in the Indian Ocean, we established that large oceanic distances represent barriers to gene flow, whereas genetic differentiation on continental shelves follows an isolation by distance model. In Australia and Indonesia differentiation at nuclear SNPs was weak, with coral reefs acting as stepping stones maintaining connectivity across large distances. Differentiation of mtDNA was stronger, and more pronounced in females, suggesting sex-biased dispersal. Four independent tests identified a set of loci putatively under selection, indicating that grey reef sharks in eastern Australia are likely under different selective pressures to those in western Australia and Indonesia. Genetic distances averaged across all loci were uncorrelated with genetic distances calculated from outlier loci, supporting the conclusion that different processes underpin genetic divergence in these two data sets. This pattern of heterogeneous genomic differentiation, suggestive of local adaptation, has implications for the conservation of grey reef sharks; furthermore, it highlights that marine species showing little genetic differentiation at neutral loci may exhibit patterns of cryptic genetic structure driven by local selection.

Genetic genealogy comes of age: perspectives on the use of deep-rooted pedigrees in human population genetics.

Science.gov (United States)

Larmuseau, M H D; Van Geystelen, A; van Oven, M; Decorte, R

2013-04-01

In this article, we promote the implementation of extensive genealogical data in population genetic studies. Genealogical records can provide valuable information on the origin of DNA donors in a population genetic study, going beyond the commonly collected data such as residence, birthplace, language, and self-reported ethnicity. Recent studies demonstrated that extended genealogical data added to surname analysis can be crucial to detect signals of (past) population stratification and to interpret the population structure in a more objective manner. Moreover, when in-depth pedigree data are combined with haploid markers, it is even possible to disentangle signals of temporal differentiation within a population genetic structure during the last centuries. Obtaining genealogical data for all DNA donors in a population genetic study is a labor-intensive task but the vastly growing (genetic) genealogical databases, due to the broad interest of the public, are making this job more time-efficient if there is a guarantee for sufficient data quality. At the end, we discuss the advantages and pitfalls of using genealogy within sampling campaigns and we provide guidelines for future population genetic studies. Copyright © 2013 Wiley Periodicals, Inc.

Preparing valuable hydrocarbons by hydrogenation

Energy Technology Data Exchange (ETDEWEB)

Pier, M

1930-08-22

A process is described for the preparation of valuable hydrocarbons by treatment of carbonaceous materials, like coal, tars, minerals oils, and their distillation and conversion products, and for refining of liquid hydrocarbon mixture obtained at raised temperature and under pressure, preferably in the presence of catalysts, by the use of hydrogen-containing gases, purified and obtained by distilling solid combustibles, characterized by the purification of the hydrogen-containing gases being accomplished for the purpose of practically complete removal of the oxygen by heating at ordinary or higher pressure in the presence of a catalyst containing silver and oxides of metals of group VI of the periodic system.

Genetic characterization of some Romanian red wine grapevine varieties

Science.gov (United States)

Ghetea, Ligia Gabriela; Motoc, Rozalia Magda; Niculescu, Ana-Maria; Litescu, Simona Carmen; Duma, Virgil-Florin; Popescu, Carmen Florentina

2008-04-01

In our study we have considered three of the most valuable Romanian red wine grapevine cultivars: Feteasca neagra, Feteasca alba and Novac. We have chosen to study grapevine because grapes and wine are an important part of a healthy diet, and because red grapes have the highest content of proanthocyanidins, that act as antioxidants (free radical scavengers) in the human body. Proanthocyanidins possess anti-mutagenic, anti-tumor, anti-viral activities and they present many other confirmed or potential benefits. Genotyping method was applied in order to asses the genetic profile at 14 microsatellite loci, for two cultivars: Feteasca neagra and Feteasca alba. In order to achieve this, the HPLC-DAD method was used. The content of anthocyans in grape skin from two cultivars - Feteasca neagra and Novac - was measured. Microsatellite markers have been certified as powerful tools for assessing genetic identities and genetic relationships between grapevine gene pools. Genetic characterization of grapevine cultivars can certify their authenticity and purity, two features that have a direct effect on the quality and value of the finished product, the wine. In our country, this is the first attempt in order to establish a genetic profile for valuable Romanian origin grapevine varieties. In some of the 14 microsatellitic loci, Feteasca neagra and Feteasca alba cultivars presented allele size variants different from the values cited in the literature, proving that these cultivars belong to a geographical distinct gene pool. The content of anthocyans in Feteasca neagra grape skin was significantly higher than in Novac.

Estimation of genetic parameters related to eggshell strength using random regression models.

Science.gov (United States)

Guo, J; Ma, M; Qu, L; Shen, M; Dou, T; Wang, K

2015-01-01

This study examined the changes in eggshell strength and the genetic parameters related to this trait throughout a hen's laying life using random regression. The data were collected from a crossbred population between 2011 and 2014, where the eggshell strength was determined repeatedly for 2260 hens. Using random regression models (RRMs), several Legendre polynomials were employed to estimate the fixed, direct genetic and permanent environment effects. The residual effects were treated as independently distributed with heterogeneous variance for each test week. The direct genetic variance was included with second-order Legendre polynomials and the permanent environment with third-order Legendre polynomials. The heritability of eggshell strength ranged from 0.26 to 0.43, the repeatability ranged between 0.47 and 0.69, and the estimated genetic correlations between test weeks was high at > 0.67. The first eigenvalue of the genetic covariance matrix accounted for about 97% of the sum of all the eigenvalues. The flexibility and statistical power of RRM suggest that this model could be an effective method to improve eggshell quality and to reduce losses due to cracked eggs in a breeding plan.

The evolution of menstruation: A new model for genetic assimilation

Science.gov (United States)

Emera, D.; Romero, R.; Wagner, G.

2012-01-01

Why do humans menstruate while most mammals do not? Here, we present our answer to this long-debated question, arguing that (i) menstruation occurs as a mechanistic consequence of hormone-induced differentiation of the endometrium (referred to as spontaneous decidualization, or SD); (ii) SD evolved because of maternal-fetal conflict; and (iii) SD evolved by genetic assimilation of the decidualization reaction, which is induced by the fetus in non-menstruating species. The idea that menstruation occurs as a consequence of SD has been proposed in the past, but here we present a novel hypothesis on how SD evolved. We argue that decidualization became genetically stabilized in menstruating lineages, allowing females to prepare for pregnancy without any signal from the fetus. We present three models for the evolution of SD by genetic assimilation, based on recent advances in our understanding of the mechanisms of endometrial differentiation and implantation. Testing these models will ultimately shed light on the evolutionary significance of menstruation, as well as on the etiology of human reproductive disorders like endometriosis and recurrent pregnancy loss. PMID:22057551

Application of the genetic algorithm to blume-emery-griffiths model: Test Cases

International Nuclear Information System (INIS)

Erdinc, A.

2004-01-01

The equilibrium properties of the Blume-Emery-Griffiths (BEO) model Hamiltonian with the arbitrary bilinear (1), biquadratic (K) and crystal field interaction (D) are studied using the genetic algorithm technique. Results are compared with lowest approximation of the cluster variation method (CVM), which is identical to the mean field approximation. We found that the genetic algorithm to be very efficient for fast search at the average fraction of the spins, especially in the early stages as the system is far from the equilibrium state. A combination of the genetic algorithm followed by one of the well-tested simulation techniques seems to be an optimal approach. The curvature of the inverse magnetic susceptibility is also presented for the stable state of the BEG model

Modeling the Isentropic Head Value of Centrifugal Gas Compressor using Genetic Programming

Directory of Open Access Journals (Sweden)

Safiyullah Ferozkhan

2016-01-01

Full Text Available Gas compressor performance is vital in oil and gas industry because of the equipment criticality which requires continuous operations. Plant operators often face difficulties in predicting appropriate time for maintenance and would usually rely on time based predictive maintenance intervals as recommended by original equipment manufacturer (OEM. The objective of this work is to develop the computational model to find the isentropic head value using genetic programming. The isentropic head value is calculated from the OEM performance chart. Inlet mass flow rate and speed of the compressor are taken as the input value. The obtained results from the GP computational models show good agreement with experimental and target data with the average prediction error of 1.318%. The genetic programming computational model will assist machinery engineers to quantify performance deterioration of gas compressor and the results from this study will be then utilized to estimate future maintenance requirements based on the historical data. In general, this genetic programming modelling provides a powerful solution for gas compressor operators to realize predictive maintenance approach in their operations.

Evolutionary model with genetics, aging, and knowledge

Science.gov (United States)

Bustillos, Armando Ticona; de Oliveira, Paulo Murilo

2004-02-01

We represent a process of learning by using bit strings, where 1 bits represent the knowledge acquired by individuals. Two ways of learning are considered: individual learning by trial and error, and social learning by copying knowledge from other individuals or from parents in the case of species with parental care. The age-structured bit string allows us to study how knowledge is accumulated during life and its influence over the genetic pool of a population after many generations. We use the Penna model to represent the genetic inheritance of each individual. In order to study how the accumulated knowledge influences the survival process, we include it to help individuals to avoid the various death situations. Modifications in the Verhulst factor do not show any special feature due to its random nature. However, by adding years to life as a function of the accumulated knowledge, we observe an improvement of the survival rates while the genetic fitness of the population becomes worse. In this latter case, knowledge becomes more important in the last years of life where individuals are threatened by diseases. Effects of offspring overprotection and differences between individual and social learning can also be observed. Sexual selection as a function of knowledge shows some effects when fidelity is imposed.

The Genetics of Autoimmune Thyroiditis: the first decade

Science.gov (United States)

Rose, Noel R.

2011-01-01

Most of our current understanding of the genetic predisposition to autoimmune disease can be traced to experiments performed in the decade from 1971 to 1981. Chella David was a key contributor to this research. Many of these early steps came from studies of experimental autoimmune thyroiditis. This model has been especially valuable because essentially the same disease can occur spontaneously in selected strains of animals or can be induced by deliberate immunization. From a genetic point of view, the disease has been investigated in three different species: mice, rats and chickens. The same antigen, thyroglobulin, initiates the disease in all three species. Among the main discoveries were the relationship of autoimmune disease to the major histocompatibility complex (MHC), the interplay of different subregions within the MHC in promoting or retarding development of disease, the differing roles of MHC class II and MHC I class genes in induction and effector phases, respectively, and the cumulative effect of non-MHC genes, each of which represents a small addition to overall susceptibility. Other experiments revealed that genetic differences in thyroglobulin allotypes influence susceptibility to thyroiditis. Thyroid glands differed in different strains in vulnerability to passive transfer of antibody. The first evidence of modulatory genes on the sex-related X chromosome emerged. All of these genetic findings were concurrently translated to the human disease, Hashimoto’s thyroiditis, where thyroglobulin is also the initiating antigen. PMID:21683550

A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction

Science.gov (United States)

Bell, Richard L.; Hauser, Sheketha; Rodd, Zachary A.; Liang, Tiebing; Sari, Youssef; McClintick, Jeanette; Rahman, Shafiqur; Engleman, Eric A.

2016-01-01

The purpose of this review is to present up-to-date pharmacological, genetic and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein we sought to place the P rat’s behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this paper discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general. PMID:27055615

Genetic enhancement of macroautophagy in vertebrate models of neurodegenerative diseases.

Science.gov (United States)

Ejlerskov, Patrick; Ashkenazi, Avraham; Rubinsztein, David C

2018-04-03

Most of the neurodegenerative diseases that afflict humans manifest with the intraneuronal accumulation of toxic proteins that are aggregate-prone. Extensive data in cell and neuronal models support the concept that such proteins, like mutant huntingtin or alpha-synuclein, are substrates for macroautophagy (hereafter autophagy). Furthermore, autophagy-inducing compounds lower the levels of such proteins and ameliorate their toxicity in diverse animal models of neurodegenerative diseases. However, most of these compounds also have autophagy-independent effects and it is important to understand if similar benefits are seen with genetic strategies that upregulate autophagy, as this strengthens the validity of this strategy in such diseases. Here we review studies in vertebrate models using genetic manipulations of core autophagy genes and describe how these improve pathology and neurodegeneration, supporting the validity of autophagy upregulation as a target for certain neurodegenerative diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

The characterization of goat genetic diversity : Towards a genomic approach

NARCIS (Netherlands)

Ajmone-Marsan, P.; Colli, L.; Han, J. L.; Achilli, A.; Lancioni, H.; Joost, S.; Crepaldi, P.; Pilla, F.; Stella, A.; Taberlet, P.; Boettcher, P.; Negrini, R.; Lenstra, J. A.

2014-01-01

The investigation of genetic diversity at molecular level has been proposed as a valuable complement and sometimes proxy to phenotypic diversity of local breeds and is presently considered as one of the FAO priorities for breed characterization. By recommending a set of selected molecular markers

Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study.

Science.gov (United States)

Rijsdijk, Frühling V; Vernon, P A; Boomsma, Dorret I

2002-05-01

Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard Progressive test score, collected in 194 18-year-old Dutch twin pairs. We investigated whether first-order group factors possess genetic and environmental variance independent of the higher-order general factor and whether the hierarchical structure is significant for all sources of variance. A hierarchical model with the 3 Cohen group-factors (verbal comprehension, perceptual organisation and freedom-from-distractibility) and a higher-order g factor showed the best fit to the phenotypic data and to additive genetic influences (A), whereas the unique environmental source of variance (E) could be modeled by a single general factor and specifics. There was no evidence for common environmental influences. The covariation among the WAIS group factors and the covariation between the group factors and the Raven is predominantly influenced by a second-order genetic factor and strongly support the notion of a biological basis of g.

Linear Mixed Models in Statistical Genetics

NARCIS (Netherlands)

R. de Vlaming (Ronald)

2017-01-01

markdownabstractOne of the goals of statistical genetics is to elucidate the genetic architecture of phenotypes (i.e., observable individual characteristics) that are affected by many genetic variants (e.g., single-nucleotide polymorphisms; SNPs). A particular aim is to identify specific SNPs that

Models for genetic evaluations of claw health traits in Spanish dairy cattle.

Science.gov (United States)

Pérez-Cabal, M A; Charfeddine, N

2015-11-01

Genetic parameters of 7 claw health traits from Spanish dairy cattle were estimated and the predictive ability of linear and ordinal threshold models were compared and assessed. This study included data on interdigital and digital dermatitis (DE), sole ulcer (SU), white line disease (WL), interdigital hyperplasia (IH), interdigital phlegmon (IP), and chronic laminitis (CL) collected between July 2012 and June 2013 from 834 dairy herds visited by 21 trained trimmers. An overall claw disorder (OCD) was also considered an indicator the absence or the presence of at least 1 of the 6 disorders. Claw health traits were scored as categorical traits with 3 degrees of severity (nonaffected, mild, and severe disorder). Genetic parameters were estimated by fitting both a standard linear model and an ordinal threshold animal model. Around 21% of cows had at least 1 claw disorder, and the most frequent disorders were SU, DE, WL, and CL. Heritabilities of claw disorders estimated with a linear model ranged from 0.01 (IP) to 0.05 (OCD), whereas estimates from the ordinal threshold models ranged from 0.06 to 0.39 (for IP and IH, respectively). Repeatabilities of claw health estimated with the linear model varied from 0.03 to 0.18 and estimates with the ordinal threshold model ranged from 0.33 to 0.69. The global trait OCD was correlated with all disorders, except for IH and IP when the linear model was fitted. Two different genetic backgrounds of claw disorders were found. Digital dermatitis showed positive correlations with IH and IP, whereas SU was positively correlated with WL and CL. The predictive ability of the models was assessed using mean squared error and Pearson correlation between the real observation and the corresponding prediction using cross-validation. Regardless of the claw health status, the linear model led to smaller mean squared error. However, differences in predictive ability were found when predicting nonaffected and affected animals. For most traits

Vegetable Genetic Resources in China

Directory of Open Access Journals (Sweden)

Haiping WANG

2018-03-01

Full Text Available China is recognized as an important region for plant biodiversity based on its vast and historical collection of vegetable germplasm. The aim of this review is to describe the exploration status of vegetable genetic resources in China, including their collection, preservation, evaluation, and utilization. China has established a number of national-level vegetable genetic resources preservation units, including the National Mid-term Genebank for Vegetable Germplasm Resources, the National Germplasm Repository for Vegetatively-Propagated Vegetables, and the National Germplasm Repository for Aquatic Vegetables. In 2015, at least 36 000 accessions were collected and preserved in these units. In the past decade, 44 descriptors and data standards for different species have been published, and most accessions have been evaluated for screening the germplasms for specific important traits such as morphological characteristics, disease resistance, pest resistance, and stress tolerance. Moreover, the genetic diversity and evolution of some vegetable germplasms have been evaluated at the molecular level. Recently, more than 1 000 accessions were distributed to researchers and breeders each year by various means for vegetable research and production. However, additional wild-relative and abroad germplasms from other regions need to be collected and preserved in the units to expand genetic diversity. Furthermore, there is a need to utilize advanced techniques to better understand the background and genetic diversity of a wide range of vegetable genetic resources. This review will provide agricultural scientists’ insights into the genetic diversity in China and provide information on the distribution and potential utilization of these valuable genetic resources. Keywords: vegetable, genetic resource, preservation, evaluation, utilization

Setaria viridis as a model system to advance millet genetics and genomics

Directory of Open Access Journals (Sweden)

Pu Huang

2016-11-01

Full Text Available Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crop.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics.

Science.gov (United States)

Huang, Pu; Shyu, Christine; Coelho, Carla P; Cao, Yingying; Brutnell, Thomas P

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail ( Setaria viridis ) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica . These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

Science.gov (United States)

Huang, Pu; Shyu, Christine; Coelho, Carla P.; Cao, Yingying; Brutnell, Thomas P.

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops. PMID:27965689

Recent developments in computer modeling add ecological realism to landscape genetics

Science.gov (United States)

Background / Question / Methods A factor limiting the rate of progress in landscape genetics has been the shortage of spatial models capable of linking life history attributes such as dispersal behavior to complex dynamic landscape features. The recent development of new models...

A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data

DEFF Research Database (Denmark)

Guillot, Gilles; Rena, Sabrina; Ledevin, Ronan

2012-01-01

Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the dierentiation of the units. We propose a statistical model with a double original...... advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unied model and inference framework, thus...... an intricate case of inter- and intra-species dierentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Geneland....

Genetic recombinational and physical linkage analyses on slash pine

Science.gov (United States)

Rob Doudrick

1996-01-01

Slash pine is native to the southeastern USA, but is commercially valuable world-wide as a timber-,fiber- and resin-producing species. Breeding objectives emphasize selection for fusiform rust disease resistance. Identification of markers linked to genetic factors conditioning specificity should expand our knowledge of disease development. Towards this end, random...

Genetic Algorithms for a Parameter Estimation of a Fermentation Process Model: A Comparison

Directory of Open Access Journals (Sweden)

Olympia Roeva

2005-12-01

Full Text Available In this paper the problem of a parameter estimation using genetic algorithms is examined. A case study considering the estimation of 6 parameters of a nonlinear dynamic model of E. coli fermentation is presented as a test problem. The parameter estimation problem is stated as a nonlinear programming problem subject to nonlinear differential-algebraic constraints. This problem is known to be frequently ill-conditioned and multimodal. Thus, traditional (gradient-based local optimization methods fail to arrive satisfied solutions. To overcome their limitations, the use of different genetic algorithms as stochastic global optimization methods is explored. These algorithms are proved to be very suitable for the optimization of highly non-linear problems with many variables. Genetic algorithms can guarantee global optimality and robustness. These facts make them advantageous in use for parameter identification of fermentation models. A comparison between simple, modified and multi-population genetic algorithms is presented. The best result is obtained using the modified genetic algorithm. The considered algorithms converged very closely to the cost value but the modified algorithm is in times faster than other two.

Guidelines for collecting and maintaining archives for genetic monitoring

Science.gov (United States)

Jackson, Jennifer A.; Laikre, Linda; Baker, C. Scott; Kendall, Katherine C.; ,

2012-01-01

Rapid advances in molecular genetic techniques and the statistical analysis of genetic data have revolutionized the way that populations of animals, plants and microorganisms can be monitored. Genetic monitoring is the practice of using molecular genetic markers to track changes in the abundance, diversity or distribution of populations, species or ecosystems over time, and to follow adaptive and non-adaptive genetic responses to changing external conditions. In recent years, genetic monitoring has become a valuable tool in conservation management of biological diversity and ecological analysis, helping to illuminate and define cryptic and poorly understood species and populations. Many of the detected biodiversity declines, changes in distribution and hybridization events have helped to drive changes in policy and management. Because a time series of samples is necessary to detect trends of change in genetic diversity and species composition, archiving is a critical component of genetic monitoring. Here we discuss the collection, development, maintenance, and use of archives for genetic monitoring. This includes an overview of the genetic markers that facilitate effective monitoring, describes how tissue and DNA can be stored, and provides guidelines for proper practice.

Amniotic Fluid Stem Cells: A Novel Source for Modeling of Human Genetic Diseases

Directory of Open Access Journals (Sweden)

Ivana Antonucci

2016-04-01

Full Text Available In recent years, great interest has been devoted to the use of Induced Pluripotent Stem cells (iPS for modeling of human genetic diseases, due to the possibility of reprogramming somatic cells of affected patients into pluripotent cells, enabling differentiation into several cell types, and allowing investigations into the molecular mechanisms of the disease. However, the protocol of iPS generation still suffers from technical limitations, showing low efficiency, being expensive and time consuming. Amniotic Fluid Stem cells (AFS represent a potential alternative novel source of stem cells for modeling of human genetic diseases. In fact, by means of prenatal diagnosis, a number of fetuses affected by chromosomal or Mendelian diseases can be identified, and the amniotic fluid collected for genetic testing can be used, after diagnosis, for the isolation, culture and differentiation of AFS cells. This can provide a useful stem cell model for the investigation of the molecular basis of the diagnosed disease without the necessity of producing iPS, since AFS cells show some features of pluripotency and are able to differentiate in cells derived from all three germ layers “in vitro”. In this article, we describe the potential benefits provided by using AFS cells in the modeling of human genetic diseases.

Genetic mouse models of brain ageing and Alzheimer's disease.

Science.gov (United States)

Bilkei-Gorzo, Andras

2014-05-01

Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. Copyright © 2013 Elsevier Inc. All rights reserved.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

DEFF Research Database (Denmark)

Bothwell, H.; Bisbing, S.; Therkildsen, Nina Overgaard

2013-01-01

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental...... loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi...... variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major...

Application of genetic algorithm in radio ecological models parameter determination

Energy Technology Data Exchange (ETDEWEB)

Pantelic, G. [Institute of Occupatioanl Health and Radiological Protection ' Dr Dragomir Karajovic' , Belgrade (Serbia)

2006-07-01

The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 {+-} 3) days and transfer coefficient from grass to milk is (0.019 {+-} 0.005). (authors)

Simulated evolution applied to study the genetic code optimality using a model of codon reassignments.

Science.gov (United States)

Santos, José; Monteagudo, Angel

2011-02-21

As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the fact that the best possible codes show the patterns of the

Simulated evolution applied to study the genetic code optimality using a model of codon reassignments

Directory of Open Access Journals (Sweden)

Monteagudo Ángel

2011-02-01

Full Text Available Abstract Background As the canonical code is not universal, different theories about its origin and organization have appeared. The optimization or level of adaptation of the canonical genetic code was measured taking into account the harmful consequences resulting from point mutations leading to the replacement of one amino acid for another. There are two basic theories to measure the level of optimization: the statistical approach, which compares the canonical genetic code with many randomly generated alternative ones, and the engineering approach, which compares the canonical code with the best possible alternative. Results Here we used a genetic algorithm to search for better adapted hypothetical codes and as a method to guess the difficulty in finding such alternative codes, allowing to clearly situate the canonical code in the fitness landscape. This novel proposal of the use of evolutionary computing provides a new perspective in the open debate between the use of the statistical approach, which postulates that the genetic code conserves amino acid properties far better than expected from a random code, and the engineering approach, which tends to indicate that the canonical genetic code is still far from optimal. We used two models of hypothetical codes: one that reflects the known examples of codon reassignment and the model most used in the two approaches which reflects the current genetic code translation table. Although the standard code is far from a possible optimum considering both models, when the more realistic model of the codon reassignments was used, the evolutionary algorithm had more difficulty to overcome the efficiency of the canonical genetic code. Conclusions Simulated evolution clearly reveals that the canonical genetic code is far from optimal regarding its optimization. Nevertheless, the efficiency of the canonical code increases when mistranslations are taken into account with the two models, as indicated by the

A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk

Science.gov (United States)

2017-10-01

AWARD NUMBER: W81XWH-15-1-0529 TITLE: A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk PRINCIPAL INVESTIGATOR...AND SUBTITLE A Model for Understanding the Genetic Basis for Disparity in Prostate Cancer Risk 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1...STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Prostate cancer is the most commonly diagnosed cancer in

A genetic algorithm for optimizing multi-pole Debye models of tissue dielectric properties

International Nuclear Information System (INIS)

Clegg, J; Robinson, M P

2012-01-01

Models of tissue dielectric properties (permittivity and conductivity) enable the interactions of tissues and electromagnetic fields to be simulated, which has many useful applications in microwave imaging, radio propagation, and non-ionizing radiation dosimetry. Parametric formulae are available, based on a multi-pole model of tissue dispersions, but although they give the dielectric properties over a wide frequency range, they do not convert easily to the time domain. An alternative is the multi-pole Debye model which works well in both time and frequency domains. Genetic algorithms are an evolutionary approach to optimization, and we found that this technique was effective at finding the best values of the multi-Debye parameters. Our genetic algorithm optimized these parameters to fit to either a Cole–Cole model or to measured data, and worked well over wide or narrow frequency ranges. Over 10 Hz–10 GHz the best fits for muscle, fat or bone were each found for ten dispersions or poles in the multi-Debye model. The genetic algorithm is a fast and effective method of developing tissue models that compares favourably with alternatives such as the rational polynomial fit. (paper)

Parasites as valuable stock markers for fisheries in Australasia, East Asia and the Pacific Islands.

Science.gov (United States)

Lester, R J G; Moore, B R

2015-01-01

Over 30 studies in Australasia, East Asia and the Pacific Islands region have collected and analysed parasite data to determine the ranges of individual fish, many leading to conclusions about stock delineation. Parasites used as biological tags have included both those known to have long residence times in the fish and those thought to be relatively transient. In many cases the parasitological conclusions have been supported by other methods especially analysis of the chemical constituents of otoliths, and to a lesser extent, genetic data. In analysing parasite data, authors have applied multiple different statistical methodologies, including summary statistics, and univariate and multivariate approaches. Recently, a growing number of researchers have found non-parametric methods, such as analysis of similarities and cluster analysis, to be valuable. Future studies into the residence times, life cycles and geographical distributions of parasites together with more robust analytical methods will yield much important information to clarify stock structures in the area.

Genetic Evaluation and Ranking of Different Animal Models Using ...

African Journals Online (AJOL)

An animal model utilizes all relationships available in a given data set. Estimates for variance components for additive direct, additive maternal, maternal environmental and direct environmental effects, and their covariances between direct and maternal genetic effects for post weaning growth traits have been obtained with ...

Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes

International Nuclear Information System (INIS)

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih; Leong, Susanna Su Jan; Chang, Matthew Wook

2014-01-01

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.

Production of Fatty Acid-Derived Valuable Chemicals in Synthetic Microbes

Energy Technology Data Exchange (ETDEWEB)

Yu, Ai-Qun; Pratomo Juwono, Nina Kurniasih [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Leong, Susanna Su Jan [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore); Singapore Institute of Technology, Singapore (Singapore); Chang, Matthew Wook, E-mail: bchcmw@nus.edu.sg [Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (Singapore); Synthetic Biology Research Program, National University of Singapore, Singapore (Singapore)

2014-12-23

Fatty acid derivatives, such as hydroxy fatty acids, fatty alcohols, fatty acid methyl/ethyl esters, and fatty alka(e)nes, have a wide range of industrial applications including plastics, lubricants, and fuels. Currently, these chemicals are obtained mainly through chemical synthesis, which is complex and costly, and their availability from natural biological sources is extremely limited. Metabolic engineering of microorganisms has provided a platform for effective production of these valuable biochemicals. Notably, synthetic biology-based metabolic engineering strategies have been extensively applied to refactor microorganisms for improved biochemical production. Here, we reviewed: (i) the current status of metabolic engineering of microbes that produce fatty acid-derived valuable chemicals, and (ii) the recent progress of synthetic biology approaches that assist metabolic engineering, such as mRNA secondary structure engineering, sensor-regulator system, regulatable expression system, ultrasensitive input/output control system, and computer science-based design of complex gene circuits. Furthermore, key challenges and strategies were discussed. Finally, we concluded that synthetic biology provides useful metabolic engineering strategies for economically viable production of fatty acid-derived valuable chemicals in engineered microbes.

Genetic modelling in schizophrenia according to HLA typing.

Science.gov (United States)

Smeraldi, E; Macciardi, F; Gasperini, M; Orsini, A; Bellodi, L; Fabio, G; Morabito, A

1986-09-01

Studying families of schizophrenic patients, we observed that the risk of developing the overt form of the illness could be enhanced by some factors. Among these various factors we focused our attention on a biological variable, namely the presence or the absence of particular HLA antigens: partitioning our schizophrenic patients according to their HLA structure (i.e. those with HLA-A1 or CRAG-A1 antigens and those with HLA-non-CRAG-A1 antigens, respectively), revealed different illness distribution in the two groups. From a genetic point of view, this finding suggests the presence of heterogeneity in the hypothetical liability system related to schizophrenia and we evaluated the heterogeneity hypothesis by applying alternative genetic models to our data, trying to detect more biologically homogeneous subgroups of the disease.

Genetic algorithm based optimization of advanced solar cell designs modeled in Silvaco AtlasTM

OpenAIRE

Utsler, James

2006-01-01

A genetic algorithm was used to optimize the power output of multi-junction solar cells. Solar cell operation was modeled using the Silvaco ATLASTM software. The output of the ATLASTM simulation runs served as the input to the genetic algorithm. The genetic algorithm was run as a diffusing computation on a network of eighteen dual processor nodes. Results showed that the genetic algorithm produced better power output optimizations when compared with the results obtained using the hill cli...

Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree

Directory of Open Access Journals (Sweden)

S. Samadianfard

2017-01-01

Full Text Available Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23 presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21 used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13 proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16 used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11 evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities. Materials and Methods: Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned

Application of genetic algorithm in radio ecological models parameter determination

International Nuclear Information System (INIS)

Pantelic, G.

2006-01-01

The method of genetic algorithms was used to determine the biological half-life of 137 Cs in cow milk after the accident in Chernobyl. Methodologically genetic algorithms are based on the fact that natural processes tend to optimize themselves and therefore this method should be more efficient in providing optimal solutions in the modeling of radio ecological and environmental events. The calculated biological half-life of 137 Cs in milk is (32 ± 3) days and transfer coefficient from grass to milk is (0.019 ± 0.005). (authors)

The Mouse Lemur, a Genetic Model Organism for Primate Biology, Behavior, and Health.

Science.gov (United States)

Ezran, Camille; Karanewsky, Caitlin J; Pendleton, Jozeph L; Sholtz, Alex; Krasnow, Maya R; Willick, Jason; Razafindrakoto, Andriamahery; Zohdy, Sarah; Albertelli, Megan A; Krasnow, Mark A

2017-06-01

Systematic genetic studies of a handful of diverse organisms over the past 50 years have transformed our understanding of biology. However, many aspects of primate biology, behavior, and disease are absent or poorly modeled in any of the current genetic model organisms including mice. We surveyed the animal kingdom to find other animals with advantages similar to mice that might better exemplify primate biology, and identified mouse lemurs ( Microcebus spp.) as the outstanding candidate. Mouse lemurs are prosimian primates, roughly half the genetic distance between mice and humans. They are the smallest, fastest developing, and among the most prolific and abundant primates in the world, distributed throughout the island of Madagascar, many in separate breeding populations due to habitat destruction. Their physiology, behavior, and phylogeny have been studied for decades in laboratory colonies in Europe and in field studies in Malagasy rainforests, and a high quality reference genome sequence has recently been completed. To initiate a classical genetic approach, we developed a deep phenotyping protocol and have screened hundreds of laboratory and wild mouse lemurs for interesting phenotypes and begun mapping the underlying mutations, in collaboration with leading mouse lemur biologists. We also seek to establish a mouse lemur gene "knockout" library by sequencing the genomes of thousands of mouse lemurs to identify null alleles in most genes from the large pool of natural genetic variants. As part of this effort, we have begun a citizen science project in which students across Madagascar explore the remarkable biology around their schools, including longitudinal studies of the local mouse lemurs. We hope this work spawns a new model organism and cultivates a deep genetic understanding of primate biology and health. We also hope it establishes a new and ethical method of genetics that bridges biological, behavioral, medical, and conservation disciplines, while

Genetic parameters for racing records in trotters using linear and generalized linear models.

Science.gov (United States)

Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

2012-09-01

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.

Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

Directory of Open Access Journals (Sweden)

Yiming Hu

2017-06-01

Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

Genetic models of absence epilepsy: New concepts and insights

NARCIS (Netherlands)

Luijtelaar, E.L.J.M. van; Stein, J.

2017-01-01

The discovery, development and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures, which has gained impact within the international epilepsy community. A focal zone has been identified in the perioral region of the somatosensory cortex in

Revised models and genetic parameter estimates for production and ...

African Journals Online (AJOL)

Genetic parameters for production and reproduction traits in the Elsenburg Dormer sheep stud were estimated using records of 11743 lambs born between 1943 and 2002. An animal model with direct and maternal additive, maternal permanent and temporary environmental effects was fitted for traits considered traits of the ...

Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

Science.gov (United States)

Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

2017-09-21

Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

Science.gov (United States)

Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

2015-03-01

A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling the genetic risk in age-related macular degeneration.

Directory of Open Access Journals (Sweden)

Felix Grassmann

Full Text Available Late-stage age-related macular degeneration (AMD is a common sight-threatening disease of the central retina affecting approximately 1 in 30 Caucasians. Besides age and smoking, genetic variants from several gene loci have reproducibly been associated with this condition and likely explain a large proportion of disease. Here, we developed a genetic risk score (GRS for AMD based on 13 risk variants from eight gene loci. The model exhibited good discriminative accuracy, area-under-curve (AUC of the receiver-operating characteristic of 0.820, which was confirmed in a cross-validation approach. Noteworthy, younger AMD patients aged below 75 had a significantly higher mean GRS (1.87, 95% CI: 1.69-2.05 than patients aged 75 and above (1.45, 95% CI: 1.36-1.54. Based on five equally sized GRS intervals, we present a risk classification with a relative AMD risk of 64.0 (95% CI: 14.11-1131.96 for individuals in the highest category (GRS 3.44-5.18, 0.5% of the general population compared to subjects with the most common genetic background (GRS -0.05-1.70, 40.2% of general population. The highest GRS category identifies AMD patients with a sensitivity of 7.9% and a specificity of 99.9% when compared to the four lower categories. Modeling a general population around 85 years of age, 87.4% of individuals in the highest GRS category would be expected to develop AMD by that age. In contrast, only 2.2% of individuals in the two lowest GRS categories which represent almost 50% of the general population are expected to manifest AMD. Our findings underscore the large proportion of AMD cases explained by genetics particularly for younger AMD patients. The five-category risk classification could be useful for therapeutic stratification or for diagnostic testing purposes once preventive treatment is available.

Genetic Diseases and Genetic Determinism Models in French Secondary School Biology Textbooks

Science.gov (United States)

Castera, Jeremy; Bruguiere, Catherine; Clement, Pierre

2008-01-01

The presentation of genetic diseases in French secondary school biology textbooks is analysed to determine the major conceptions taught in the field of human genetics. References to genetic diseases, and the processes by which they are explained (monogeny, polygeny, chromosomal anomaly and environmental influence) are studied in recent French…

New Therapies Offer Valuable Options for Patients with Melanoma

Science.gov (United States)

Two phase III clinical trials of new therapies for patients with metastatic melanoma presented in June at the 2011 ASCO conference confirmed that vemurafenib and ipilimumab (Yervoy™) offer valuable new options for the disease.

Behavioral phenotypes of genetic mouse models of autism.

Science.gov (United States)

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

2016-01-01

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

Teaching genetics using hands-on models, problem solving, and inquiry-based methods

Science.gov (United States)

Hoppe, Stephanie Ann

Teaching genetics can be challenging because of the difficulty of the content and misconceptions students might hold. This thesis focused on using hands-on model activities, problem solving, and inquiry-based teaching/learning methods in order to increase student understanding in an introductory biology class in the area of genetics. Various activities using these three methods were implemented into the classes to address any misconceptions and increase student learning of the difficult concepts. The activities that were implemented were shown to be successful based on pre-post assessment score comparison. The students were assessed on the subjects of inheritance patterns, meiosis, and protein synthesis and demonstrated growth in all of the areas. It was found that hands-on models, problem solving, and inquiry-based activities were more successful in learning concepts in genetics and the students were more engaged than tradition styles of lecture.

A case report on inVALUABLE: insect value chain in a circular bioeconomy

DEFF Research Database (Denmark)

Heckmann, L.-H.; Andersen, J.L.; Eilenberg, J.

2018-01-01

partners span the entire value chain and include entrepreneurs, experts in biology, biotechnology, automation, processing and food tech and safety. This paper provides an overview of the goal, activities and some preliminary results obtained during the first year of the project.......The vision of inVALUABLE is to create a sustainable resource-efficient industry for animal production based on insects. inVALUABLE has focus on the R&D demand for scaling up production of insects in Denmark and assessing the application potential of particularly mealworms. The inVALUABLE consortium...

Distribution and population genetics of walleye and sauger

Science.gov (United States)

Haponski, Amanda E.; Sloss, Brian L.

2014-01-01

Conserving genetic diversity and local adaptations are management priorities for wild populations of exploited species, which increasingly are subject to climate change, habitat loss, and pollution. These constitute growing concerns for the walleye Sander vitreus, an ecologically and economically valuable North American temperate fish with large Laurentian Great Lakes' fisheries. This study compares genetic diversity and divergence patterns across its widespread native range using mitochondrial (mt) DNA control region sequences and nine nuclear DNA microsatellite (μsat) loci, examining historic and contemporary influences. We analyze the genetic and morphological characters of a putative endemic variant– “blue pike” S. v. “glaucus” –described from Lakes Erie and Ontario, which became extinct. Walleye with turquoise-colored mucus also are evaluated, since some have questioned whether these are related to the “blue pike”.

A unifying study of phenotypic and molecular genetic variability in ...

Indian Academy of Sciences (India)

2016-08-26

Aug 26, 2016 ... Home; Journals; Journal of Genetics; Volume 93; Issue 1 ... Populations from the Paranaense biogeographic province showed the highest mean value of number of seeds per fruit making them valuable as well with regard to the exploitation of management strategies as a ... Please take note of this change.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

Science.gov (United States)

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

New insights into the endophenotypic status of cognition in bipolar disorder: genetic modelling study of twins and siblings.

Science.gov (United States)

Georgiades, Anna; Rijsdijk, Fruhling; Kane, Fergus; Rebollo-Mesa, Irene; Kalidindi, Sridevi; Schulze, Katja K; Stahl, Daniel; Walshe, Muriel; Sahakian, Barbara J; McDonald, Colm; Hall, Mei-Hua; Murray, Robin M; Kravariti, Eugenia

2016-06-01

Twin studies have lacked statistical power to apply advanced genetic modelling techniques to the search for cognitive endophenotypes for bipolar disorder. To quantify the shared genetic variability between bipolar disorder and cognitive measures. Structural equation modelling was performed on cognitive data collected from 331 twins/siblings of varying genetic relatedness, disease status and concordance for bipolar disorder. Using a parsimonious AE model, verbal episodic and spatial working memory showed statistically significant genetic correlations with bipolar disorder (rg = |0.23|-|0.27|), which lost statistical significance after covarying for affective symptoms. Using an ACE model, IQ and visual-spatial learning showed statistically significant genetic correlations with bipolar disorder (rg = |0.51|-|1.00|), which remained significant after covarying for affective symptoms. Verbal episodic and spatial working memory capture a modest fraction of the bipolar diathesis. IQ and visual-spatial learning may tap into genetic substrates of non-affective symptomatology in bipolar disorder. © The Royal College of Psychiatrists 2016.

Simple sequence repeat (SSR) markers analysis of genetic diversity ...

African Journals Online (AJOL)

hope&shola

2012-04-24

Apr 24, 2012 ... erucic acid in the oil and low glucosinolate content in the meal has made rapeseed a valuable source of high quality oil for people and nutritional protein for live-stock. (Qiu et al., 2006). Previous studies have demonstrated that yellow seeds have a thinner seed coat than black seeds in the same genetic ...

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models.

Science.gov (United States)

Vanderick, S; Troch, T; Gillon, A; Glorieux, G; Gengler, N

2014-12-01

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33,155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85,118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice. © 2014 Blackwell Verlag GmbH.

Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

Science.gov (United States)

Forutan, M; Ansari Mahyari, S; Sargolzaei, M

2015-02-01

Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. © 2014 Blackwell Verlag GmbH.

Genetic Aspects of Autism Spectrum Disorders: Insights from Animal Models

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Swati eBanerjee

2014-02-01

Full Text Available Autism spectrum disorders (ASD are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute towards the formation, stabilization and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD.

The Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES)

Science.gov (United States)

Kuwayama, Y.; Mabee, B.; Wulf Tregar, S.

2017-12-01

National and international organizations are placing greater emphasis on the societal and economic benefits that can be derived from applications of Earth observations, yet improvements are needed to connect to the decision processes that produce actions with direct societal benefits. There is a need to substantiate the benefits of Earth science applications in socially and economically meaningful terms in order to demonstrate return on investment and to prioritize investments across data products, modeling capabilities, and information systems. However, methods and techniques for quantifying the value proposition of Earth observations are currently not fully established. Furthermore, it has been challenging to communicate the value of these investments to audiences beyond the Earth science community. The Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES), a cooperative agreement between Resources for the Future (RFF) and the National Aeronautics and Space Administration (NASA), has the goal of advancing methods for the valuation and communication of the applied benefits linked with Earth observations. The VALUABLES Consortium will focus on three pillars: (a) a research pillar that will apply existing and innovative methods to quantify the socioeconomic benefits of information from Earth observations; (b) a capacity building pillar to catalyze interdisciplinary linkages between Earth scientists and social scientists; and (c) a communications pillar that will convey the value of Earth observations to stakeholders in government, universities, the NGO community, and the interested public. In this presentation, we will describe ongoing and future activities of the VALUABLES Consortium, provide a brief overview of frameworks to quantify the socioeconomic value of Earth observations, and describe how Earth scientists and social scientist can get involved in the Consortium's activities.

Use of Genetic Models to Study the Urinary Concentrating Mechanism

DEFF Research Database (Denmark)

Olesen, Emma Tina Bisgaard; Kortenoeven, Marleen L.A.; Fenton, Robert A.

2015-01-01

technology is providing critical new information about urinary concentrating processes and thus mechanisms for maintaining body water homeostasis. In this chapter we provide a brief overview of genetic mouse model generation, and then summarize findings in transgenic and knockout mice pertinent to our...

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Application of genetic algorithm in modeling on-wafer inductors for up to 110 Ghz

Science.gov (United States)

Liu, Nianhong; Fu, Jun; Liu, Hui; Cui, Wenpu; Liu, Zhihong; Liu, Linlin; Zhou, Wei; Wang, Quan; Guo, Ao

2018-05-01

In this work, the genetic algorithm has been introducted into parameter extraction for on-wafer inductors for up to 110 GHz millimeter-wave operations, and nine independent parameters of the equivalent circuit model are optimized together. With the genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the preliminary parameters without optimization. Especially, the fitting accuracy of the Q value achieves a significant improvement after the optimization.

Analysis of conditional genetic effects and variance components in developmental genetics.

Science.gov (United States)

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Potential genetic polymorphisms predicting polycystic ovary syndrome

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Yao Chen

2018-05-01

Full Text Available Polycystic ovary syndrome (PCOS is a heterogenous endocrine disorder with typical symptoms of oligomenorrhoea, hyperandrogenism, hirsutism, obesity, insulin resistance and increased risk of type 2 diabetes mellitus. Extensive evidence indicates that PCOS is a genetic disease and numerous biochemical pathways have been linked with its pathogenesis. A number of genes from these pathways have been investigated, which include those involved with steroid hormone biosynthesis and metabolism, action of gonadotropin and gonadal hormones, folliculogenesis, obesity and energy regulation, insulin secretion and action and many others. In this review, we summarize the historical and recent findings in genetic polymorphisms of PCOS from the relevant publications and outline some genetic polymorphisms that are potentially associated with the risk of PCOS. This information could uncover candidate genes associating with PCOS, which will be valuable for the development of novel diagnostic and treatment platforms for PCOS patients.

Advances in genetic detection of kidney disease

International Nuclear Information System (INIS)

Dosekun, Akinsan K.; Foringer, John R.; Kone, Bruce C.

2003-01-01

The Human Genome Project has provided a vast amount of molecular genetic information for the analysis of normal and diseased genes. This new information provides new opportunities for precise diagnosis, assessment of predisposition and risk factors and novel therapeutic strategies. At the same time, this constantly expanding knowledge base represents on e of the most difficult challenges in molecular medicine. For monogenic disease nearly 2000 human disease genes have thus for been identified. Most of these conditions are characterized by large mutational variation and even greater phenotypic variation. In nephrology, several genetic diseases have been elucidated that provide new insight into the structure, function and developmental biology of the glomerulus, tubules and urogenital tracts, as well as renal cell tumors. Great improvements in the diagnostic resolution of genetic diseases have been achieved, such that single base pair mutations can be readily detected. Because of accurate diagnosis and risk assessment, genetic testing may be valuable in improving disease management and preventive care when genotype-specific therapies are available. Moreover, such testing may identify de novo mutations and potentially aid in understanding the disease process. This review summarizes recent advances in the renal genetic database and methods for genetic testing of renal diseases. (author)

Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm.

Science.gov (United States)

Yan, Jingwen; Du, Lei; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-09-01

Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single-nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. The complexity of these datasets has presented critical bioinformatics challenges that require new enabling tools. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. However, most of the existing SCCA algorithms are designed using the soft thresholding method, which assumes that the input features are independent from one another. This assumption clearly does not hold for the imaging genetic data. In this article, we propose a new knowledge-guided SCCA algorithm (KG-SCCA) to overcome this limitation as well as improve learning results by incorporating valuable prior knowledge. The proposed KG-SCCA method is able to model two types of prior knowledge: one as a group structure (e.g. linkage disequilibrium blocks among SNPs) and the other as a network structure (e.g. gene co-expression network among brain regions). The new model incorporates these prior structures by introducing new regularization terms to encourage weight similarity between grouped or connected features. A new algorithm is designed to solve the KG-SCCA model without imposing the independence constraint on the input features. We demonstrate the effectiveness of our algorithm with both synthetic and real data. For real data, using an Alzheimer's disease (AD) cohort, we examine the imaging genetic associations between all SNPs in the APOE gene (i.e. top AD gene) and amyloid deposition measures among cortical regions (i.e. a major AD hallmark). In comparison with a widely used SCCA implementation, our KG-SCCA algorithm produces not only improved cross-validation performances but also biologically meaningful

Mapping of the stochastic Lotka-Volterra model to models of population genetics and game theory

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Constable, George W. A.; McKane, Alan J.

2017-08-01

The relationship between the M -species stochastic Lotka-Volterra competition (SLVC) model and the M -allele Moran model of population genetics is explored via timescale separation arguments. When selection for species is weak and the population size is large but finite, precise conditions are determined for the stochastic dynamics of the SLVC model to be mappable to the neutral Moran model, the Moran model with frequency-independent selection, and the Moran model with frequency-dependent selection (equivalently a game-theoretic formulation of the Moran model). We demonstrate how these mappings can be used to calculate extinction probabilities and the times until a species' extinction in the SLVC model.

Genetic Algorithms Principles Towards Hidden Markov Model

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Nabil M. Hewahi

2011-10-01

Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.

Chemical event chain model of coupled genetic oscillators.

Science.gov (United States)

Jörg, David J; Morelli, Luis G; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Chemical event chain model of coupled genetic oscillators

Science.gov (United States)

Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

Science.gov (United States)

Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

2013-01-01

In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications

International Nuclear Information System (INIS)

Blaifi, S.; Moulahoum, S.; Colak, I.; Merrouche, W.

2016-01-01

Highlights: • We proposed a developed dynamic battery model suitable for photovoltaic systems. • We used genetic algorithm optimization method to find parameters that gives minimized error. • The validation was carried out with real measurements from stand-alone photovoltaic string. - Abstract: Modeling of batteries in photovoltaic systems has been a major issue related to the random dynamic regime imposed by the changes of solar irradiation and ambient temperature added to the complexity of battery electrochemical and electrical behaviors. However, various approaches have been proposed to model the battery behavior by predicting from detailed electrochemical, electrical or analytical models to high-level stochastic models. In this paper, an improvement of dynamic electrical battery model is proposed by automatic parameter extraction using genetic algorithm in order to give usefulness and future implementation for practical application. It is highlighted that the enhancement of 21 values of the parameters of CEIMAT model presents a good agreement with real measurements for different modes like charge or discharge and various conditions.

Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

Science.gov (United States)

Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

2014-01-01

Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

Genetic evaluation of European quails by random regression models

Directory of Open Access Journals (Sweden)

Flaviana Miranda Gonçalves

2012-09-01

Full Text Available The objective of this study was to compare different random regression models, defined from different classes of heterogeneity of variance combined with different Legendre polynomial orders for the estimate of (covariance of quails. The data came from 28,076 observations of 4,507 female meat quails of the LF1 lineage. Quail body weights were determined at birth and 1, 14, 21, 28, 35 and 42 days of age. Six different classes of residual variance were fitted to Legendre polynomial functions (orders ranging from 2 to 6 to determine which model had the best fit to describe the (covariance structures as a function of time. According to the evaluated criteria (AIC, BIC and LRT, the model with six classes of residual variances and of sixth-order Legendre polynomial was the best fit. The estimated additive genetic variance increased from birth to 28 days of age, and dropped slightly from 35 to 42 days. The heritability estimates decreased along the growth curve and changed from 0.51 (1 day to 0.16 (42 days. Animal genetic and permanent environmental correlation estimates between weights and age classes were always high and positive, except for birth weight. The sixth order Legendre polynomial, along with the residual variance divided into six classes was the best fit for the growth rate curve of meat quails; therefore, they should be considered for breeding evaluation processes by random regression models.

Genetic Programming for Automatic Hydrological Modelling

Science.gov (United States)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

Science.gov (United States)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

Nature and nurture: environmental influences on a genetic rat model of depression.

Science.gov (United States)

Mehta-Raghavan, N S; Wert, S L; Morley, C; Graf, E N; Redei, E E

2016-03-29

In this study, we sought to learn whether adverse events such as chronic restraint stress (CRS), or 'nurture' in the form of environmental enrichment (EE), could modify depression-like behavior and blood biomarker transcript levels in a genetic rat model of depression. The Wistar Kyoto More Immobile (WMI) is a genetic model of depression that aided in the identification of blood transcriptomic markers, which successfully distinguished adolescent and adult subjects with major depressive disorders from their matched no-disorder controls. Here, we followed the effects of CRS and EE in adult male WMIs and their genetically similar control strain, the Wistar Kyoto Less Immobile (WLI), that does not show depression-like behavior, by measuring the levels of these transcripts in the blood and hippocampus. In WLIs, increased depression-like behavior and transcriptomic changes were present in response to CRS, but in WMIs no behavioral or additive transcriptomic changes occurred. Environmental enrichment decreased both the inherent depression-like behavior in the WMIs and the behavioral difference between WMIs and WLIs, but did not reverse basal transcript level differences between the strains. The inverse behavioral change induced by CRS and EE in the WLIs did not result in parallel inverse expression changes of the transcriptomic markers, suggesting that these behavioral responses to the environment work via separate molecular pathways. In contrast, 'trait' transcriptomic markers with expression differences inherent and unchanging between the strains regardless of the environment suggest that in our model, environmental and genetic etiologies of depression work through independent molecular mechanisms.

Development of useful genetic resources by proton-beam irradiation

International Nuclear Information System (INIS)

Kim, In Gyu; Kim, Kug Chan; Park, Hyi Gook; Jung, Il Lae; Seo, Yong Won; Chang, Chul Seong; Kim, Jae Yoon; Ham, Jae Woong

2005-08-01

The aim of this study is to develop new, useful and high-valuable genetic resources through the overproduction of biodegradable plastics and the propagation of wheat using proton-beam irradiation. Useful host strain was isolated through the mutagenization of the Escherichia coli K-12 strain, followed by characterizing the genetic and physiological properties of the E. coli mutant strains. The selected E. coli mutant strain produced above 85g/L of PHB, showed above 99% of PHB intracellular content and spontaneously liberated intracellular PHB granules. Based on the results, the production cost of PHB has been estimated to approximately 2$/kg, leading effective cost-down. Investigated the propagation of wheat and its variation, a selectable criterion of wet pro of was established and genetic analysis of useful mutant was carried out

Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China.

Directory of Open Access Journals (Sweden)

Hong-Lian Ruan

Full Text Available To date, the only established model for assessing risk for nasopharyngeal carcinoma (NPC relies on the sero-status of the Epstein-Barr virus (EBV. By contrast, the risk assessment models proposed here include environmental risk factors, family history of NPC, and information on genetic variants. The models were developed using epidemiological and genetic data from a large case-control study, which included 1,387 subjects with NPC and 1,459 controls of Cantonese origin. The predictive accuracy of the models were then assessed by calculating the area under the receiver-operating characteristic curves (AUC. To compare the discriminatory improvement of models with and without genetic information, we estimated the net reclassification improvement (NRI and integrated discrimination index (IDI. Well-established environmental risk factors for NPC include consumption of salted fish and preserved vegetables and cigarette smoking (in pack years. The environmental model alone shows modest discriminatory ability (AUC = 0.68; 95% CI: 0.66, 0.70, which is only slightly increased by the addition of data on family history of NPC (AUC = 0.70; 95% CI: 0.68, 0.72. With the addition of data on genetic variants, however, our model's discriminatory ability rises to 0.74 (95% CI: 0.72, 0.76. The improvements in NRI and IDI also suggest the potential usefulness of considering genetic variants when screening for NPC in endemic areas. If these findings are confirmed in larger cohort and population-based case-control studies, use of the new models to analyse data from NPC-endemic areas could well lead to earlier detection of NPC.

Novel extractants with high selectivity for valuable metals in seawater. Calixarene derivatives

International Nuclear Information System (INIS)

Kakoi, Takahiko; Goto, Masahiro

1997-01-01

Seawater contains various valuable metals such as uranium and lithium. Therefore, attempts are being made to develop highly selective extractants which recognize target metal ions in reclaimed seawater. In this review, we have focused our study on the application of novel cyclic compound calixarene based extractants. A novel host compound calixarene, which is a cyclic compound connecting some phenol rings, is capable of forming several different extractant ring sizes and introducing various kinds of functional groups towards targeting of metal ions in seawater. Therefore, calixarene derivatives are capable of extracting valuable metals such as uranium, alkaline metals, heavy metals, rare earth metals and noble metals selectively by varying structural ring size and functional groups. The novel host compound calixarene has given promising results which line it up as a potential extractant for the separation of valuable metal ions in seawater. (author)

A genetic algorithm for solving supply chain network design model

Science.gov (United States)

Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.

2013-09-01

Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.

Estimating the actual subject-specific genetic correlations in behavior genetics.

Science.gov (United States)

Molenaar, Peter C M

2012-10-01

Generalization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

A Tri-Part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning about Authentic Genetics Dilemmas

Science.gov (United States)

Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

2015-01-01

Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational…

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

Science.gov (United States)

Li, J; Qiu, J; Tang, Z; Shen, L

1992-01-01

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

Directory of Open Access Journals (Sweden)

Maria Gabriela Campolina Diniz Peixoto

2014-05-01

Full Text Available The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524 of test-day milk yield (TDMY from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects, whereas the contemporary group, calving age (linear and quadratic effects and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Genetic variation architecture of mitochondrial genome reveals the differentiation in Korean landrace and weedy rice

OpenAIRE

Wei Tong; Qiang He; Yong-Jin Park

2017-01-01

Mitochondrial genome variations have been detected despite the overall conservation of this gene content, which has been valuable for plant population genetics and evolutionary studies. Here, we describe mitochondrial variation architecture and our performance of a phylogenetic dissection of Korean landrace and weedy rice. A total of 4,717 variations across the mitochondrial genome were identified adjunct with 10 wild rice. Genetic diversity assessment revealed that wild rice has higher nucle...

Genetic algorithms used for PWRs refuel management automatic optimization: a new modelling

International Nuclear Information System (INIS)

Chapot, Jorge Luiz C.; Schirru, Roberto; Silva, Fernando Carvalho da

1996-01-01

A Genetic Algorithms-based system, linking the computer codes GENESIS 5.0 and ANC through the interface ALGER, has been developed aiming the PWRs fuel management optimization. An innovative codification, the Lists Model, has been incorporated to the genetic system, which avoids the use of variants of the standard crossover operator and generates only valid loading patterns in the core. The GENESIS/ALGER/ANC system has been successfully tested in an optimization study for Angra-1 second cycle. (author)

Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

Science.gov (United States)

Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

2017-12-01

1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

Cost optimization model and its heuristic genetic algorithms

International Nuclear Information System (INIS)

Liu Wei; Wang Yongqing; Guo Jilin

1999-01-01

Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model

A genetic model of progressively partial melting for uranium-bearing granites in south China

International Nuclear Information System (INIS)

Zhai Jianping.

1989-01-01

A genetic model of progressively partial and enrichment mechanism of uranium during partial melting of the sources of material studied and the significance of the genetic model in search of uranium deposits is elaborated. This model accounts better for some geological and geochemical features of uranium-bearing granties and suspects the traditional idea that igneous uranium-bearing granites were formed by fusion of U-rich strata surrounding these granites. Finally this paper points out that the infuence of U-rich strata of wall rocks of granites over uranium-bearing granites depends on variation of water solubility in the magma and assimilation of magma to wall rocks during its ascending and crystallization

Genetic complexity in a Drosophila model of diabetes-associated misfolded human proinsulin.

Science.gov (United States)

Park, Soo-Young; Ludwig, Michael Z; Tamarina, Natalia A; He, Bin Z; Carl, Sarah H; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Williams, Calvin L; Miles, Cecelia M; Philipson, Louis H; Steiner, Donald F; Bell, Graeme I; Kreitman, Martin

2014-02-01

Drosophila melanogaster has been widely used as a model of human Mendelian disease, but its value in modeling complex disease has received little attention. Fly models of complex disease would enable high-resolution mapping of disease-modifying loci and the identification of novel targets for therapeutic intervention. Here, we describe a fly model of permanent neonatal diabetes mellitus and explore the complexity of this model. The approach involves the transgenic expression of a misfolded mutant of human preproinsulin, hINS(C96Y), which is a cause of permanent neonatal diabetes. When expressed in fly imaginal discs, hINS(C96Y) causes a reduction of adult structures, including the eye, wing, and notum. Eye imaginal discs exhibit defects in both the structure and the arrangement of ommatidia. In the wing, expression of hINS(C96Y) leads to ectopic expression of veins and mechano-sensory organs, indicating disruption of wild-type signaling processes regulating cell fates. These readily measurable "disease" phenotypes are sensitive to temperature, gene dose, and sex. Mutant (but not wild-type) proinsulin expression in the eye imaginal disc induces IRE1-mediated XBP1 alternative splicing, a signal for endoplasmic reticulum stress response activation, and produces global change in gene expression. Mutant hINS transgene tester strains, when crossed to stocks from the Drosophila Genetic Reference Panel, produce F1 adults with a continuous range of disease phenotypes and large broad-sense heritability. Surprisingly, the severity of mutant hINS-induced disease in the eye is not correlated with that in the notum in these crosses, nor with eye reduction phenotypes caused by the expression of two dominant eye mutants acting in two different eye development pathways, Drop (Dr) or Lobe (L), when crossed into the same genetic backgrounds. The tissue specificity of genetic variability for mutant hINS-induced disease has, therefore, its own distinct signature. The genetic dominance

Genetic Segregation Analysis of a Rapeseed Dwarf Mutant

International Nuclear Information System (INIS)

Xiang, G.; Yu, S.; Zhang, T.; Zhao, J.; Lei, S.; Du, C.

2016-01-01

Dwarf resources in Brassica napus are very important for developing high-yield cultivars through dwarf-type and lodging-resistant breeding. However, few dwarf varieties have been available for this species. Here, we reported a new rapeseed dwarf mutant GRC1157, which exhibits obvious phenotypic variations on dwarf. Six generations (P /sub 1/, P/sub 1/, F/sub 1/, F/sub 1/, B/sub 1/, and B/sub 1/) were produced from a cross between dwarf mutant GRC1157 and an elite tall-type line XR16 to analyze genetic inheritances of plant height (PH), numbers of the 1st valid branch (VBN), main inflorescence length (MIL), pod numbers per main inflorescence (MPN), pod length (PL) and seed numbers per pod (PSN) using the mixed major gene plus polygene inheritance model. The genetic analysis shows different traits were controlled by different inheritance models: PH and PL by two pairs of additive-dominant-epistatic major genes plus additive-dominant-epistatic polygenes, MPN and PSN by two-pair additive-dominant-epistatic major genes plus additive-dominant polygenes, MIL by two-pair additive-dominant-epistatic major genes and VBN by one-pair additive-dominant major genes plus additive-dominant-epistatic polygenes. Furthermore, positive correlations between PH and some other traits were observed, suggesting that some traits may be co-regulated by several linkage or same loci/genes. In addition, high heritability (40.35-93.7 percent) were found for five traits (except VBN) in different segregating generations, indicating these traits were mainly affected by hereditary factors and suitable for early artificial selection. In sum, the dwarf mutant GRC1157 can serve as a valuable resource for rapeseed dwarf breeding and the genetic analysis in this study provided a foundation for further mapping and cloning dwarf genes in mutant GRC1157. (author)

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

Science.gov (United States)

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Human Urine-Derived Renal Progenitors for Personalized Modeling of Genetic Kidney Disorders.

Science.gov (United States)

Lazzeri, Elena; Ronconi, Elisa; Angelotti, Maria Lucia; Peired, Anna; Mazzinghi, Benedetta; Becherucci, Francesca; Conti, Sara; Sansavini, Giulia; Sisti, Alessandro; Ravaglia, Fiammetta; Lombardi, Duccio; Provenzano, Aldesia; Manonelles, Anna; Cruzado, Josep M; Giglio, Sabrina; Roperto, Rosa Maria; Materassi, Marco; Lasagni, Laura; Romagnani, Paola

2015-08-01

The critical role of genetic and epigenetic factors in the pathogenesis of kidney disorders is gradually becoming clear, and the need for disease models that recapitulate human kidney disorders in a personalized manner is paramount. In this study, we describe a method to select and amplify renal progenitor cultures from the urine of patients with kidney disorders. Urine-derived human renal progenitors exhibited phenotype and functional properties identical to those purified from kidney tissue, including the capacity to differentiate into tubular cells and podocytes, as demonstrated by confocal microscopy, Western blot analysis of podocyte-specific proteins, and scanning electron microscopy. Lineage tracing studies performed with conditional transgenic mice, in which podocytes are irreversibly tagged upon tamoxifen treatment (NPHS2.iCreER;mT/mG), that were subjected to doxorubicin nephropathy demonstrated that renal progenitors are the only urinary cell population that can be amplified in long-term culture. To validate the use of these cells for personalized modeling of kidney disorders, renal progenitors were obtained from (1) the urine of children with nephrotic syndrome and carrying potentially pathogenic mutations in genes encoding for podocyte proteins and (2) the urine of children without genetic alterations, as validated by next-generation sequencing. Renal progenitors obtained from patients carrying pathogenic mutations generated podocytes that exhibited an abnormal cytoskeleton structure and functional abnormalities compared with those obtained from patients with proteinuria but without genetic mutations. The results of this study demonstrate that urine-derived patient-specific renal progenitor cultures may be an innovative research tool for modeling of genetic kidney disorders. Copyright © 2015 by the American Society of Nephrology.

Genetic diversity of a Daugava basin brown trout (Salmo trutta brood stock

Directory of Open Access Journals (Sweden)

Schmidt Thomas

2017-01-01

Full Text Available Genetics play an increasingly important role in the conservation of threatened fish populations. We have examined twelve microsatellite markers to determine the genetic diversity of a brood stock of brown trout from the Latvian Daugava river basin, used in a local supportive breeding program and compared diversity values to other Baltic populations. Allelic data was further inspected for indications of increased inbreeding. Additionally, we have analyzed the mitochondrial control region to classify the population within a broader phylogenetic framework. We found that the genetic diversity was comparatively low, but there was no strong evidence of high inbreeding. A newly detected mitochondrial haplotype indicates unnoticed genetic diversity of “Atlantic lineage” brown trout in the Daugava basin region. Our study provides first genetic details on resident brown trout from the Baltic Daugava river basin to improve the regional conservation management of this valuable genetic resource and contributes phylogeographically useful information.

Genetic compatibility determines endophyte-grass combinations.

Directory of Open Access Journals (Sweden)

Kari Saikkonen

Full Text Available Even highly mutually beneficial microbial-plant interactions, such as mycorrhizal- and rhizobial-plant exchanges, involve selfishness, cheating and power-struggles between the partners, which depending on prevailing selective pressures, lead to a continuum of interactions from antagonistic to mutualistic. Using manipulated grass-endophyte combinations in a five year common garden experiment, we show that grass genotypes and genetic mismatches constrain genetic combinations between the vertically (via host seeds transmitted endophytes and the out-crossing host, thereby reducing infections in established grass populations. Infections were lost in both grass tillers and seedlings in F(1 and F(2 generations, respectively. Experimental plants were collected as seeds from two different environments, i.e., meadows and nearby riverbanks. Endophyte-related benefits to the host included an increased number of inflorescences, but only in meadow plants and not until the last growing season of the experiment. Our results illustrate the importance of genetic host specificity and trans-generational maternal effects on the genetic structure of a host population, which act as destabilizing forces in endophyte-grass symbioses. We propose that (1 genetic mismatches may act as a buffering mechanism against highly competitive endophyte-grass genotype combinations threatening the biodiversity of grassland communities and (2 these mismatches should be acknowledged, particularly in breeding programmes aimed at harnessing systemic and heritable endophytes to improve the agriculturally valuable characteristics of cultivars.

Population genetics of the Asian tiger mosquito Aedes albopictus, an invasive vector of human diseases

Science.gov (United States)

Goubert, C; Minard, G; Vieira, C; Boulesteix, M

2016-01-01

The Asian tiger mosquito Aedes albopictus is currently one of the most threatening invasive species in the world. Native to Southeast Asia, the species has spread throughout the world in the past 30 years and is now present in every continent but Antarctica. Because it was the main vector of recent Dengue and Chikungunya outbreaks, and because of its competency for numerous other viruses and pathogens such as the Zika virus, A. albopictus stands out as a model species for invasive diseases vector studies. A synthesis of the current knowledge about the genetic diversity of A. albopictus is needed, knowing the interplays between the vector, the pathogens, the environment and their epidemiological consequences. Such resources are also valuable for assessing the role of genetic diversity in the invasive success. We review here the large but sometimes dispersed literature about the population genetics of A. albopictus. We first debate about the experimental design of these studies and present an up-to-date assessment of the available molecular markers. We then summarize the main genetic characteristics of natural populations and synthesize the available data regarding the worldwide structuring of the vector. Finally, we pinpoint the gaps that remain to be addressed and suggest possible research directions. PMID:27273325

Genetic Programming and Standardization in Water Temperature Modelling

Directory of Open Access Journals (Sweden)

Maritza Arganis

2009-01-01

Full Text Available An application of Genetic Programming (an evolutionary computational tool without and with standardization data is presented with the aim of modeling the behavior of the water temperature in a river in terms of meteorological variables that are easily measured, to explore their explanatory power and to emphasize the utility of the standardization of variables in order to reduce the effect of those with large variance. Recorded data corresponding to the water temperature behavior at the Ebro River, Spain, are used as analysis case, showing a performance improvement on the developed model when data are standardized. This improvement is reflected in a reduction of the mean square error. Finally, the models obtained in this document were applied to estimate the water temperature in 2004, in order to provide evidence about their applicability to forecasting purposes.

Consequences of the genetic threshold model for observing partial migration under climate change scenarios.

Science.gov (United States)

Cobben, Marleen M P; van Noordwijk, Arie J

2017-10-01

Migration is a widespread phenomenon across the animal kingdom as a response to seasonality in environmental conditions. Partially migratory populations are populations that consist of both migratory and residential individuals. Such populations are very common, yet their stability has long been debated. The inheritance of migratory activity is currently best described by the threshold model of quantitative genetics. The inclusion of such a genetic threshold model for migratory behavior leads to a stable zone in time and space of partially migratory populations under a wide range of demographic parameter values, when assuming stable environmental conditions and unlimited genetic diversity. Migratory species are expected to be particularly sensitive to global warming, as arrival at the breeding grounds might be increasingly mistimed as a result of the uncoupling of long-used cues and actual environmental conditions, with decreasing reproduction as a consequence. Here, we investigate the consequences for migratory behavior and the stability of partially migratory populations under five climate change scenarios and the assumption of a genetic threshold value for migratory behavior in an individual-based model. The results show a spatially and temporally stable zone of partially migratory populations after different lengths of time in all scenarios. In the scenarios in which the species expands its range from a particular set of starting populations, the genetic diversity and location at initialization determine the species' colonization speed across the zone of partial migration and therefore across the entire landscape. Abruptly changing environmental conditions after model initialization never caused a qualitative change in phenotype distributions, or complete extinction. This suggests that climate change-induced shifts in species' ranges as well as changes in survival probabilities and reproductive success can be met with flexibility in migratory behavior at the

Dissecting the genetic architecture of frost tolerance in Central European winter wheat.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Würschum, Tobias; Longin, C Friedrich H; Korzun, Viktor; Kollers, Sonja; Schachschneider, Ralf; Zeng, Jian; Fernando, Rohan; Dubcovsky, Jorge; Reif, Jochen C

2013-11-01

Abiotic stress tolerance in plants is pivotal to increase yield stability, but its genetic basis is still poorly understood. To gain insight into the genetic architecture of frost tolerance, this work evaluated a large mapping population of 1739 wheat (Triticum aestivum L.) lines and hybrids adapted to Central Europe in field trials in Germany and fingerprinted the lines with a 9000 single-nucleotide polymorphism array. Additive effects prevailed over dominance effects. A two-dimensional genome scan revealed the presence of epistatic effects. Genome-wide association mapping in combination with a robust cross-validation strategy identified one frost tolerance locus with a major effect located on chromosome 5B. This locus was not in linkage disequilibrium with the known frost loci Fr-B1 and Fr-B2. The use of the detected diagnostic markers on chromosome 5B, however, does not allow prediction of frost tolerance with high accuracy. Application of genome-wide selection approaches that take into account also loci with small effect sizes considerably improved prediction of the genetic variation of frost tolerance in wheat. The developed prediction model is valuable for improving frost tolerance because this trait displays a wide variation in occurrence across years and is therefore a difficult target for conventional phenotypic selection.

Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

Science.gov (United States)

Furlotte, Nicholas A; Eskin, Eleazar

2015-05-01

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

Directory of Open Access Journals (Sweden)

Lubna Moin

2009-04-01

Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

The intrapreneur: A distinct and valuable role to be institutionalized and strategically managed

DEFF Research Database (Denmark)

Ashourizadeh, Shayegheh; Schøtt, Thomas

are distinct from routine employees and somewhat similar to entrepreneurs. Thereby intrapreneurs are a human resource that by developing new activities for their employer and also by creating new jobs is very valuable. – The rate of intrapreneurship among employees is higher in Denmark than in almost all other......, especially in Denmark, to adopt strategies for institutionalization and management of this human resource....... more frequently than routine employees are self-efficacious, opportunity-perceiving, risk-willing and role-modeling starters, have meaningful and autonomous jobs, and are satisfied with their jobs and salary, but also experience more stress in work; and in these job-characteristics intrapreneurs...

Genetic human prion disease modelled in PrP transgenic Drosophila.

Science.gov (United States)

Thackray, Alana M; Cardova, Alzbeta; Wolf, Hanna; Pradl, Lydia; Vorberg, Ina; Jackson, Walker S; Bujdoso, Raymond

2017-09-20

Inherited human prion diseases, such as fatal familial insomnia (FFI) and familial Creutzfeldt-Jakob disease (fCJD), are associated with autosomal dominant mutations in the human prion protein gene PRNP and accumulation of PrP Sc , an abnormal isomer of the normal host protein PrP C , in the brain of affected individuals. PrP Sc is the principal component of the transmissible neurotoxic prion agent. It is important to identify molecular pathways and cellular processes that regulate prion formation and prion-induced neurotoxicity. This will allow identification of possible therapeutic interventions for individuals with, or at risk from, genetic human prion disease. Increasingly, Drosophila has been used to model human neurodegenerative disease. An important unanswered question is whether genetic prion disease with concomitant spontaneous prion formation can be modelled in Drosophila We have used pUAST/PhiC31-mediated site-directed mutagenesis to generate Drosophila transgenic for murine or hamster PrP (prion protein) that carry single-codon mutations associated with genetic human prion disease. Mouse or hamster PrP harbouring an FFI (D178N) or fCJD (E200K) mutation showed mild Proteinase K resistance when expressed in Drosophila Adult Drosophila transgenic for FFI or fCJD variants of mouse or hamster PrP displayed a spontaneous decline in locomotor ability that increased in severity as the flies aged. Significantly, this mutant PrP-mediated neurotoxic fly phenotype was transferable to recipient Drosophila that expressed the wild-type form of the transgene. Collectively, our novel data are indicative of the spontaneous formation of a PrP-dependent neurotoxic phenotype in FFI- or CJD-PrP transgenic Drosophila and show that inherited human prion disease can be modelled in this invertebrate host. © 2017 The Author(s).

Application of hierarchical genetic models to Raven and WAIS subtests: a Dutch twin study

NARCIS (Netherlands)

Rijsdijk, F.V.; Vernon, P.A.; Boomsma, D.I.

2002-01-01

Hierarchical models of intelligence are highly informative and widely accepted. Application of these models to twin data, however, is sparse. This paper addresses the question of how a genetic hierarchical model fits the Wechsler Adult Intelligence Scale (WAIS) subtests and the Raven Standard

Modeling Self-Healing of Concrete Using Hybrid Genetic Algorithm-Artificial Neural Network.

Science.gov (United States)

Ramadan Suleiman, Ahmed; Nehdi, Moncef L

2017-02-07

This paper presents an approach to predicting the intrinsic self-healing in concrete using a hybrid genetic algorithm-artificial neural network (GA-ANN). A genetic algorithm was implemented in the network as a stochastic optimizing tool for the initial optimal weights and biases. This approach can assist the network in achieving a global optimum and avoid the possibility of the network getting trapped at local optima. The proposed model was trained and validated using an especially built database using various experimental studies retrieved from the open literature. The model inputs include the cement content, water-to-cement ratio (w/c), type and dosage of supplementary cementitious materials, bio-healing materials, and both expansive and crystalline additives. Self-healing indicated by means of crack width is the model output. The results showed that the proposed GA-ANN model is capable of capturing the complex effects of various self-healing agents (e.g., biochemical material, silica-based additive, expansive and crystalline components) on the self-healing performance in cement-based materials.

FAMILY THOUGHT IN THE RUSSIAN LANGUAGE MODEL OF THE WORLD: HISTORY OF THE VALUABLE RELATION TO A FAMILY ACCORDING TO RUSSIAN

Directory of Open Access Journals (Sweden)

G. S. Samoylova

2016-01-01

Full Text Available The article consider the structure of a word meaning a family in diachronic aspect. The valuable attitude towards concept «family» is characteristic of the entire periods in the history of Russian, and transformation of semantics of the word concept is insignificant. The central idea in definition of a family in modern Russian is the idea of spiritual proximity of people, the close emotional relations. The word is actively used in figurative sense for expression of estimated meanings. In a different way there is a history of values of the terms of relationship entering a theme group «family». In modern Russian these words cease to express a positive emotional assessment at the use in relation to not relatives. According to authors, it demonstrates change of valuable reference points in a modern language picture of the world.

Modeling AEC—New Approaches to Study Rare Genetic Disorders

Science.gov (United States)

Koch, Peter J.; Dinella, Jason; Fete, Mary; Siegfried, Elaine C.; Koster, Maranke I.

2015-01-01

Ankyloblepharon-ectodermal defects-cleft lip/palate (AEC) syndrome is a rare monogenetic disorder that is characterized by severe abnormalities in ectoderm-derived tissues, such as skin and its appendages. A major cause of morbidity among affected infants is severe and chronic skin erosions. Currently, supportive care is the only available treatment option for AEC patients. Mutations in TP63, a gene that encodes key regulators of epidermal development, are the genetic cause of AEC. However, it is currently not clear how mutations in TP63 lead to the various defects seen in the patients’ skin. In this review, we will discuss current knowledge of the AEC disease mechanism obtained by studying patient tissue and genetically engineered mouse models designed to mimic aspects of the disorder. We will then focus on new approaches to model AEC, including the use of patient cells and stem cell technology to replicate the disease in a human tissue culture model. The latter approach will advance our understanding of the disease and will allow for the development of new in vitro systems to identify drugs for the treatment of skin erosions in AEC patients. Further, the use of stem cell technology, in particular induced pluripotent stem cells (iPSC), will enable researchers to develop new therapeutic approaches to treat the disease using the patient’s own cells (autologous keratinocyte transplantation) after correction of the disease-causing mutations. PMID:24665072

Molecular genetics of cancer and tumorigenesis: Drosophila models

Institute of Scientific and Technical Information of China (English)

Wu-Min Deng

2011-01-01

Why do some cells not respond to normal control of cell division and become tumorous? Which signals trigger some tumor cells to migrate and colonize other tissues? What genetic factors are responsible for tumorigenesis and cancer development? What environmental factors play a role in cancer formation and progression? In how many ways can our bodies prevent and restrict the growth of cancerous cells?How can we identify and deliver effective drugs to fight cancer? In the fight against cancer,which kills more people than any other disease,these and other questions have long interested researchers from a diverse range of fields.To answer these questions and to fight cancer more effectively,we must increase our understanding of basic cancer biology.Model organisms,including the fruit fly Drosophila melanogaster,have played instrumental roles in our understanding of this devastating disease and the search for effective cures.Drosophila and its highly effective,easy-touse,and ever-expanding genetic tools have contributed toand enriched our knowledge of cancer and tumor formation tremendously.

Testing for biases in selection on avian reproductive traits and partitioning direct and indirect selection using quantitative genetic models.

Science.gov (United States)

Reed, Thomas E; Gienapp, Phillip; Visser, Marcel E

2016-10-01

Key life history traits such as breeding time and clutch size are frequently both heritable and under directional selection, yet many studies fail to document microevolutionary responses. One general explanation is that selection estimates are biased by the omission of correlated traits that have causal effects on fitness, but few valid tests of this exist. Here, we show, using a quantitative genetic framework and six decades of life-history data on two free-living populations of great tits Parus major, that selection estimates for egg-laying date and clutch size are relatively unbiased. Predicted responses to selection based on the Robertson-Price Identity were similar to those based on the multivariate breeder's equation (MVBE), indicating that unmeasured covarying traits were not missing from the analysis. Changing patterns of phenotypic selection on these traits (for laying date, linked to climate change) therefore reflect changing selection on breeding values, and genetic constraints appear not to limit their independent evolution. Quantitative genetic analysis of correlational data from pedigreed populations can be a valuable complement to experimental approaches to help identify whether apparent associations between traits and fitness are biased by missing traits, and to parse the roles of direct versus indirect selection across a range of environments. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Experiencing the genetic body: parents' encounters with pediatric clinical genetics.

Science.gov (United States)

Raspberry, Kelly; Skinner, Debra

2007-01-01

Because of advancements in genetic research and technologies, the clinical practice of genetics is becoming a prevalent component of biomedicine. As the genetic basis for more and more diseases are found, it is possible that ways of experiencing health, illness, identity, kin relations, and the body are becoming geneticized, or understood within a genetic model of disease. Yet, other models and relations that go beyond genetic explanations also shape interpretations of health and disease. This article explores how one group of individuals for whom genetic disorder is highly relevant formulates their views of the body in light of genetic knowledge. Using data from an ethnographic study of 106 parents or potential parents of children with known or suspected genetic disorders who were referred to a pediatric genetic counseling and evaluation clinic in the southeastern United States, we find that these parents do, to some degree, perceive of their children's disorders in terms of a genetic body that encompasses two principal qualities: a sense of predetermined health and illness and an awareness of a profound historicity that reaches into the past and extends into the present and future. They experience this genetic body as both fixed and historical, but they also express ideas of a genetic body made less deterministic by their own efforts and future possibilities. This account of parents' experiences with genetics and clinical practice contributes to a growing body of work on the ways in which genetic information and technologies are transforming popular and medical notions of the body, and with it, health, illness, kinship relations, and personal and social identities.

Evaluating the Genetics of Common Variable Immunodeficiency: Monogenetic Model and Beyond

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Guillem de Valles-Ibáñez

2018-05-01

Full Text Available Common variable immunodeficiency (CVID is the most frequent symptomatic primary immunodeficiency characterized by recurrent infections, hypogammaglobulinemia and poor response to vaccines. Its diagnosis is made based on clinical and immunological criteria, after exclusion of other diseases that can cause similar phenotypes. Currently, less than 20% of cases of CVID have a known underlying genetic cause. We have analyzed whole-exome sequencing and copy number variants data of 36 children and adolescents diagnosed with CVID and healthy relatives to estimate the proportion of monogenic cases. We have replicated an association of CVID to p.C104R in TNFRSF13B and reported the second case of homozygous patient to date. Our results also identify five causative genetic variants in LRBA, CTLA4, NFKB1, and PIK3R1, as well as other very likely causative variants in PRKCD, MAPK8, or DOCK8 among others. We experimentally validate the effect of the LRBA stop-gain mutation which abolishes protein production and downregulates the expression of CTLA4, and of the frameshift indel in CTLA4 producing expression downregulation of the protein. Our results indicate a monogenic origin of at least 15–24% of the CVID cases included in the study. The proportion of monogenic patients seems to be lower in CVID than in other PID that have also been analyzed by whole exome or targeted gene panels sequencing. Regardless of the exact proportion of CVID monogenic cases, other genetic models have to be considered for CVID. We propose that because of its prevalence and other features as intermediate penetrancies and phenotypic variation within families, CVID could fit with other more complex genetic scenarios. In particular, in this work, we explore the possibility of CVID being originated by an oligogenic model with the presence of heterozygous mutations in interacting proteins or by the accumulation of detrimental variants in particular immunological pathways, as well as

Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

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Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

2003-11-01

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

Assessment of Genetic Diversity and Population Genetic Structure of Corylus mandshurica in China Using SSR Markers.

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Zong, Jian-Wei; Zhao, Tian-Tian; Ma, Qing-Hua; Liang, Li-Song; Wang, Gui-Xi

2015-01-01

Corylus mandshurica, also known as pilose hazelnut, is an economically and ecologically important species in China. In this study, ten polymorphic simple sequence repeat (SSR) markers were applied to evaluate the genetic diversity and population structure of 348 C. mandshurica individuals among 12 populations in China. The SSR markers expressed a relatively high level of genetic diversity (Na = 15.3, Ne = 5.6604, I = 1.8853, Ho = 0.6668, and He = 0.7777). According to the coefficient of genetic differentiation (Fst = 0.1215), genetic variation within the populations (87.85%) were remarkably higher than among populations (12.15%). The average gene flow (Nm = 1.8080) significantly impacts the genetic structure of C. mandshurica populations. The relatively high gene flow (Nm = 1.8080) among wild C. mandshurica may be caused by wind-pollinated flowers, highly nutritious seeds and self-incompatible mating system. The UPGMA (unweighted pair group method of arithmetic averages) dendrogram was divided into two main clusters. Moreover, the results of STRUCTURE analysis suggested that C. mandshurica populations fell into two main clusters. Comparison of the UPGMA dendrogram and the Bayesian STRUCTURE analysis showed general agreement between the population subdivisions and the genetic relationships among populations of C. mandshurica. Group I accessions were located in Northeast China, while Group II accessions were in North China. It is worth noting that a number of genetically similar populations were located in the same geographic region. The results further showed that there was obvious genetic differentiation among populations from Northeast China to North China. Results from the Mantel test showed a weak but still significant positive correlation between Nei's genetic distance and geographic distance (km) among populations (r = 0.419, P = 0.005), suggesting that genetic differentiation in the 12 C. mandshurica populations might be related to geographic distance. These

Assessment of Genetic Diversity and Population Genetic Structure of Corylus mandshurica in China Using SSR Markers.

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Jian-Wei Zong

Full Text Available Corylus mandshurica, also known as pilose hazelnut, is an economically and ecologically important species in China. In this study, ten polymorphic simple sequence repeat (SSR markers were applied to evaluate the genetic diversity and population structure of 348 C. mandshurica individuals among 12 populations in China. The SSR markers expressed a relatively high level of genetic diversity (Na = 15.3, Ne = 5.6604, I = 1.8853, Ho = 0.6668, and He = 0.7777. According to the coefficient of genetic differentiation (Fst = 0.1215, genetic variation within the populations (87.85% were remarkably higher than among populations (12.15%. The average gene flow (Nm = 1.8080 significantly impacts the genetic structure of C. mandshurica populations. The relatively high gene flow (Nm = 1.8080 among wild C. mandshurica may be caused by wind-pollinated flowers, highly nutritious seeds and self-incompatible mating system. The UPGMA (unweighted pair group method of arithmetic averages dendrogram was divided into two main clusters. Moreover, the results of STRUCTURE analysis suggested that C. mandshurica populations fell into two main clusters. Comparison of the UPGMA dendrogram and the Bayesian STRUCTURE analysis showed general agreement between the population subdivisions and the genetic relationships among populations of C. mandshurica. Group I accessions were located in Northeast China, while Group II accessions were in North China. It is worth noting that a number of genetically similar populations were located in the same geographic region. The results further showed that there was obvious genetic differentiation among populations from Northeast China to North China. Results from the Mantel test showed a weak but still significant positive correlation between Nei's genetic distance and geographic distance (km among populations (r = 0.419, P = 0.005, suggesting that genetic differentiation in the 12 C. mandshurica populations might be related to geographic

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

Science.gov (United States)

De Haas, Y; Janss, L L G; Kadarmideen, H N

2007-10-01

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

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Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

Global Status of Genetically Modified Crops: Current Trends and Prospects

OpenAIRE

Hautea, Randy A.

2002-01-01

Modern biotechnology-facilitated crop improvement is undoubtedly one of the most significant technological developments in agriculture. The first wave of genetically-modified (GM) or transgenic crops include cultivars with important input traits such as herbicide tolerance and insect resistance. Future products are expected to provide benefits that could include tolerance to environmental stresses and enhanced nutritional content, which can be particularly valuable in crops that are important...

Parameters Calculation of ZnO Surge Arrester Models by Genetic Algorithms

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A. Bayadi

2006-09-01

Full Text Available This paper proposes to provide a new technique based on the genetic algorithm to obtain the best possible series of values of the parameters of the ZnO surge arresters models. The validity of the predicted parameters is then checked by comparing the results predicted with the experimental results available in the literature. Using the ATP-EMTP package an application of the arrester model on network system studies is presented and discussed.

Comparing ESC and iPSC?Based Models for Human Genetic Disorders

OpenAIRE

Halevy, Tomer; Urbach, Achia

2014-01-01

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients’ somatic cells, and the ne...

Genetic diversity of high performance cultivars of upland and irrigated Brazilian rice.

Science.gov (United States)

Coelho, G R C; Brondani, C; Hoffmann, L V; Valdisser, P A M R; Borba, T C O; Mendonça, J A; Rodrigues, L A; de Menezes, I P P

2017-09-21

The objective of this study was to analyze the diversity and discrimination of high-performance Brazilian rice cultivars using microsatellite markers. Twenty-nine rice cultivars belonging to EMBRAPA Arroz e Feijão germplasm bank in Brazil were genotyped by 24 SSR markers to establish their structure and genetic discrimination. It was demonstrated that the analyzed germplasm of rice presents an expressive and significant genetic diversity with low heterogeneity among the cultivars. All 29 cultivars were differentiated genetically, and were organized into two groups related to their upland and irrigated cultivation systems. These groups showed a high genetic differentiation, with greater diversity within the group that includes the cultivars for irrigated system. The genotyping data of these cultivars, with the morphological e phenotypical data, are valuable information to be used by rice breeding programs to develop new improved cultivars.

Transcriptome profile and unique genetic evolution of positively selected genes in yak lungs.

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Lan, DaoLiang; Xiong, XianRong; Ji, WenHui; Li, Jian; Mipam, Tserang-Donko; Ai, Yi; Chai, ZhiXin

2018-04-01

The yak (Bos grunniens), which is a unique bovine breed that is distributed mainly in the Qinghai-Tibetan Plateau, is considered a good model for studying plateau adaptability in mammals. The lungs are important functional organs that enable animals to adapt to their external environment. However, the genetic mechanism underlying the adaptability of yak lungs to harsh plateau environments remains unknown. To explore the unique evolutionary process and genetic mechanism of yak adaptation to plateau environments, we performed transcriptome sequencing of yak and cattle (Bos taurus) lungs using RNA-Seq technology and a subsequent comparison analysis to identify the positively selected genes in the yak. After deep sequencing, a normal transcriptome profile of yak lung that containing a total of 16,815 expressed genes was obtained, and the characteristics of yak lungs transcriptome was described by functional analysis. Furthermore, Ka/Ks comparison statistics result showed that 39 strong positively selected genes are identified from yak lungs. Further GO and KEGG analysis was conducted for the functional annotation of these genes. The results of this study provide valuable data for further explorations of the unique evolutionary process of high-altitude hypoxia adaptation in yaks in the Tibetan Plateau and the genetic mechanism at the molecular level.

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

Science.gov (United States)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

MVT a most valuable theorem

CERN Document Server

Smorynski, Craig

2017-01-01

This book is about the rise and supposed fall of the mean value theorem. It discusses the evolution of the theorem and the concepts behind it, how the theorem relates to other fundamental results in calculus, and modern re-evaluations of its role in the standard calculus course. The mean value theorem is one of the central results of calculus. It was called “the fundamental theorem of the differential calculus” because of its power to provide simple and rigorous proofs of basic results encountered in a first-year course in calculus. In mathematical terms, the book is a thorough treatment of this theorem and some related results in the field; in historical terms, it is not a history of calculus or mathematics, but a case study in both. MVT: A Most Valuable Theorem is aimed at those who teach calculus, especially those setting out to do so for the first time. It is also accessible to anyone who has finished the first semester of the standard course in the subject and will be of interest to undergraduate mat...

Genetic Diversity Analysis of Medicinally Important Horticultural Crop Aegle marmelos by ISSR Markers.

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Mujeeb, Farina; Bajpai, Preeti; Pathak, Neelam; Verma, Smita Rastogi

2017-01-01

Inter simple sequence repeat (ISSR) markers help in identifying and determining the extent of genetic diversity in cultivars. Here, we describe their application in determining the genetic diversity of bael (Aegle marmelos Corr.). Universal ISSR primers are selected and their marker characteristics such as polymorphism information content, effective multiplex ratio and marker index have been evaluated. ISSR-PCR is then performed using universal ISSR primers to generate polymorphic bands. This information is used to determine the degree of genetic similarity among the bael varieties/accessions by cluster analysis using unweighted pair-group method with arithmetic averages (UPGMA). This technology is valuable for biodiversity conservation and for making an efficient choice of parents in breeding programs.

Poisson versus threshold models for genetic analysis of clinical mastitis in US Holsteins.

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Vazquez, A I; Weigel, K A; Gianola, D; Bates, D M; Perez-Cabal, M A; Rosa, G J M; Chang, Y M

2009-10-01

Typically, clinical mastitis is coded as the presence or absence of disease in a given lactation, and records are analyzed with either linear models or binary threshold models. Because the presence of mastitis may include cows with multiple episodes, there is a loss of information when counts are treated as binary responses. Poisson models are appropriated for random variables measured as the number of events, and although these models are used extensively in studying the epidemiology of mastitis, they have rarely been used for studying the genetic aspects of mastitis. Ordinal threshold models are pertinent for ordered categorical responses; although one can hypothesize that the number of clinical mastitis episodes per animal reflects a continuous underlying increase in mastitis susceptibility, these models have rarely been used in genetic analysis of mastitis. The objective of this study was to compare probit, Poisson, and ordinal threshold models for the genetic evaluation of US Holstein sires for clinical mastitis. Mastitis was measured as a binary trait or as the number of mastitis cases. Data from 44,908 first-parity cows recorded in on-farm herd management software were gathered, edited, and processed for the present study. The cows were daughters of 1,861 sires, distributed over 94 herds. Predictive ability was assessed via a 5-fold cross-validation using 2 loss functions: mean squared error of prediction (MSEP) as the end point and a cost difference function. The heritability estimates were 0.061 for mastitis measured as a binary trait in the probit model and 0.085 and 0.132 for the number of mastitis cases in the ordinal threshold and Poisson models, respectively; because of scale differences, only the probit and ordinal threshold models are directly comparable. Among healthy animals, MSEP was smallest for the probit model, and the cost function was smallest for the ordinal threshold model. Among diseased animals, MSEP and the cost function were smallest

Salt Lakes of the African Rift System: A Valuable Research ...

African Journals Online (AJOL)

Salt Lakes of the African Rift System: A Valuable Research Opportunity for Insight into Nature's Concenrtated Multi-Electrolyte Science. JYN Philip, DMS Mosha. Abstract. The Tanzanian rift system salt lakes present significant cultural, ecological, recreational and economical values. Beyond the wealth of minerals, resources ...

An Adaptive Agent-Based Model of Homing Pigeons: A Genetic Algorithm Approach

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Francis Oloo

2017-01-01

Full Text Available Conventionally, agent-based modelling approaches start from a conceptual model capturing the theoretical understanding of the systems of interest. Simulation outcomes are then used “at the end” to validate the conceptual understanding. In today’s data rich era, there are suggestions that models should be data-driven. Data-driven workflows are common in mathematical models. However, their application to agent-based models is still in its infancy. Integration of real-time sensor data into modelling workflows opens up the possibility of comparing simulations against real data during the model run. Calibration and validation procedures thus become automated processes that are iteratively executed during the simulation. We hypothesize that incorporation of real-time sensor data into agent-based models improves the predictive ability of such models. In particular, that such integration results in increasingly well calibrated model parameters and rule sets. In this contribution, we explore this question by implementing a flocking model that evolves in real-time. Specifically, we use genetic algorithms approach to simulate representative parameters to describe flight routes of homing pigeons. The navigation parameters of pigeons are simulated and dynamically evaluated against emulated GPS sensor data streams and optimised based on the fitness of candidate parameters. As a result, the model was able to accurately simulate the relative-turn angles and step-distance of homing pigeons. Further, the optimised parameters could replicate loops, which are common patterns in flight tracks of homing pigeons. Finally, the use of genetic algorithms in this study allowed for a simultaneous data-driven optimization and sensitivity analysis.

Comparative genetics: synergizing human and NOD mouse studies for identifying genetic causation of type 1 diabetes.

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Driver, John P; Chen, Yi-Guang; Mathews, Clayton E

2012-01-01

Although once widely anticipated to unlock how human type 1 diabetes (T1D) develops, extensive study of the nonobese diabetic (NOD) mouse has failed to yield effective treatments for patients with the disease. This has led many to question the usefulness of this animal model. While criticism about the differences between NOD and human T1D is legitimate, in many cases disease in both species results from perturbations modulated by the same genes or different genes that function within the same biological pathways. Like in humans, unusual polymorphisms within an MHC class II molecule contributes the most T1D risk in NOD mice. This insight supports the validity of this model and suggests the NOD has been improperly utilized to study how to cure or prevent disease in patients. Indeed, clinical trials are far from administering T1D therapeutics to humans at the same concentration ranges and pathological states that inhibit disease in NOD mice. Until these obstacles are overcome it is premature to label the NOD mouse a poor surrogate to test agents that cure or prevent T1D. An additional criticism of the NOD mouse is the past difficulty in identifying genes underlying T1D using conventional mapping studies. However, most of the few diabetogenic alleles identified to date appear relevant to the human disorder. This suggests that rather than abandoning genetic studies in NOD mice, future efforts should focus on improving the efficiency with which diabetes susceptibility genes are detected. The current review highlights why the NOD mouse remains a relevant and valuable tool to understand the genes and their interactions that promote autoimmune diabetes and therapeutics that inhibit this disease. It also describes a new range of technologies that will likely transform how the NOD mouse is used to uncover the genetic causes of T1D for years to come.

A Comparison of Telephone Genetic Counseling and In-Person Genetic Counseling from the Genetic Counselor's Perspective.

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Burgess, Kelly R; Carmany, Erin P; Trepanier, Angela M

2016-02-01

Growing demand for and limited geographic access to genetic counseling services is increasing the need for alternative service delivery models (SDM) like telephone genetic counseling (TGC). Little research has been done on genetic counselors' perspectives of the practice of TGC. We created an anonymous online survey to assess whether telephone genetic counselors believed the tasks identified in the ABGC (American Board of Genetic Counseling) Practice Analysis were performed similarly or differently in TGC compared to in person genetic counseling (IPGC). If there were differences noted, we sought to determine the nature of the differences and if additional training might be needed to address them. Eighty eight genetic counselors with experience in TGC completed some or all of the survey. Respondents identified differences in 13 (14.8%) of the 88 tasks studied. The tasks identified as most different in TGC were: "establishing rapport through verbal and nonverbal interactions" (60.2%; 50/83 respondents identified the task as different), "recognizing factors affecting the counseling interaction" (47.8%; 32/67), "assessing client/family emotions, support, etc." (40.1%; 27/66) and "educating clients about basic genetic concepts" (35.6%; 26/73). A slight majority (53.8%; 35/65) felt additional training was needed to communicate information without visual aids and more effectively perform psychosocial assessments. In summary, although a majority of genetic counseling tasks are performed similarly between TGC and IPGC, TGC counselors recognize that specific training in the TGC model may be needed to address the key differences.

Non invasive methods for genetic analysis applied to ecological and behavioral studies in Latino-America

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Susana González

2007-07-01

Full Text Available Documenting the presence and abundance of the neotropical mammals is the first step for understanding their population ecology, behavior and genetic dynamics in designing conservation plans. The combination of field research with molecular genetics techniques are new tools that provide valuable biological information avoiding the disturbance in the ecosystems, trying to minimize the human impact in the process to gather biological information. The objective of this paper is to review the available non invasive sampling techniques that have been used in Neotropical mammal studies to apply to determine the presence and abundance, population structure, sex ratio, taxonomic diagnostic using mitochondrial markers, and assessing genetic variability using nuclear markers. There are a wide range of non invasive sampling techniques used to determine the species identification that inhabit an area such as searching for tracks, feces, and carcasses. Other useful equipment is the camera traps that can generate an image bank that can be valuable to assess species presence and abundance by morphology. With recent advances in molecular biology, it is now possible to use the trace amounts of DNA in feces and amplify it to analyze the species diversity in an area, and the genetic variability at intraspecific level. This is particularly helpful in cases of sympatric and cryptic species in which morphology failed to diagnose the taxonomic status of several species of brocket deer of the genus Mazama.

Genetic characterization and improved genotyping of the dysferlin-deficient mouse strain Dysf (tm1Kcam).

Science.gov (United States)

Wiktorowicz, Tatiana; Kinter, Jochen; Kobuke, Kazuhiro; Campbell, Kevin P; Sinnreich, Michael

2015-01-01

Mouse models of dysferlinopathies are valuable tools with which to investigate the pathomechanisms underlying these diseases and to test novel therapeutic strategies. One such mouse model is the Dysf (tm1Kcam) strain, which was generated using a targeting vector to replace a 12-kb region of the dysferlin gene and which features a progressive muscular dystrophy. A prerequisite for successful animal studies using genetic mouse models is an accurate genotyping protocol. Unfortunately, the lack of robustness of currently available genotyping protocols for the Dysf (tm1Kcam) mouse has prevented efficient colony management. Initial attempts to improve the genotyping protocol based on the published genomic structure failed. These difficulties led us to analyze the targeted locus of the dysferlin gene of the Dysf (tm1Kcam) mouse in greater detail. In this study we resequenced and analyzed the targeted locus of the Dysf (tm1Kcam) mouse and developed a novel PCR protocol for genotyping. We found that instead of a deletion, the dysferlin locus in the Dysf (tm1Kcam) mouse carries a targeted insertion. This genetic characterization enabled us to establish a reliable method for genotyping of the Dysf (tm1Kcam) mouse, and thus has made efficient colony management possible. Our work will make the Dysf (tm1Kcam) mouse model more attractive for animal studies of dysferlinopathies.

Genetic coding and united-hypercomplex systems in the models of algebraic biology.

Science.gov (United States)

Petoukhov, Sergey V

2017-08-01

Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

Deficits in fine motor skills in a genetic animal model of ADHD

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Qian Yu

2010-09-01

Full Text Available Abstract Background In an attempt to model some behavioral aspects of Attention Deficit/Hyperactivity Disorder (ADHD, we examined whether an existing genetic animal model of ADHD is valid for investigating not only locomotor hyperactivity, but also more complex motor coordination problems displayed by the majority of children with ADHD. Methods We subjected young adolescent Spontaneously Hypertensive Rats (SHRs, the most commonly used genetic animal model of ADHD, to a battery of tests for motor activity, gross motor coordination, and skilled reaching. Wistar (WIS rats were used as controls. Results Similar to children with ADHD, young adolescent SHRs displayed locomotor hyperactivity in a familiar, but not in a novel environment. They also had lower performance scores in a complex skilled reaching task when compared to WIS rats, especially in the most sensitive measure of skilled performance (i.e., single attempt success. In contrast, their gross motor performance on a Rota-Rod test was similar to that of WIS rats. Conclusion The results support the notion that the SHR strain is a useful animal model system to investigate potential molecular mechanisms underlying fine motor skill problems in children with ADHD.

OPTIMIZATION OF LAND USE SUITABILITY FOR AGRICULTURE USING INTEGRATED GEOSPATIAL MODEL AND GENETIC ALGORITHMS

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S. B. Mansor

2012-08-01

Full Text Available In this study, a geospatial model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the infrastructural preference. The model was developed based on multi-agent genetic algorithm. The model was customized to accommodate the constraint set for the study area, namely the resource saving and environmental-friendly. The model was then applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Menderjan Basin in Iran. The first task was to study the dominant crops and economic suitability evaluation of land. Second task was to determine the fitness function for the genetic algorithms. The third objective was to optimize the land use map using economical benefits. The results has indicated that the proposed model has much better performance for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.

Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Directory of Open Access Journals (Sweden)

Guosheng Su

Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

The Drosophila melanogaster host model

Science.gov (United States)

Igboin, Christina O.; Griffen, Ann L.; Leys, Eugene J.

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed. PMID:22368770

The Drosophila melanogaster host model

Directory of Open Access Journals (Sweden)

Christina O. Igboin

2012-02-01

Full Text Available The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed.

The Drosophila melanogaster host model.

Science.gov (United States)

Igboin, Christina O; Griffen, Ann L; Leys, Eugene J

2012-01-01

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen-host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial-host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis-host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed.

FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

Science.gov (United States)

De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.

2013-02-01

We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.

Methods for genetic transformation in Dendrobium.

Science.gov (United States)

da Silva, Jaime A Teixeira; Dobránszki, Judit; Cardoso, Jean Carlos; Chandler, Stephen F; Zeng, Songjun

2016-03-01

The genetic transformation of Dendrobium orchids will allow for the introduction of novel colours, altered architecture and valuable traits such as abiotic and biotic stress tolerance. The orchid genus Dendrobium contains species that have both ornamental value and medicinal importance. There is thus interest in producing cultivars that have increased resistance to pests, novel horticultural characteristics such as novel flower colours, improved productivity, longer flower spikes, or longer post-harvest shelf-life. Tissue culture is used to establish clonal plants while in vitro flowering allows for the production of flowers or floral parts within a sterile environment, expanding the selection of explants that can be used for tissue culture or genetic transformation. The latter is potentially the most effective, rapid and practical way to introduce new agronomic traits into Dendrobium. Most (69.4 %) Dendrobium genetic transformation studies have used particle bombardment (biolistics) while 64 % have employed some form of Agrobacterium-mediated transformation. A singe study has explored ovary injection, but no studies exist on floral dip transformation. While most of these studies have involved the use of selector or reporter genes, there are now a handful of studies that have introduced genes for horticulturally important traits.

Using Genetically Engineered Animal Models in the Postgenomic Era to Understand Gene Function in Alcoholism

Science.gov (United States)

Reilly, Matthew T.; Harris, R. Adron; Noronha, Antonio

2012-01-01

Over the last 50 years, researchers have made substantial progress in identifying genetic variations that underlie the complex phenotype of alcoholism. Not much is known, however, about how this genetic variation translates into altered biological function. Genetic animal models recapitulating specific characteristics of the human condition have helped elucidate gene function and the genetic basis of disease. In particular, major advances have come from the ability to manipulate genes through a variety of genetic technologies that provide an unprecedented capacity to determine gene function in the living organism and in alcohol-related behaviors. Even newer genetic-engineering technologies have given researchers the ability to control when and where a specific gene or mutation is activated or deleted, allowing investigators to narrow the role of the gene’s function to circumscribed neural pathways and across development. These technologies are important for all areas of neuroscience, and several public and private initiatives are making a new generation of genetic-engineering tools available to the scientific community at large. Finally, high-throughput “next-generation sequencing” technologies are set to rapidly increase knowledge of the genome, epigenome, and transcriptome, which, combined with genetically engineered mouse mutants, will enhance insight into biological function. All of these resources will provide deeper insight into the genetic basis of alcoholism. PMID:23134044

Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines

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Riedelsheimer Christian

2012-09-01

Full Text Available Abstract Background There is increasing empirical evidence that whole-genome prediction (WGP is a powerful tool for predicting line and hybrid performance in maize. However, there is a lack of knowledge about the sensitivity of WGP models towards the genetic architecture of the trait. Whereas previous studies exclusively focused on highly polygenic traits, important agronomic traits such as disease resistances, nutrifunctional or climate adaptational traits have a genetic architecture which is either much less complex or unknown. For such cases, information about model robustness and guidelines for model selection are lacking. Here, we compared five WGP models with different assumptions about the distribution of the underlying genetic effects. As contrasting model traits, we chose three highly polygenic agronomic traits and three metabolites each with a major QTL explaining 22 to 30% of the genetic variance in a panel of 289 diverse maize inbred lines genotyped with 56,110 SNPs. Results We found the five WGP models to be remarkable robust towards trait architecture with the largest differences in prediction accuracies ranging between 0.05 and 0.14 for the same trait, most likely as the result of the high level of linkage disequilibrium prevailing in elite maize germplasm. Whereas RR-BLUP performed best for the agronomic traits, it was inferior to LASSO or elastic net for the three metabolites. We found the approach of genome partitioning of genetic variance, first applied in human genetics, as useful in guiding the breeder which model to choose, if prior knowledge of the trait architecture is lacking. Conclusions Our results suggest that in diverse germplasm of elite maize inbred lines with a high level of LD, WGP models differ only slightly in their accuracies, irrespective of the number and effects of QTL found in previous linkage or association mapping studies. However, small gains in prediction accuracies can be achieved if the WGP model is

Molecular Population Genetics.

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Casillas, Sònia; Barbadilla, Antonio

2017-03-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

Genotype-phenotype correlations in neurogenetics: Lesch-Nyhan disease as a model disorder.

Science.gov (United States)

Fu, Rong; Ceballos-Picot, Irene; Torres, Rosa J; Larovere, Laura E; Yamada, Yasukazu; Nguyen, Khue V; Hegde, Madhuri; Visser, Jasper E; Schretlen, David J; Nyhan, William L; Puig, Juan G; O'Neill, Patrick J; Jinnah, H A

2014-05-01

Establishing meaningful relationships between genetic variations and clinical disease is a fundamental goal for all human genetic disorders. However, these genotype-phenotype correlations remain incompletely characterized and sometimes conflicting for many diseases. Lesch-Nyhan disease is an X-linked recessive disorder that is caused by a wide variety of mutations in the HPRT1 gene. The gene encodes hypoxanthine-guanine phosphoribosyl transferase, an enzyme involved in purine metabolism. The fine structure of enzyme has been established by crystallography studies, and its function can be measured with very precise biochemical assays. This rich knowledge of genetic alterations in the gene and their functional effect on its protein product provides a powerful model for exploring factors that influence genotype-phenotype correlations. The present study summarizes 615 known genetic mutations, their influence on the gene product, and their relationship to the clinical phenotype. In general, the results are compatible with the concept that the overall severity of the disease depends on how mutations ultimately influence enzyme activity. However, careful evaluation of exceptions to this concept point to several additional genetic and non-genetic factors that influence genotype-phenotype correlations. These factors are not unique to Lesch-Nyhan disease, and are relevant to most other genetic diseases. The disease therefore serves as a valuable model for understanding the challenges associated with establishing genotype-phenotype correlations for other disorders.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

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Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops

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Ru, Sushan; Hardner, Craig; Carter, Patrick A; Evans, Kate; Main, Dorrie; Peace, Cameron

2016-01-01

Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations—known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available. PMID:27148453

Complete restoration of multiple dystrophin isoforms in genetically corrected Duchenne muscular dystrophy patient–derived cardiomyocytes

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Susi Zatti

2014-01-01

Full Text Available Duchenne muscular dystrophy (DMD–associated cardiac diseases are emerging as a major cause of morbidity and mortality in DMD patients, and many therapies for treatment of skeletal muscle failed to improve cardiac function. The reprogramming of patients' somatic cells into pluripotent stem cells, combined with technologies for correcting the genetic defect, possesses great potential for the development of new treatments for genetic diseases. In this study, we obtained human cardiomyocytes from DMD patient–derived, induced pluripotent stem cells genetically corrected with a human artificial chromosome carrying the whole dystrophin genomic sequence. Stimulation by cytokines was combined with cell culturing on hydrogel with physiological stiffness, allowing an adhesion-dependent maturation and a proper dystrophin expression. The obtained cardiomyocytes showed remarkable sarcomeric organization of cardiac troponin T and α-actinin, expressed cardiac-specific markers, and displayed electrically induced calcium transients lasting less than 1 second. We demonstrated that the human artificial chromosome carrying the whole dystrophin genomic sequence is stably maintained throughout the cardiac differentiation process and that multiple promoters of the dystrophin gene are properly activated, driving expression of different isoforms. These dystrophic cardiomyocytes can be a valuable source for in vitro modeling of DMD-associated cardiac disease. Furthermore, the derivation of genetically corrected, patient-specific cardiomyocytes represents a step toward the development of innovative cell and gene therapy approaches for DMD.

Automated Test Assembly for Cognitive Diagnosis Models Using a Genetic Algorithm

Science.gov (United States)

Finkelman, Matthew; Kim, Wonsuk; Roussos, Louis A.

2009-01-01

Much recent psychometric literature has focused on cognitive diagnosis models (CDMs), a promising class of instruments used to measure the strengths and weaknesses of examinees. This article introduces a genetic algorithm to perform automated test assembly alongside CDMs. The algorithm is flexible in that it can be applied whether the goal is to…

Estimation of the frequency of occult mutations for an autosomal recessive disease in the presence of genetic heterogeneity: application to genetic hearing loss disorders.

Science.gov (United States)

Kimberling, William J

2005-11-01

The routine testing for pathologic mutation(s) in a patient's DNA has become the foundation of modern molecular genetic diagnosis. It is especially valuable when the phenotype shows genetic heterogeneity, and its importance will grow as treatments become genotype specific. However, the technology of mutation detection is imperfect and mutations are often missed. This can be especially troublesome when dealing with a recessive disorder where the combination of genetic heterogeneity and missed mutation creates an imprecision in the genotypic assessment of individuals who do not appear to have the expected complement of two pathologic mutations. This article describes a statistical approach to the estimation of the likelihood of a genetic diagnosis under these conditions. In addition to providing a means of testing for missed mutations, it also provides a method of estimating and testing for the presence of genetic heterogeneity in the absence of linkage data. Gene frequencies as well as estimates of sensitivity and specificity can be obtained as well. The test is applied to GJB2 recessive nonsyndromic deafness, Usher syndrome types Ib and IIa, and Pendred-enlarged vestibular aqueduct syndrome. Copyright 2005 Wiley-Liss, Inc.

Strategies for MCMC computation in quantitative genetics

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Ibanez, Noelia; 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 but with a sp......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...

Assessing Website Quality in Context: Retrieving Information about Genetically Modified Food on the Web

Science.gov (United States)

McInerney, Claire R.; Bird, Nora J.

2005-01-01

Introduction: Knowing the credibility of information about genetically modified food on the Internet is critical to the everyday life information seeking of consumers as they form opinions about this nascent agricultural technology. The Website Quality Evaluation Tool (WQET) is a valuable instrument that can be used to determine the credibility of…

Genetic analysis of partial egg production records in Japanese quail using random regression models.

Science.gov (United States)

Abou Khadiga, G; Mahmoud, B Y F; Farahat, G S; Emam, A M; El-Full, E A

2017-08-01

The main objectives of this study were to detect the most appropriate random regression model (RRM) to fit the data of monthly egg production in 2 lines (selected and control) of Japanese quail and to test the consistency of different criteria of model choice. Data from 1,200 female Japanese quails for the first 5 months of egg production from 4 consecutive generations of an egg line selected for egg production in the first month (EP1) was analyzed. Eight RRMs with different orders of Legendre polynomials were compared to determine the proper model for analysis. All criteria of model choice suggested that the adequate model included the second-order Legendre polynomials for fixed effects, and the third-order for additive genetic effects and permanent environmental effects. Predictive ability of the best model was the highest among all models (ρ = 0.987). According to the best model fitted to the data, estimates of heritability were relatively low to moderate (0.10 to 0.17) showed a descending pattern from the first to the fifth month of production. A similar pattern was observed for permanent environmental effects with greater estimates in the first (0.36) and second (0.23) months of production than heritability estimates. Genetic correlations between separate production periods were higher (0.18 to 0.93) than their phenotypic counterparts (0.15 to 0.87). The superiority of the selected line over the control was observed through significant (P egg production in earlier ages (first and second months) than later ones. A methodology based on random regression animal models can be recommended for genetic evaluation of egg production in Japanese quail. © 2017 Poultry Science Association Inc.

Geographic, genetic and life-history variability in a sex-changing fish

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Chiara Benvenuto

2015-11-01

Full Text Available Sequential hermaphroditism, commonly referred to as sex change or sex reversal, is a striking phenomenon in mating-system evolution and the most remarkable example of sexual plasticity. Among vertebrates, it is specific to teleosts. Some fish species reproduce initially as females and then change into males (protogynous hermaphrodites or vice versa (protandrous hermaphrodites. The white sea bream, Diplodus sargus, exhibits a high degree of sexual plasticity: populations have been reported to be gonochoristic, protandrous or digynic (with primary females, derived from intersexual juveniles, and secondary females, derived from males. We analysed populations collected from eight different locations across the species distribution range (between the Mediterranean and the North-Eastern Atlantic. These populations are characterized by different degrees of connectivity, spatial demographics and life histories. Using individual-based analyses, we linked the genetic structure of each specimen with environmental heterogeneity, life-history traits and reproductive modes. Our aim is to gather a better understanding of the variation in reproductive life-history strategies in this sexually plastic species. Diplodus sargus is a valuable candidate organism to investigate sequential hermaphroditism and it also has a commercial value. The application of population genetics tools against the background of life-history theory can bring valuable insights for the management of marine resources. The geographical patterns of sex change (and of age- and size-at-sex change linked with population genetics can be pivotal for both theoretical investigations and conservation and management plans in marine areas.

Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

OpenAIRE

Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

2010-01-01

Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

Assessing Website quality in context: retrieving information about genetically modified food on the Web

Directory of Open Access Journals (Sweden)

Claire R. McInerney

2005-01-01

Full Text Available Introduction. Knowing the credibility of information about genetically modified food on the Internet is critical to the everyday life information seeking of consumers as they form opinions about this nascent agricultural technology. The Website Quality Evaluation Tool (WQET is a valuable instrument that can be used to determine the credibility of Websites on any topic. Method. This study sought to use the WQET to determine the quality of Websites in the context of biotechnology or genetically modified food and to seek one or more easily identified characteristics, such as bias, commitment, use of metatags and site update-access interval (length of time between last update of the site and the date reviewed that might be used as a quick discriminator of a Website's quality. Analysis. Using SPSS, ANOVA and regression analyses were performed with the website variables of a population of one hundred Websites about genetically modified food. Results. Only the site update-access interval was determined to be a shortcut quality indicator with an inverse relationship. The longer the interval the lower the quality score. Conclusion. The study established a model for Website quality evaluation. The update-access interval proved to be the single clear-cut indicator to judge Website quality in everyday information seeking.

Genetic study of Pea (Pisum sativum L.) mutants with changed shape and/or dentation of leaves

International Nuclear Information System (INIS)

Naidenova, N.

2001-01-01

The purpose of this study is to describe the morphological differences between normal plants and mutants (due to irradiation) with different shape and/or dentation of leaflets and to evaluate their productivity and genetic potential. Dry seeds have been submitted to gamma irradiation with doses 100 Gy, 150 Gy and 200 Gy.The mutants studies in this research introduce an important source for further investigation of genetics of the mutant traits - dentation of leaflets, shape and especially flowering time that is controlled by genetically determined responses to photo period and temperature. Due to the clear phenotypic expression of the shape and leaves in some plants it is considered that the development of the leaves mutants is and important finding for pea genetics making tham valuable morphological markers for genetic investigations

an assessment of timber trees producing valuable fruits and seeds ...

African Journals Online (AJOL)

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It is observed that most of the timber trees producing valuable fruits and seeds have low ... sector of the economy by providing major raw materials (saw logs, ... the trees also produce industrial raw materials like latex, ... villagers while avoiding some of the ecological costs of ..... enzymes of rats with carbon tetrachloride.

Genetic basis of hindlimb loss in a naturally occurring vertebrate model

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Emily K. Don

2016-03-01

Full Text Available Here we genetically characterise pelvic finless, a naturally occurring model of hindlimb loss in zebrafish that lacks pelvic fin structures, which are homologous to tetrapod hindlimbs, but displays no other abnormalities. Using a hybrid positional cloning and next generation sequencing approach, we identified mutations in the nuclear localisation signal (NLS of T-box transcription factor 4 (Tbx4 that impair nuclear localisation of the protein, resulting in altered gene expression patterns during pelvic fin development and the failure of pelvic fin development. Using a TALEN-induced tbx4 knockout allele we confirm that mutations within the Tbx4 NLS (A78V; G79A are sufficient to disrupt pelvic fin development. By combining histological, genetic, and cellular approaches we show that the hindlimb initiation gene tbx4 has an evolutionarily conserved, essential role in pelvic fin development. In addition, our novel viable model of hindlimb deficiency is likely to facilitate the elucidation of the detailed molecular mechanisms through which Tbx4 functions during pelvic fin and hindlimb development.

A software tool to model genetic regulatory networks. Applications to the modeling of threshold phenomena and of spatial patterning in Drosophila.

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Rui Dilão

Full Text Available We present a general methodology in order to build mathematical models of genetic regulatory networks. This approach is based on the mass action law and on the Jacob and Monod operon model. The mathematical models are built symbolically by the Mathematica software package GeneticNetworks. This package accepts as input the interaction graphs of the transcriptional activators and repressors of a biological process and, as output, gives the mathematical model in the form of a system of ordinary differential equations. All the relevant biological parameters are chosen automatically by the software. Within this framework, we show that concentration dependent threshold effects in biology emerge from the catalytic properties of genes and its associated conservation laws. We apply this methodology to the segment patterning in Drosophila early development and we calibrate the genetic transcriptional network responsible for the patterning of the gap gene proteins Hunchback and Knirps, along the antero-posterior axis of the Drosophila embryo. In this approach, the zygotically produced proteins Hunchback and Knirps do not diffuse along the antero-posterior axis of the embryo of Drosophila, developing a spatial pattern due to concentration dependent thresholds. This shows that patterning at the gap genes stage can be explained by the concentration gradients along the embryo of the transcriptional regulators.

The true meaning of 'exotic species' as a model for genetically engineered organisms.

Science.gov (United States)

Regal, P J

1993-03-15

The exotic or non-indigenous species model for deliberately introduced genetically engineered organisms (GEOs) has often been misunderstood or misrepresented. Yet proper comparisons of of ecologically competent GEOs to the patterns of adaptation of introduced species have been highly useful among scientists in attempting to determine how to apply biological theory to specific GEO risk issues, and in attempting to define the probabilities and scale of ecological risks with GEOs. In truth, the model predicts that most projects may be environmentally safe, but a significant minority may be very risky. The model includes a history of institutional follies that also should remind workers of the danger of oversimplifying biological issues, and warn against repeating the sorts of professional misjudgements that have too often been made in introducing organisms to new settings. We once expected that the non-indigenous species model would be refined by more analysis of species eruptions, ecological genetics, and the biology of select GEOs themselves, as outlined. But there has been political resistance to the effective regulation of GEOs, and a bureaucratic tendency to focus research agendas on narrow data collection. Thus there has been too little promotion by responsible agencies of studies to provide the broad conceptual base for truly science-based regulation. In its presently unrefined state, the non-indigenous species comparison would overestimate the risks of GEOs if it were (mis)applied to genetically disrupted, ecologically crippled GEOs, but in some cases of wild-type organisms with novel engineered traits, it could greatly underestimate the risks. Further analysis is urgently needed.

Ripple-Spreading Network Model Optimization by Genetic Algorithm

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Xiao-Bing Hu

2013-01-01

Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

Risk adjustment model of credit life insurance using a genetic algorithm

Science.gov (United States)

Saputra, A.; Sukono; Rusyaman, E.

2018-03-01

In managing the risk of credit life insurance, insurance company should acknowledge the character of the risks to predict future losses. Risk characteristics can be learned in a claim distribution model. There are two standard approaches in designing the distribution model of claims over the insurance period i.e, collective risk model and individual risk model. In the collective risk model, the claim arises when risk occurs is called individual claim, accumulation of individual claim during a period of insurance is called an aggregate claim. The aggregate claim model may be formed by large model and a number of individual claims. How the measurement of insurance risk with the premium model approach and whether this approach is appropriate for estimating the potential losses occur in the future. In order to solve the problem Genetic Algorithm with Roulette Wheel Selection is used.

The genetics of childhood obesity and interaction with dietary macronutrients.

Science.gov (United States)

Garver, William S; Newman, Sara B; Gonzales-Pacheco, Diana M; Castillo, Joseph J; Jelinek, David; Heidenreich, Randall A; Orlando, Robert A

2013-05-01

The genes contributing to childhood obesity are categorized into three different types based on distinct genetic and phenotypic characteristics. These types of childhood obesity are represented by rare monogenic forms of syndromic or non-syndromic childhood obesity, and common polygenic childhood obesity. In some cases, genetic susceptibility to these forms of childhood obesity may result from different variations of the same gene. Although the prevalence for rare monogenic forms of childhood obesity has not increased in recent times, the prevalence of common childhood obesity has increased in the United States and developing countries throughout the world during the past few decades. A number of recent genome-wide association studies and mouse model studies have established the identification of susceptibility genes contributing to common childhood obesity. Accumulating evidence suggests that this type of childhood obesity represents a complex metabolic disease resulting from an interaction with environmental factors, including dietary macronutrients. The objective of this article is to provide a review on the origins, mechanisms, and health consequences of obesity susceptibility genes and interaction with dietary macronutrients that predispose to childhood obesity. It is proposed that increased knowledge of these obesity susceptibility genes and interaction with dietary macronutrients will provide valuable insight for individual, family, and community preventative lifestyle intervention, and eventually targeted nutritional and medicinal therapies.

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

Science.gov (United States)

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

2018-02-21

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

Bayesian Modeling for Genetic Anticipation in Presence of Mutational Heterogeneity: A Case Study in Lynch Syndrome

DEFF Research Database (Denmark)

Boonstra, Philip S; Mukherjee, Bhramar; Taylor, Jeremy M G

2011-01-01

Summary Genetic anticipation, described by earlier age of onset (AOO) and more aggressive symptoms in successive generations, is a phenomenon noted in certain hereditary diseases. Its extent may vary between families and/or between mutation subtypes known to be associated with the disease phenotype....... In this article, we posit a Bayesian approach to infer genetic anticipation under flexible random effects models for censored data that capture the effect of successive generations on AOO. Primary interest lies in the random effects. Misspecifying the distribution of random effects may result in incorrect...... to cause hereditary nonpolyposis colorectal cancer, also called Lynch syndrome (LS). We find evidence for a decrease in AOO between generations in this article. Our model predicts family-level anticipation effects that are potentially useful in genetic counseling clinics for high-risk families....

A genetic-algorithm-aided stochastic optimization model for regional air quality management under uncertainty.

Science.gov (United States)

Qin, Xiaosheng; Huang, Guohe; Liu, Lei

2010-01-01

A genetic-algorithm-aided stochastic optimization (GASO) model was developed in this study for supporting regional air quality management under uncertainty. The model incorporated genetic algorithm (GA) and Monte Carlo simulation techniques into a general stochastic chance-constrained programming (CCP) framework and allowed uncertainties in simulation and optimization model parameters to be considered explicitly in the design of least-cost strategies. GA was used to seek the optimal solution of the management model by progressively evaluating the performances of individual solutions. Monte Carlo simulation was used to check the feasibility of each solution. A management problem in terms of regional air pollution control was studied to demonstrate the applicability of the proposed method. Results of the case study indicated the proposed model could effectively communicate uncertainties into the optimization process and generate solutions that contained a spectrum of potential air pollutant treatment options with risk and cost information. Decision alternatives could be obtained by analyzing tradeoffs between the overall pollutant treatment cost and the system-failure risk due to inherent uncertainties.

Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

Science.gov (United States)

Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

2012-02-08

The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

Science.gov (United States)

Chao, Lin; Rang, Camilla Ulla; Proenca, Audrey Menegaz; Chao, Jasper Ubirajara

2016-01-01

Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington's genetic assimilation

Asymmetrical Damage Partitioning in Bacteria: A Model for the Evolution of Stochasticity, Determinism, and Genetic Assimilation.

Directory of Open Access Journals (Sweden)

Lin Chao

2016-01-01

Full Text Available Non-genetic phenotypic variation is common in biological organisms. The variation is potentially beneficial if the environment is changing. If the benefit is large, selection can favor the evolution of genetic assimilation, the process by which the expression of a trait is transferred from environmental to genetic control. Genetic assimilation is an important evolutionary transition, but it is poorly understood because the fitness costs and benefits of variation are often unknown. Here we show that the partitioning of damage by a mother bacterium to its two daughters can evolve through genetic assimilation. Bacterial phenotypes are also highly variable. Because gene-regulating elements can have low copy numbers, the variation is attributed to stochastic sampling. Extant Escherichia coli partition asymmetrically and deterministically more damage to the old daughter, the one receiving the mother's old pole. By modeling in silico damage partitioning in a population, we show that deterministic asymmetry is advantageous because it increases fitness variance and hence the efficiency of natural selection. However, we find that symmetrical but stochastic partitioning can be similarly beneficial. To examine why bacteria evolved deterministic asymmetry, we modeled the effect of damage anchored to the mother's old pole. While anchored damage strengthens selection for asymmetry by creating additional fitness variance, it has the opposite effect on symmetry. The difference results because anchored damage reinforces the polarization of partitioning in asymmetric bacteria. In symmetric bacteria, it dilutes the polarization. Thus, stochasticity alone may have protected early bacteria from damage, but deterministic asymmetry has evolved to be equally important in extant bacteria. We estimate that 47% of damage partitioning is deterministic in E. coli. We suggest that the evolution of deterministic asymmetry from stochasticity offers an example of Waddington

A reconfigurable NAND/NOR genetic logic gate.

Science.gov (United States)

Goñi-Moreno, Angel; Amos, Martyn

2012-09-18

Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

Genetic GIScience

DEFF Research Database (Denmark)

Jacquez, Geoffrey; Sabel, Clive E; Shi, Chen

2015-01-01

The exposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic...... geographic information science (genetic GIScience), that is founded on the exposome, genome+, and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal, and behavioral determinants (the behavome......). Genetic GIScience poses three key needs: first, a mathematical foundation for emergent theory; second, process-based models that bridge biological and geographic scales; third, biologically plausible estimates of space?time disease lags. Compartmental models are a possible solution; this article develops...

Genetic fuzzy system modeling and simulation of vascular behaviour

DEFF Research Database (Denmark)

Tang, Jiaowei; Boonen, Harrie C.M.

Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes in c...... the pressure change of different blood vessels. Conclusion: Genetic fuzzy system is one of potential modeling methods in modeling and simulation of vascular behavior.......Background: The purpose of our project is to identify the rule sets and their interaction within the framework of cardiovascular function. By an iterative process of computational simulation and experimental work, we strive to mimic the physiological basis for cardiovascular adaptive changes...... in cardiovascular disease and ultimately improve pharmacotherapy. For this purpose, novel computational approaches incorporating adaptive properties, auto-regulatory control and rule sets will be assessed, properties that are commonly lacking in deterministic models based on differential equations. We hypothesize...

Dog obesity--the need for identifying predisposing genetic markers.

Science.gov (United States)

Switonski, M; Mankowska, M

2013-12-01

Incidence of overweight and obesity in dogs exceeds 30%, and several breeds are predisposed to this heritable phenotype. Rapid progress of canine genomics and advanced knowledge on the genetic background of human obesity bring a unique opportunity to perform such studies in dogs. Natural candidate genes for obesity are these encoding adipokines. Extended studies in humans indicated that polymorphisms of three of them, i.e. ADIPOQ, IL1 and TNF, are associated with predisposition to obesity. On the other hand, the use of genome-wide association studies revealed an association between human obesity and polymorphism of more than 50 other genes. Until now only few preliminary reports on polymorphism of canine FTO, MC4R, MC3R and PPARG genes have been published. Since the dog is a valuable model organism for human diseases one can foresee that such studies may also contribute to an in-depth understanding of human obesity pathogenesis. Copyright © 2013 Elsevier Ltd. All rights reserved.

EvoSNP-DB: A database of genetic diversity in East Asian populations.

Science.gov (United States)

Kim, Young Uk; Kim, Young Jin; Lee, Jong-Young; Park, Kiejung

2013-08-01

Genome-wide association studies (GWAS) have become popular as an approach for the identification of large numbers of phenotype-associated variants. However, differences in genetic architecture and environmental factors mean that the effect of variants can vary across populations. Understanding population genetic diversity is valuable for the investigation of possible population specific and independent effects of variants. EvoSNP-DB aims to provide information regarding genetic diversity among East Asian populations, including Chinese, Japanese, and Korean. Non-redundant SNPs (1.6 million) were genotyped in 54 Korean trios (162 samples) and were compared with 4 million SNPs from HapMap phase II populations. EvoSNP-DB provides two user interfaces for data query and visualization, and integrates scores of genetic diversity (Fst and VarLD) at the level of SNPs, genes, and chromosome regions. EvoSNP-DB is a web-based application that allows users to navigate and visualize measurements of population genetic differences in an interactive manner, and is available online at [http://biomi.cdc.go.kr/EvoSNP/].

Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study.

Science.gov (United States)

Sanders, Marieke S; de Jonge, Rogier C J; Terwee, Caroline B; Heymans, Martijn W; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A; van Furth, A Marceline

2013-07-23

Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to severity and outcome of BM. In this study it was determined whether host genetic risk factors improve the predictive abilities of an existing model regarding hearing loss after childhood BM. Four hundred and seventy-one Dutch Caucasian childhood BM were genotyped for 11 single nucleotide polymorphisms (SNPs) in seven different genes involved in pathogen recognition. Genetic data were added to the original clinical prediction model and performance of new models was compared to the original model by likelihood ratio tests and the area under the curve (AUC) of the receiver operating characteristic curves. Addition of TLR9-1237 SNPs and the combination of TLR2 + 2477 and TLR4 + 896 SNPs improved the clinical prediction model, but not significantly (increase of AUC's from 0.856 to 0.861 and from 0.856 to 0.875 (p = 0.570 and 0.335, respectively). Other SNPs analysed were not linked to hearing loss. Although addition of genetic risk factors did not significantly improve the clinical prediction model for post-meningitis hearing loss, AUC's of the pre-existing model remain high after addition of genetic factors. Future studies should evaluate whether more combinations of SNPs in larger cohorts has an additional value to the existing prediction model for post meningitis hearing loss.

Genetic analysis of somatic cell score in Danish dairy cattle using ramdom regression test-day model

DEFF Research Database (Denmark)

Elsaid, Reda; Sabry, Ayman; Lund, Mogens Sandø

2011-01-01

,233 Danish Holstein cows, were extracted from the national milk recording database. Each data set was analyzed with random regression models using AI-REML. Fixed effects in all models were age at first calving, herd test day, days carrying calf, effects of germ plasm importation (e.g. additive breed effects......) and low between the beginning and the end of lactation. The estimated environmental correlations were lower than the genetic correlations, but the trends were similar. Based on test-day records, the accuracy of genetic evaluations for SCC should be improved when the variation in heritabilities...

Genetic Diversity Analysis in 27 Tomato Accessions Using Morphological and Molecular Markers

Directory of Open Access Journals (Sweden)

Catur Herison

2018-02-01

Full Text Available Genetic diversity is the most important aspect in tomato breeding activities. Better assessment on the diversity of the collected accessions will come up with better result of the cultivar development. This study aimed at analyzing the genetic diversity of 27 tomato accessions by morphological and molecular markers. Twenty seven accessions collected from various regions of Indonesia were planted in the field and evaluated for their morphological traits, and RAPD analyzed for their molecular markers. The UPGMA clustering analyzes, elaborating the combination of morphological and molecular data, indicated that the tomato accessions could be grouped into 5 major groups with 70 % genetic similarity levels. Current study indicated that although many accessions came from different locations, they congregated into the same group. Cherry, Kudamati 1 and Lombok 3 were the farthest genetic distant accessions to the others. Those three genotypes will be the most valuable accessions, when they were crossed with other accessions, for designing a prospective breeding program in the future.

Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

Energy Technology Data Exchange (ETDEWEB)

May Permann

2007-03-01

Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

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Nebot

2012-04-01

Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

Native South American genetic structure and prehistory inferred from hierarchical modeling of mtDNA.

Science.gov (United States)

Lewis, Cecil M; Long, Jeffrey C

2008-03-01

Genetic diversity in Native South Americans forms a complex pattern at both the continental and local levels. In comparing the West to the East, there is more variation within groups and smaller genetic distances between groups. From this pattern, researchers have proposed that there is more variation in the West and that a larger, more genetically diverse, founding population entered the West than the East. Here, we question this characterization of South American genetic variation and its interpretation. Our concern arises because others have inferred regional variation from the mean variation within local populations without taking into account the variation among local populations within the same region. This failure produces a biased view of the actual variation in the East. In this study, we analyze the mitochondrial DNA sequence between positions 16040 and 16322 of the Cambridge reference sequence. Our sample represents a total of 886 people from 27 indigenous populations from South (22), Central (3), and North America (2). The basic unit of our analyses is nucleotide identity by descent, which is easily modeled and proportional to nucleotide diversity. We use a forward modeling strategy to fit a series of nested models to identity by descent within and between all pairs of local populations. This method provides estimates of identity by descent at different levels of population hierarchy without assuming homogeneity within populations, regions, or continents. Our main discovery is that Eastern South America harbors more genetic variation than has been recognized. We find no evidence that there is increased identity by descent in the East relative to the total for South America. By contrast, we discovered that populations in the Western region, as a group, harbor more identity by descent than has been previously recognized, despite the fact that average identity by descent within groups is lower. In this light, there is no need to postulate separate founding

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

DEFF Research Database (Denmark)

Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage

2012-01-01

of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Science.gov (United States)

Baskaran, Subbiah; Noever, D.

1999-01-01

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

The five-factor model of personality and borderline personality disorder: a genetic analysis of comorbidity.

Science.gov (United States)

Distel, Marijn A; Trull, Timothy J; Willemsen, Gonneke; Vink, Jacqueline M; Derom, Catherine A; Lynskey, Michael; Martin, Nicholas G; Boomsma, Dorret I

2009-12-15

Recently, the nature of personality disorders and their relationship with normal personality traits has received extensive attention. The five-factor model (FFM) of personality, consisting of the personality traits neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, is one of the proposed models to conceptualize personality disorders as maladaptive variants of continuously distributed personality traits. The present study examined the phenotypic and genetic association between borderline personality and FFM personality traits. Data were available for 4403 monozygotic twins, 4425 dizygotic twins, and 1661 siblings from 6140 Dutch, Belgian, and Australian families. Broad-sense heritability estimates for neuroticism, agreeableness, conscientiousness, extraversion, openness to experience, and borderline personality were 43%, 36%, 43%, 47%, 54%, and 45%, respectively. Phenotypic correlations between borderline personality and the FFM personality traits ranged from .06 for openness to experience to .68 for neuroticism. Multiple regression analyses showed that a combination of high neuroticism and low agreeableness best predicted borderline personality. Multivariate genetic analyses showed the genetic factors that influence individual differences in neuroticism, agreeableness, conscientiousness, and extraversion account for all genetic liability to borderline personality. Unique environmental effects on borderline personality, however, were not completely shared with those for the FFM traits (33% is unique to borderline personality). Borderline personality shares all genetic variation with neuroticism, agreeableness, conscientiousness, and extraversion. The unique environmental influences specific to borderline personality may cause individuals with a specific pattern of personality traits to cross a threshold and develop borderline personality.

Reduced Genetic Diversity and Increased Structure in American Mink on the Swedish Coast following Invasive Species Control.

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Zalewski, Andrzej; Zalewska, Hanna; Lunneryd, Sven-Gunnar; André, Carl; Mikusiński, Grzegorz

2016-01-01

Eradication and population reductions are often used to mitigate the negative impacts of non-native invasive species on native biodiversity. However, monitoring the effectiveness of non-native species control programmes is necessary to evaluate the efficacy of these measures. Genetic monitoring could provide valuable insights into temporal changes in demographic, ecological, and evolutionary processes in invasive populations being subject to control programmes. Such programmes should cause a decrease in effective population size and/or in genetic diversity of the targeted non-native species and an increase in population genetic structuring over time. We used microsatellite DNA data from American mink (Neovison vison) to determine whether the removal of this predator on the Koster Islands archipelago and the nearby Swedish mainland affected genetic variation over six consecutive years of mink culling by trappers as part of a population control programme. We found that on Koster Islands allelic richness decreased (from on average 4.53 to 3.55), genetic structuring increased, and effective population size did not change. In contrast, the mink population from the Swedish coast showed no changes in genetic diversity or structure, suggesting the stability of this population over 6 years of culling. Effective population size did not change over time but was higher on the coast than on the islands across all years. Migration rates from the islands to the coast were almost two times higher than from the coast to the islands. Most migrants leaving the coast were localised on the southern edge of the archipelago, as expected from the direction of the sea current between the two sites. Genetic monitoring provided valuable information on temporal changes in the population of American mink suggesting that this approach can be used to evaluate and improve control programmes of invasive vertebrates.

Reduced Genetic Diversity and Increased Structure in American Mink on the Swedish Coast following Invasive Species Control.

Directory of Open Access Journals (Sweden)

Andrzej Zalewski

Full Text Available Eradication and population reductions are often used to mitigate the negative impacts of non-native invasive species on native biodiversity. However, monitoring the effectiveness of non-native species control programmes is necessary to evaluate the efficacy of these measures. Genetic monitoring could provide valuable insights into temporal changes in demographic, ecological, and evolutionary processes in invasive populations being subject to control programmes. Such programmes should cause a decrease in effective population size and/or in genetic diversity of the targeted non-native species and an increase in population genetic structuring over time. We used microsatellite DNA data from American mink (Neovison vison to determine whether the removal of this predator on the Koster Islands archipelago and the nearby Swedish mainland affected genetic variation over six consecutive years of mink culling by trappers as part of a population control programme. We found that on Koster Islands allelic richness decreased (from on average 4.53 to 3.55, genetic structuring increased, and effective population size did not change. In contrast, the mink population from the Swedish coast showed no changes in genetic diversity or structure, suggesting the stability of this population over 6 years of culling. Effective population size did not change over time but was higher on the coast than on the islands across all years. Migration rates from the islands to the coast were almost two times higher than from the coast to the islands. Most migrants leaving the coast were localised on the southern edge of the archipelago, as expected from the direction of the sea current between the two sites. Genetic monitoring provided valuable information on temporal changes in the population of American mink suggesting that this approach can be used to evaluate and improve control programmes of invasive vertebrates.

Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach

International Nuclear Information System (INIS)

Kisi, Ozgur

2014-01-01

The study investigates the ability of FG (fuzzy genetic) approach in modeling solar radiation of seven cities from Mediterranean region of Anatolia, Turkey. Latitude, longitude, altitude and month of the year data from the Adana, K. Maras, Mersin, Antalya, Isparta, Burdur and Antakya cities are used as inputs to the FG model to estimate one month ahead solar radiation. FG model is compared with ANNs (artificial neural networks) and ANFIS (adaptive neruro fuzzzy inference system) models with respect to RMSE (root mean square errors), MAE (mean absolute errors) and determination coefficient (R 2 ) statistics. Comparison results indicate that the FG model performs better than the ANN and ANFIS models. It is found that the FG model can be successfully used for estimating solar radiation by using latitude, longitude, altitude and month of the year information. FG model with RMSE = 6.29 MJ/m 2 , MAE = 4.69 MJ/m 2 and R 2 = 0.905 in the test stage was found to be superior to the optimal ANN model with RMSE = 7.17 MJ/m 2 , MAE = 5.29 MJ/m 2 and R 2 = 0.876 and ANFIS model with RMSE = 6.75 MJ/m 2 , MAE = 5.10 MJ/m 2 and R 2 = 0.892 in estimating solar radiation. - Highlights: • SR (Solar radiation) of seven cities from Mediterranean region of Turkey is predicted. • FG (Fuzzy genetic) models are developed for accurately estimation of SR. • The ability of the FG models used in the study is found to be satisfactory. • FG models are compared with commonly used ANNs (artificial neural networks). • FG models are found to perform better than the ANNs models

On coding genotypes for genetic markers with multiple alleles in genetic association study of quantitative traits

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Wang Tao

2011-09-01

Full Text Available Abstract Background In genetic association study of quantitative traits using F∞ models, how to code the marker genotypes and interpret the model parameters appropriately is important for constructing hypothesis tests and making statistical inferences. Currently, the coding of marker genotypes in building F∞ models has mainly focused on the biallelic case. A thorough work on the coding of marker genotypes and interpretation of model parameters for F∞ models is needed especially for genetic markers with multiple alleles. Results In this study, we will formulate F∞ genetic models under various regression model frameworks and introduce three genotype coding schemes for genetic markers with multiple alleles. Starting from an allele-based modeling strategy, we first describe a regression framework to model the expected genotypic values at given markers. Then, as extension from the biallelic case, we introduce three coding schemes for constructing fully parameterized one-locus F∞ models and discuss the relationships between the model parameters and the expected genotypic values. Next, under a simplified modeling framework for the expected genotypic values, we consider several reduced one-locus F∞ models from the three coding schemes on the estimability and interpretation of their model parameters. Finally, we explore some extensions of the one-locus F∞ models to two loci. Several fully parameterized as well as reduced two-locus F∞ models are addressed. Conclusions The genotype coding schemes provide different ways to construct F∞ models for association testing of multi-allele genetic markers with quantitative traits. Which coding scheme should be applied depends on how convenient it can provide the statistical inferences on the parameters of our research interests. Based on these F∞ models, the standard regression model fitting tools can be used to estimate and test for various genetic effects through statistical contrasts with the

Applying ecological models to communities of genetic elements: the case of neutral theory.

Science.gov (United States)

Linquist, Stefan; Cottenie, Karl; Elliott, Tyler A; Saylor, Brent; Kremer, Stefan C; Gregory, T Ryan

2015-07-01

A promising recent development in molecular biology involves viewing the genome as a mini-ecosystem, where genetic elements are compared to organisms and the surrounding cellular and genomic structures are regarded as the local environment. Here, we critically evaluate the prospects of ecological neutral theory (ENT), a popular model in ecology, as it applies at the genomic level. This assessment requires an overview of the controversy surrounding neutral models in community ecology. In particular, we discuss the limitations of using ENT both as an explanation of community dynamics and as a null hypothesis. We then analyse a case study in which ENT has been applied to genomic data. Our central finding is that genetic elements do not conform to the requirements of ENT once its assumptions and limitations are made explicit. We further compare this genome-level application of ENT to two other, more familiar approaches in genomics that rely on neutral mechanisms: Kimura's molecular neutral theory and Lynch's mutational-hazard model. Interestingly, this comparison reveals that there are two distinct concepts of neutrality associated with these models, which we dub 'fitness neutrality' and 'competitive neutrality'. This distinction helps to clarify the various roles for neutral models in genomics, for example in explaining the evolution of genome size. © 2015 John Wiley & Sons Ltd.

Helicobacter pylori genetic diversification in the Mongolian gerbil model.

Science.gov (United States)

Beckett, Amber C; Loh, John T; Chopra, Abha; Leary, Shay; Lin, Aung Soe; McDonnell, Wyatt J; Dixon, Beverly R E A; Noto, Jennifer M; Israel, Dawn A; Peek, Richard M; Mallal, Simon; Algood, Holly M Scott; Cover, Timothy L

2018-01-01

Helicobacter pylori requires genetic agility to infect new hosts and establish long-term colonization of changing gastric environments. In this study, we analyzed H. pylori genetic adaptation in the Mongolian gerbil model. This model is of particular interest because H. pylori -infected gerbils develop a high level of gastric inflammation and often develop gastric adenocarcinoma or gastric ulceration. We analyzed the whole genome sequences of H. pylori strains cultured from experimentally infected gerbils, in comparison to the genome sequence of the input strain. The mean annualized single nucleotide polymorphism (SNP) rate per site was 1.5e -5 , which is similar to the rates detected previously in H. pylori- infected humans. Many of the mutations occurred within or upstream of genes associated with iron-related functions ( fur , tonB1 , fecA2 , fecA3 , and frpB3 ) or encoding outer membrane proteins ( alpA, oipA, fecA2, fecA3, frpB3 and cagY ). Most of the SNPs within coding regions (86%) were non-synonymous mutations. Several deletion or insertion mutations led to disruption of open reading frames, suggesting that the corresponding gene products are not required or are deleterious during chronic H. pylori colonization of the gerbil stomach. Five variants (three SNPs and two deletions) were detected in isolates from multiple animals, which suggests that these mutations conferred a selective advantage. One of the mutations (FurR88H) detected in isolates from multiple animals was previously shown to confer increased resistance to oxidative stress, and we now show that this SNP also confers a survival advantage when H. pylori is co-cultured with neutrophils. Collectively, these analyses allow the identification of mutations that are positively selected during H. pylori colonization of the gerbil model.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

Science.gov (United States)

Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

2013-12-01

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

The Potential of Zebrafish as a Model Organism for Improving the Translation of Genetic Anticancer Nanomedicines

Directory of Open Access Journals (Sweden)

C Gutiérrez-Lovera

2017-11-01

Full Text Available In the last few decades, the field of nanomedicine applied to cancer has revolutionized cancer treatment: several nanoformulations have already reached the market and are routinely being used in the clinical practice. In the case of genetic nanomedicines, i.e., designed to deliver gene therapies to cancer cells for therapeutic purposes, advances have been less impressive. This is because of the many barriers that limit the access of the therapeutic nucleic acids to their target site, and the lack of models that would allow for an improvement in the understanding of how nanocarriers can be tailored to overcome them. Zebrafish has important advantages as a model species for the study of anticancer therapies, and have a lot to offer regarding the rational development of efficient delivery of genetic nanomedicines, and hence increasing the chances of their successful translation. This review aims to provide an overview of the recent advances in the development of genetic anticancer nanomedicines, and of the zebrafish models that stand as promising tools to shed light on their mechanisms of action and overall potential in oncology.

Radio-over-fiber linearization with optimized genetic algorithm CPWL model.

Science.gov (United States)

Mateo, Carlos; Carro, Pedro L; García-Dúcar, Paloma; De Mingo, Jesús; Salinas, Íñigo

2017-02-20

This article proposes an optimized version of a canonical piece-wise-linear (CPWL) digital predistorter in order to enhance the linearity of a radio-over-fiber (RoF) LTE mobile fronthaul. In this work, we propose a threshold allocation optimization process carried out by a genetic algorithm (GA) in order to optimize the CPWL model (GA-CPWL). Firstly, experiments show how the CPWL model outperforms the classical memory polynomial DPD in an intensity modulation/direct detection (IM/DD) RoF link. Then, the GA-CPWL predistorter is compared with the CPWL model in several scenarios, in order to verify that the proposed DPD offers better performance in different optical transmission conditions. Experimental results reveal that with a proper threshold allocation, the GA-CPWL predistorter offers very promising outcomes.

Recovering valuable metals from recycled photovoltaic modules.

Science.gov (United States)

Yi, Youn Kyu; Kim, Hyun Soo; Tran, Tam; Hong, Sung Kil; Kim, Myong Jun

2014-07-01

Recovering valuable metals such as Si, Ag, Cu, and Al has become a pressing issue as end-of-life photovoltaic modules need to be recycled in the near future to meet legislative requirements in most countries. Of major interest is the recovery and recycling of high-purity silicon (> 99.9%) for the production of wafers and semiconductors. The value of Si in crystalline-type photovoltaic modules is estimated to be -$95/kW at the 2012 metal price. At the current installed capacity of 30 GW/yr, the metal value in the PV modules represents valuable resources that should be recovered in the future. The recycling of end-of-life photovoltaic modules would supply > 88,000 and 207,000 tpa Si by 2040 and 2050, respectively. This represents more than 50% of the required Si for module fabrication. Experimental testwork on crystalline Si modules could recover a > 99.98%-grade Si product by HNO3/NaOH leaching to remove Al, Ag, and Ti and other metal ions from the doped Si. A further pyrometallurgical smelting at 1520 degrees C using CaO-CaF2-SiO2 slag mixture to scavenge the residual metals after acid leaching could finally produce > 99.998%-grade Si. A process based on HNO3/NaOH leaching and subsequent smelting is proposed for recycling Si from rejected or recycled photovoltaic modules. Implications: The photovoltaic industry is considering options of recycling PV modules to recover metals such as Si, Ag, Cu, Al, and others used in the manufacturing of the PV cells. This is to retain its "green" image and to comply with current legislations in several countries. An evaluation of potential resources made available from PV wastes and the technologies used for processing these materials is therefore of significant importance to the industry. Of interest are the costs of processing and the potential revenues gained from recycling, which should determine the viability of economic recycling of PV modules in the future.

Putting mechanisms into crop production models.

Science.gov (United States)

Boote, Kenneth J; Jones, James W; White, Jeffrey W; Asseng, Senthold; Lizaso, Jon I

2013-09-01

Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop growth and development and at season-end, final yield. Their ability to integrate effects of genetics, environment and crop management have led to applications ranging from understanding gene function to predicting potential impacts of climate change. The history of crop models is reviewed briefly, and their level of mechanistic detail for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use efficiency is discussed. Crop models have improved steadily over the past 30-40 years, but much work remains. Improvements are needed for the prediction of transpiration response to elevated CO₂ and high temperature effects on phenology and reproductive fertility, and simulation of root growth and nutrient uptake under stressful edaphic conditions. Mechanistic improvements are needed to better connect crop growth to genetics and to soil fertility, soil waterlogging and pest damage. Because crop models integrate multiple processes and consider impacts of environment and management, they have excellent potential for linking research from genomics and allied disciplines to crop responses at the field scale, thus providing a valuable tool for deciphering genotype by environment by management effects. © 2013 John Wiley & Sons Ltd.

A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

Science.gov (United States)

Danandeh Mehr, Ali; Kahya, Ercan

2017-06-01

Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

Behavioral phenotypes in schizophrenic animal models with multiple combinations of genetic and environmental factors.

Science.gov (United States)

Hida, Hirotake; Mouri, Akihiro; Noda, Yukihiro

2013-01-01

Schizophrenia is a multifactorial psychiatric disorder in which both genetic and environmental factors play a role. Genetic [e.g., Disrupted-in-schizophrenia 1 (DISC1), Neuregulin-1 (NRG1)] and environmental factors (e.g., maternal viral infection, obstetric complications, social stress) may act during the developmental period to increase the incidence of schizophrenia. In animal models, interactions between susceptibility genes and the environment can be controlled in ways not possible in humans; therefore, such models are useful for investigating interactions between or within factors in the pathogenesis and pathophysiology of schizophrenia. We provide an overview of schizophrenic animal models investigating interactions between or within factors. First, we reviewed gene-environment interaction animal models, in which schizophrenic candidate gene mutant mice were subjected to perinatal immune activation or adolescent stress. Next, environment-environment interaction animal models, in which mice were subjected to a combination of perinatal immune activation and adolescent administration of drugs, were described. These animal models showed interaction between or within factors; behavioral changes, which were obscured by each factor, were marked by interaction of factors and vice versa. Appropriate behavioral approaches with such models will be invaluable for translational research on novel compounds, and also for providing insight into the pathogenesis and pathophysiology of schizophrenia.

Genetic Analysis of Somatic Cell Score in Danish Holsteins Using a Liability-Normal Mixture Model

DEFF Research Database (Denmark)

Madsen, P; Shariati, M M; Ødegård, J

2008-01-01

Mixture models are appealing for identifying hidden structures affecting somatic cell score (SCS) data, such as unrecorded cases of subclinical mastitis. Thus, liability-normal mixture (LNM) models were used for genetic analysis of SCS data, with the aim of predicting breeding values for such cas...

Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.

Science.gov (United States)

Lehermeier, Christina; Schön, Chris-Carolin; de Los Campos, Gustavo

2015-09-01

Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to "correct" for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP. Copyright © 2015 by the Genetics Society of America.

World`s Most Valuable Brand Resonation With Categories of Different Customer Needs

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Kaspars VIKSNE

2017-09-01

Full Text Available One of the key performance indicators of brand success is its value. Brand value is an outcome of brand`s performance in market, and is largely depended from brand`s ability to satisfy certain customer needs. For the greatest success in the world`s market brand should resonate its ability to satisfy some of customer`s most universal needs. In this paper authors strives to find out which of the needs world`s most successful brands are resonating with. Therefore paper goal is to is to determine what customer needs world`s most valuable brands are primarily satisfying. First part of paper authors briefly evaluate Maslow theory of needs. In second part of paper authors identify main challenges of brand valuation, and briefly describe today`s most valuable brands. In third part of paper authors analyzes if resonating certain human need in brand makes it to be more valuable. In last part of paper authors summarizes the main findings and gives recommendations for better marketing practices to other brands whose owners have high market ambitions. In order to attain the paper`s goal, authors will use following research methods: Comparative analysis for comparing brands in different brand rankings; Content analysis for determining what need satisfaction brand advertisements resonate; Data analysis for quantify the results gathered from content analysis

Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient.

Science.gov (United States)

Rossetto, Maurizio; Allen, Chris B; Thurlby, Katie A G; Weston, Peter H; Milner, Melita L

2012-08-20

Four of the five species of Telopea (Proteaceae) are distributed in a latitudinal replacement pattern on the south-eastern Australian mainland. In similar circumstances, a simple allopatric speciation model that identifies the origins of genetic isolation within temporal geographic separation is considered as the default model. However, secondary contact between differentiated lineages can result in similar distributional patterns to those arising from a process of parapatric speciation (where gene flow between lineages remains uninterrupted during differentiation). Our aim was to use the characteristic distributional patterns in Telopea to test whether it reflected the evolutionary models of allopatric or parapatric speciation. Using a combination of genetic evidence and environmental niche modelling, we focused on three main questions: do currently described geographic borders coincide with genetic and environmental boundaries; are there hybrid zones in areas of secondary contact between closely related species; did species distributions contract during the last glacial maximum resulting in distributional gaps even where overlap and hybridisation currently occur? Total genomic DNA was extracted from 619 individuals sampled from 36 populations representing the four species. Seven nuclear microsatellites (nSSR) and six chloroplast microsatellites (cpSSR) were amplified across all populations. Genetic structure and the signature of admixture in overlap zones was described using the Bayesian clustering methods implemented in STUCTURE and NewHybrids respectively. Relationships between chlorotypes were reconstructed as a median-joining network. Environmental niche models were produced for all species using environmental parameters from both the present day and the last glacial maximum (LGM).The nSSR loci amplified a total of 154 alleles, while data for the cpSSR loci produced a network of six chlorotypes. STRUCTURE revealed an optimum number of five clusters

[Nodulation competitiveness of nodule bacteria: Genetic control and adaptive significance].

Science.gov (United States)

Onishchuk, O P; Vorobyov, N I; Provorov, N A

2017-01-01

The most recent data on the system of cmp (competitiveness) genes that determine the nodulation competitiveness of rhizobial strains, i.e., the ability to compete for nodule formation in leguminous plants, is analyzed. Three genetic approaches for the construction of economically valuable strains of rhizobia are proposed: the amplification of positive regulators of competitiveness, the inactivation of the negative regulators of this trait, and the introduction of efficient competitiveness factors into strains capable of active nitrogen fixation.

The Mouse House: a brief history of the ORNL mouse-genetics program, 1947-2009.

Science.gov (United States)

Russell, Liane B

2013-01-01

valuable source of mouse models for human genetic disorders. Copyright © 2013 Elsevier B.V. All rights reserved.

Developments in statistical analysis in quantitative genetics

DEFF Research Database (Denmark)

Sorensen, Daniel

2009-01-01

of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......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 by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...

An alternative approach to recovering valuable metals from zinc phosphating sludge.

Science.gov (United States)

Kuo, Yi-Ming

2012-01-30

This study used a vitrification process (with good potential for commercialization) to recover valuable metals from Zn phosphating sludge. The involved vitrification process achieves two major goals: it transformed hazardous Zn phosphating sludge into inert slag and it concentrated Fe (83.5%) and Zn (92.8%) into ingot and fine particulate-phase material, respectively. The Fe content in the ingot was 278,000 mg/kg, making the ingot a potential raw material for iron making. The fine particulate-phase material (collected from flue gas) contained abundant Zn (544,000 mg/kg) in the form of ZnO. The content (67.7%) of ZnO was high, so it can be directly sold to refineries. The recovered coarse particulate-phase material, with insufficient amount of ZnO, can be recycled as a feeding material for Zn re-concentration. Therefore, the vitrification process can not only treat hazardous materials but also effectively recover valuable metals. Copyright © 2011 Elsevier B.V. All rights reserved.

Present, past and future of the European rock fern Asplenium fontanum: combining distribution modelling and population genetics to study the effect of climate change on geographic range and genetic diversity.

Science.gov (United States)

Bystriakova, Nadia; Ansell, Stephen W; Russell, Stephen J; Grundmann, Michael; Vogel, Johannes C; Schneider, Harald

2014-02-01

Climate change is expected to alter the geographic range of many plant species dramatically. Predicting this response will be critical to managing the conservation of plant resources and the effects of invasive species. The aim of this study was to predict the response of temperate homosporous ferns to climate change. Genetic diversity and changes in distribution range were inferred for the diploid rock fern Asplenium fontanum along a South-North transect, extending from its putative last glacial maximum (LGM) refugia in southern France towards southern Germany and eastern-central France. This study reconciles observations from distribution models and phylogeographic analyses derived from plastid and nuclear diversity. Genetic diversity distribution and niche modelling propose that genetic diversity accumulates in the LGM climate refugium in southern France with the formation of a diversity gradient reflecting a slow, post-LGM range expansion towards the current distribution range. Evidence supports the fern's preference for outcrossing, contradicting the expectation that homosporous ferns would populate new sites by single-spore colonization. Prediction of climate and distribution range change suggests that a dramatic loss of range and genetic diversity in this fern is possible. The observed migration is best described by the phalanx expansion model. The results suggest that homosporous ferns reproducing preferentially by outcrossing accumulate genetic diversity primarily in LGM climate refugia and may be threatened if these areas disappear due to global climate change.

Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

Science.gov (United States)

Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

2006-01-01

Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

Tag SNP selection via a genetic algorithm.

Science.gov (United States)

Mahdevar, Ghasem; Zahiri, Javad; Sadeghi, Mehdi; Nowzari-Dalini, Abbas; Ahrabian, Hayedeh

2010-10-01

Single Nucleotide Polymorphisms (SNPs) provide valuable information on human evolutionary history and may lead us to identify genetic variants responsible for human complex diseases. Unfortunately, molecular haplotyping methods are costly, laborious, and time consuming; therefore, algorithms for constructing full haplotype patterns from small available data through computational methods, Tag SNP selection problem, are convenient and attractive. This problem is proved to be an NP-hard problem, so heuristic methods may be useful. In this paper we present a heuristic method based on genetic algorithm to find reasonable solution within acceptable time. The algorithm was tested on a variety of simulated and experimental data. In comparison with the exact algorithm, based on brute force approach, results show that our method can obtain optimal solutions in almost all cases and runs much faster than exact algorithm when the number of SNP sites is large. Our software is available upon request to the corresponding author.

Genetics of human hydrocephalus

Science.gov (United States)

Williams, Michael A.; Rigamonti, Daniele

2006-01-01

Human hydrocephalus is a common medical condition that is characterized by abnormalities in the flow or resorption of cerebrospinal fluid (CSF), resulting in ventricular dilatation. Human hydrocephalus can be classified into two clinical forms, congenital and acquired. Hydrocephalus is one of the complex and multifactorial neurological disorders. A growing body of evidence indicates that genetic factors play a major role in the pathogenesis of hydrocephalus. An understanding of the genetic components and mechanism of this complex disorder may offer us significant insights into the molecular etiology of impaired brain development and an accumulation of the cerebrospinal fluid in cerebral compartments during the pathogenesis of hydrocephalus. Genetic studies in animal models have started to open the way for understanding the underlying pathology of hydrocephalus. At least 43 mutants/loci linked to hereditary hydrocephalus have been identified in animal models and humans. Up to date, 9 genes associated with hydrocephalus have been identified in animal models. In contrast, only one such gene has been identified in humans. Most of known hydrocephalus gene products are the important cytokines, growth factors or related molecules in the cellular signal pathways during early brain development. The current molecular genetic evidence from animal models indicate that in the early development stage, impaired and abnormal brain development caused by abnormal cellular signaling and functioning, all these cellular and developmental events would eventually lead to the congenital hydrocephalus. Owing to our very primitive knowledge of the genetics and molecular pathogenesis of human hydrocephalus, it is difficult to evaluate whether data gained from animal models can be extrapolated to humans. Initiation of a large population genetics study in humans will certainly provide invaluable information about the molecular and cellular etiology and the developmental mechanisms of human

Experimental Population Genetics in the Introductory Genetics Laboratory Using "Drosophila" as a Model Organism

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Johnson, Ronald; Kennon, Tillman

2009-01-01

Hypotheses of population genetics are derived and tested by students in the introductory genetics laboratory classroom as they explore the effects of biotic variables (physical traits of fruit flies) and abiotic variables (island size and distance) on fruit fly populations. In addition to this hypothesis-driven experiment, the development of…

Find the weakest link. A comparison between demographic, genetic and demo-genetic metapopulation extinction times

Directory of Open Access Journals (Sweden)

Robert Alexandre

2011-09-01

Full Text Available Abstract Background While the ultimate causes of most species extinctions are environmental, environmental constraints have various secondary consequences on evolutionary and ecological processes. The roles of demographic, genetic mechanisms and their interactions in limiting the viabilities of species or populations have stirred much debate and remain difficult to evaluate in the absence of demography-genetics conceptual and technical framework. Here, I computed projected times to metapopulation extinction using (1 a model focusing on the effects of species properties, habitat quality, quantity and temporal variability on the time to demographic extinction; (2 a genetic model focusing on the dynamics of the drift and inbreeding loads under the same species and habitat constraints; (3 a demo-genetic model accounting for demographic-genetic processes and feedbacks. Results Results indicate that a given population may have a high demographic, but low genetic viability or vice versa; and whether genetic or demographic aspects will be the most limiting to overall viability depends on the constraints faced by the species (e.g., reduction of habitat quantity or quality. As a consequence, depending on metapopulation or species characteristics, incorporating genetic considerations to demographically-based viability assessments may either moderately or severely reduce the persistence time. On the other hand, purely genetically-based estimates of species viability may either underestimate (by neglecting demo-genetic interactions or overestimate (by neglecting the demographic resilience true viability. Conclusion Unbiased assessments of the viabilities of species may only be obtained by identifying and considering the most limiting processes (i.e., demography or genetics, or, preferentially, by integrating them.

Serum-free Erythroid Differentiation for Efficient Genetic Modification and High-Level Adult Hemoglobin Production.

Science.gov (United States)

Uchida, Naoya; Demirci, Selami; Haro-Mora, Juan J; Fujita, Atsushi; Raines, Lydia N; Hsieh, Matthew M; Tisdale, John F

2018-06-15

In vitro erythroid differentiation from primary human cells is valuable to develop genetic strategies for hemoglobin disorders. However, current erythroid differentiation methods are encumbered by modest transduction rates and high baseline fetal hemoglobin production. In this study, we sought to improve both genetic modification and hemoglobin production among human erythroid cells in vitro . To model therapeutic strategies, we transduced human CD34 + cells and peripheral blood mononuclear cells (PBMCs) with lentiviral vectors and compared erythropoietin-based erythroid differentiation using fetal-bovine-serum-containing media and serum-free media. We observed more efficient transduction (85%-93%) in serum-free media than serum-containing media (20%-69%), whereas the addition of knockout serum replacement (KSR) was required for serum-free media to promote efficient erythroid differentiation (96%). High-level adult hemoglobin production detectable by electrophoresis was achieved using serum-free media similar to serum-containing media. Importantly, low fetal hemoglobin production was observed in the optimized serum-free media. Using KSR-containing, serum-free erythroid differentiation media, therapeutic adult hemoglobin production was detected at protein levels with β-globin lentiviral transduction in both CD34 + cells and PBMCs from sickle cell disease subjects. Our in vitro erythroid differentiation system provides a practical evaluation platform for adult hemoglobin production among human erythroid cells following genetic manipulation.

On the use of sibling recurrence risks to select environmental factors liable to interact with genetic risk factors.

Science.gov (United States)

Kazma, Rémi; Bonaïti-Pellié, Catherine; Norris, Jill M; Génin, Emmanuelle

2010-01-01

Gene-environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene-environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene-environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype.

On the Reliability of Nonlinear Modeling using Enhanced Genetic Programming Techniques

Science.gov (United States)

Winkler, S. M.; Affenzeller, M.; Wagner, S.

The use of genetic programming (GP) in nonlinear system identification enables the automated search for mathematical models that are evolved by an evolutionary process using the principles of selection, crossover and mutation. Due to the stochastic element that is intrinsic to any evolutionary process, GP cannot guarantee the generation of similar or even equal models in each GP process execution; still, if there is a physical model underlying to the data that are analyzed, then GP is expected to find these structures and produce somehow similar results. In this paper we define a function for measuring the syntactic similarity of mathematical models represented as structure trees; using this similarity function we compare the results produced by GP techniques for a data set representing measurement data of a BMW Diesel engine.

Genetic Diversity Analysis of South and East Asian Duck Populations Using Highly Polymorphic Microsatellite Markers

Directory of Open Access Journals (Sweden)

Dongwon Seo

2016-04-01

Full Text Available Native duck populations have lower productivity, and have not been developed as much as commercials duck breeds. However, native ducks have more importance in terms of genetic diversity and potentially valuable economic traits. For this reason, population discriminable genetic markers are needed for conservation and development of native ducks. In this study, 24 highly polymorphic microsatellite (MS markers were investigated using commercial ducks and native East and South Asian ducks. The average polymorphic information content (PIC value for all MS markers was 0.584, indicating high discrimination power. All populations were discriminated using 14 highly polymorphic MS markers by genetic distance and phylogenetic analysis. The results indicated that there were close genetic relationships among populations. In the structure analysis, East Asian ducks shared more haplotypes with commercial ducks than South Asian ducks, and they had more independent haplotypes than others did. These results will provide useful information for genetic diversity studies in ducks and for the development of duck traceability systems in the market.

Modeling of genetic algorithms with a finite population

NARCIS (Netherlands)

C.H.M. van Kemenade

1997-01-01

textabstractCross-competition between non-overlapping building blocks can strongly influence the performance of evolutionary algorithms. The choice of the selection scheme can have a strong influence on the performance of a genetic algorithm. This paper describes a number of different genetic

Probability Model of Allele Frequency of Alzheimer’s Disease Genetic Risk Factor

Directory of Open Access Journals (Sweden)

Afshin Fayyaz-Movaghar

2016-06-01

Full Text Available Background and Purpose: The identification of genetics risk factors of human diseases is very important. This study is conducted to model the allele frequencies (AFs of Alzheimer’s disease. Materials and Methods: In this study, several candidate probability distributions are fitted on a data set of Alzheimer’s disease genetic risk factor. Unknown parameters of the considered distributions are estimated, and some criterions of goodness-of-fit are calculated for the sake of comparison. Results: Based on some statistical criterions, the beta distribution gives the best fit on AFs. However, the estimate values of the parameters of beta distribution lead us to the standard uniform distribution. Conclusion: The AFs of Alzheimer’s disease follow the standard uniform distribution.

Genetic variability of Cordia alliodora (R. and P.) Oken progenies; Caracterizacion de la variabilidad genetica de progenies de Cordia alliodora (R. and P.) Oken.

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Marulanda, Marta Leonor; Lopez, Ana Maria; Uribe, Marcela; Ospina, Carlos Mario

2011-07-01

Cordia alliodora is a well-known wood producer tree of tropical areas of Latin America and the Caribbean characterized for producing valuable wood and by its fast growth rate. In Colombia, it is frequent on agro-forestall systems with coffee. This species, like most forest species have biological problems for genetic improvement programs, such as long regeneration periods and high costs for supporting a population in a long term. The molecular assisted markers in plant breeding programs have had a great impact on genetic improvement, due to the fact they minimize their intervals of regeneration, increase the genetic gain by generation and allow the evaluation of the genetic information essential for the species. In this work, 60 genotypes of C. alliodora were characterized, belonging to the provenance and progenies tests established by the program of genetic improvement of Cenicafe. The characterization was carried out through micro satellite markers, after developing a genomic library enriched with micro satellites of the species. Finally, 24 specific micro satellites were evaluated, 20 of which allowed the detection of 28 polymorphic and multiallelic loci. These results provide a guide for orienting the policies of sustainable production and conservation of this valuable species; also, it provides a useful tool for the identification of clones with commercial interest.

Prenatal diagnosis--principles of diagnostic procedures and genetic counseling.

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Ryszard Slezak

2008-04-01

Full Text Available The frequency of inherited malformations as well as genetic disorders in newborns account for around 3-5%. These frequency is much higher in early stages of pregnancy, because serious malformations and genetic disorders usually lead to spontaneous abortion. Prenatal diagnosis allowed identification of malformations and/or some genetic syndromes in fetuses during the first trimester of pregnancy. Thereafter, taking into account the severity of the disorders the decision should be taken in regard of subsequent course of the pregnancy taking into account a possibilities of treatment, parent's acceptation of a handicapped child but also, in some cases the possibility of termination of the pregnancy. In prenatal testing, both screening and diagnostic procedures are included. Screening procedures such as first and second trimester biochemical and/or ultrasound screening, first trimester combined ultrasound/biochemical screening and integrated screening should be widely offered to pregnant women. However, interpretation of screening results requires awareness of both sensitivity and predictive value of these procedures. In prenatal diagnosis ultrasound/MRI searching as well as genetic procedures are offered to pregnant women. A variety of approaches for genetic prenatal analyses are now available, including preimplantation diagnosis, chorion villi sampling, amniocentesis, fetal blood sampling as well as promising experimental procedures (e.g. fetal cell and DNA isolation from maternal blood. An incredible progress in genetic methods opened new possibilities for valuable genetic diagnosis. Although karyotyping is widely accepted as golden standard, the discussion is ongoing throughout Europe concerning shifting to new genetic techniques which allow obtaining rapid results in prenatal diagnosis of aneuploidy (e.g. RAPID-FISH, MLPA, quantitative PCR.

A genetic linkage map for the saltwater crocodile (Crocodylus porosus

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Lance Stacey L

2009-07-01

Full Text Available Abstract Background Genome elucidation is now in high gear for many organisms, and whilst genetic maps have been developed for a broad array of species, surprisingly, no such maps exist for a crocodilian, or indeed any other non-avian member of the Class Reptilia. Genetic linkage maps are essential tools for the mapping and dissection of complex quantitative trait loci (QTL, and in order to permit systematic genome scans for the identification of genes affecting economically important traits in farmed crocodilians, a comprehensive genetic linage map will be necessary. Results A first-generation genetic linkage map for the saltwater crocodile (Crocodylus porosus was constructed using 203 microsatellite markers amplified across a two-generation pedigree comprising ten full-sib families from a commercial population at Darwin Crocodile Farm, Northern Territory, Australia. Linkage analyses identified fourteen linkage groups comprising a total of 180 loci, with 23 loci remaining unlinked. Markers were ordered within linkage groups employing a heuristic approach using CRIMAP v3.0 software. The estimated female and male recombination map lengths were 1824.1 and 319.0 centimorgans (cM respectively, revealing an uncommonly large disparity in recombination map lengths between sexes (ratio of 5.7:1. Conclusion We have generated the first genetic linkage map for a crocodilian, or indeed any other non-avian reptile. The uncommonly large disparity in recombination map lengths confirms previous preliminary evidence of major differences in sex-specific recombination rates in a species that exhibits temperature-dependent sex determination (TSD. However, at this point the reason for this disparity in saltwater crocodiles remains unclear. This map will be a valuable resource for crocodilian researchers, facilitating the systematic genome scans necessary for identifying genes affecting complex traits of economic importance in the crocodile industry. In addition

Identification of Factors Determining Market Value of the Most Valuable Football Players

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Sebastian Majewski

2016-03-01

Full Text Available Purpose: The problem of identifying the most important determinants of the market value of football players is quite well described in the literature. There are many works that try to identify these factors. Some of them are focused on variables to make a set complete and others are on models and methods. The aim of this article is to present the variables influencing the valuation and to build an econometric model valuing footballers playing on the forward position, taking into consideration the assumptions of the econometric modelling. Such an approach indicates managers as other sources for obtaining information. Methodology: Econometric models were used to verify the hypothesis formulated in this research. The database was created on the basis of variables presented on the website www.transfermarkt. de that presents the values of the most valuable football players in the world playing on the forward position. The Gretl program was used in the research. Findings: The literature review showed that there are many independent variables having an impact on the value of the player. There are also many different models used to valuate footballers’ performance rights. The results of estimation of models in the research indicated that such factors as Canadian classification points adjusted the market value of the team and dummy variables describing “goodwill” (only for the best players had an impact on the market value of footballers’ performance rights. Limitations/implications: Information about different factors having an impact on football players’ market value could support the investment decision process of football managers. Originality/value: The results were part of a study concerning economics of sport, particularly processes of management of football clubs and valuation of intangible assets.

Applying personal genetic data to injury risk assessment in athletes.

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Gabrielle T Goodlin

Full Text Available Recent studies have identified genetic markers associated with risk for certain sports-related injuries and performance-related conditions, with the hope that these markers could be used by individual athletes to personalize their training and diet regimens. We found that we could greatly expand the knowledge base of sports genetic information by using published data originally found in health and disease studies. For example, the results from large genome-wide association studies for low bone mineral density in elderly women can be re-purposed for low bone mineral density in young endurance athletes. In total, we found 124 single-nucleotide polymorphisms associated with: anterior cruciate ligament tear, Achilles tendon injury, low bone mineral density and stress fracture, osteoarthritis, vitamin/mineral deficiencies, and sickle cell trait. Of these single nucleotide polymorphisms, 91% have not previously been used in sports genetics. We conducted a pilot program on fourteen triathletes using this expanded knowledge base of genetic variants associated with sports injury. These athletes were genotyped and educated about how their individual genetic make-up affected their personal risk profile during an hour-long personal consultation. Overall, participants were favorable of the program, found it informative, and most acted upon their genetic results. This pilot program shows that recent genetic research provides valuable information to help reduce sports injuries and to optimize nutrition. There are many genetic studies for health and disease that can be mined to provide useful information to athletes about their individual risk for relevant injuries.

Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

NARCIS (Netherlands)

van der Net, Jeroen B.; Janssens, A. Cecile J. W.; Eijkemans, Marinus J. C.; Kastelein, John J. P.; Sijbrands, Eric J. G.; Steyerberg, Ewout W.

2008-01-01

Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional

Cumulative t-link threshold models for the genetic analysis of calving ease scores

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Tempelman Robert J

2003-09-01

Full Text Available Abstract In this study, a hierarchical threshold mixed model based on a cumulative t-link specification for the analysis of ordinal data or more, specifically, calving ease scores, was developed. The validation of this model and the Markov chain Monte Carlo (MCMC algorithm was carried out on simulated data from normally and t4 (i.e. a t-distribution with four degrees of freedom distributed populations using the deviance information criterion (DIC and a pseudo Bayes factor (PBF measure to validate recently proposed model choice criteria. The simulation study indicated that although inference on the degrees of freedom parameter is possible, MCMC mixing was problematic. Nevertheless, the DIC and PBF were validated to be satisfactory measures of model fit to data. A sire and maternal grandsire cumulative t-link model was applied to a calving ease dataset from 8847 Italian Piemontese first parity dams. The cumulative t-link model was shown to lead to posterior means of direct and maternal heritabilities (0.40 ± 0.06, 0.11 ± 0.04 and a direct maternal genetic correlation (-0.58 ± 0.15 that were not different from the corresponding posterior means of the heritabilities (0.42 ± 0.07, 0.14 ± 0.04 and the genetic correlation (-0.55 ± 0.14 inferred under the conventional cumulative probit link threshold model. Furthermore, the correlation (> 0.99 between posterior means of sire progeny merit from the two models suggested no meaningful rerankings. Nevertheless, the cumulative t-link model was decisively chosen as the better fitting model for this calving ease data using DIC and PBF.

QSAR study on the histamine (H3 receptor antagonists using the genetic algorithm: Multi parameter linear regression

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Adimi Maryam

2012-01-01

Full Text Available A quantitative structure activity relationship (QSAR model has been produced for predicting antagonist potency of biphenyl derivatives as human histamine (H3 receptors. The molecular structures of the compounds are numerically represented by various kinds of molecular descriptors. The whole data set was divided into training and test sets. Genetic algorithm based multiple linear regression is used to select most statistically effective descriptors. The final QSAR model (N =24, R2=0.916, F = 51.771, Q2 LOO = 0.872, Q2 LGO = 0.847, Q2 BOOT = 0.857 was fully validated employing leaveone- out (LOO cross-validation approach, Fischer statistics (F, Yrandomisation test, and predictions based on the test data set. The test set presented an external prediction power of R2 test=0.855. In conclusion, the QSAR model generated can be used as a valuable tool for designing similar groups of new antagonists of histamine (H3 receptors.

Mathematical Modelling Plant Signalling Networks

KAUST Repository

Muraro, D.

2013-01-01

During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

A Multi-Marker Genetic Association Test Based on the Rasch Model Applied to Alzheimer's Disease.

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Wenjia Wang

Full Text Available Results from Genome-Wide Association Studies (GWAS have shown that the genetic basis of complex traits often include many genetic variants with small to moderate effects whose identification remains a challenging problem. In this context multi-marker analysis at the gene and pathway level can complement traditional point-wise approaches that treat the genetic markers individually. In this paper we propose a novel statistical approach for multi-marker analysis based on the Rasch model. The method summarizes the categorical genotypes of SNPs by a generalized logistic function into a genetic score that can be used for association analysis. Through different sets of simulations, the false-positive rate and power of the proposed approach are compared to a set of existing methods, and shows good performances. The application of the Rasch model on Alzheimer's Disease (AD ADNI GWAS dataset also allows a coherent interpretation of the results. Our analysis supports the idea that APOE is a major susceptibility gene for AD. In the top genes selected by proposed method, several could be functionally linked to AD. In particular, a pathway analysis of these genes also highlights the metabolism of cholesterol, that is known to play a key role in AD pathogenesis. Interestingly, many of these top genes can be integrated in a hypothetic signalling network.

Inferring genetic parameters of lactation in Tropical Milking Criollo cattle with random regression test-day models.

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Santellano-Estrada, E; Becerril-Pérez, C M; de Alba, J; Chang, Y M; Gianola, D; Torres-Hernández, G; Ramírez-Valverde, R

2008-11-01

This study inferred genetic and permanent environmental variation of milk yield in Tropical Milking Criollo cattle and compared 5 random regression test-day models using Wilmink's function and Legendre polynomials. Data consisted of 15,377 test-day records from 467 Tropical Milking Criollo cows that calved between 1974 and 2006 in the tropical lowlands of the Gulf Coast of Mexico and in southern Nicaragua. Estimated heritabilities of test-day milk yields ranged from 0.18 to 0.45, and repeatabilities ranged from 0.35 to 0.68 for the period spanning from 6 to 400 d in milk. Genetic correlation between days in milk 10 and 400 was around 0.50 but greater than 0.90 for most pairs of test days. The model that used first-order Legendre polynomials for additive genetic effects and second-order Legendre polynomials for permanent environmental effects gave the smallest residual variance and was also favored by the Akaike information criterion and likelihood ratio tests.

Mapping QTL for Seed Germinability under Low Temperature Using a New High-Density Genetic Map of Rice

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Ningfei Jiang

2017-07-01

Full Text Available Mapping major quantitative trait loci (QTL responsible for rice seed germinability under low temperature (GULT can provide valuable genetic source for improving cold tolerance in rice breeding. In this study, 124 rice backcross recombinant inbred lines (BRILs derived from a cross indica cv. Changhui 891 and japonica cv. 02428 were genotyped through re-sequencing technology. A bin map was generated which includes 3057 bins covering distance of 1266.5 cM with an average of 0.41 cM between markers. On the basis of newly constructed high-density genetic map, six QTL were detected ranging from 40 to 140 kb on Nipponbare genome. Among these, two QTL qCGR8 and qGRR11 alleles shared by 02428 could increase GULT and seed germination recovery rate after cold stress, respectively. However, qNGR1 and qNGR4 may be two major QTL affecting indica Changhui 891germination under normal condition. QTL qGRR1 and qGRR8 affected the seed germination recovery rate after cold stress and the alleles with increasing effects were shared by the Changhui 891 could improve seed germination rate after cold stress dramatically. These QTL could be a highly valuable genetic factors for cold tolerance improvement in rice lines. Moreover, the BRILs developed in this study will serve as an appropriate choice for mapping and studying genetic basis of rice complex traits.

The Mouse House: A brief history of the ORNL mouse-genetics program, 1947–2009

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Russell, Liane B.

2013-10-01

The large mouse genetics program at the Oak Ridge National Lab is often re-membered chiefly for the germ-cell mutation-rate data it generated and their uses in estimating the risk of heritable radiation damage. In fact, it soon became a multi-faceted research effort that, over a period of almost 60 years, generated a wealth of information in the areas of mammalian mutagenesis, basic genetics (later enriched by molecular techniques), cytogenetics, reproductive biology, biochemistry of germ cells, and teratology. Research in the area of germ-cell mutagenesis explored the important physical and biological factors that affect the frequency and nature of induced mutations and made several unexpected discoveries, such as the major importance of the perigametic interval (the zygote stage) for the origin of spontaneous mutations and for the sensitivity to induced genetic change. Of practical value was the discovery that ethylnitrosourea was a supermutagen for point mutations, making high-efficiency mutagenesis in the mouse feasible worldwide. Teratogenesis findings resulted in recommendations still generally accepted in radiological practice. Studies supporting the mutagenesis research added whole bodies of information about mammalian germ-cell development and about molecular targets in germ cells. The early decision to not merely count but propagate genetic variants of all sorts made possible further discoveries, such as the Y-Chromosome s importance in mammalian sex determination and the identification of rare X-autosome translocations, which, in turn, led to the formulation of the single-active-X hypothesis and provided tools for studies of functional mosaicism for autosomal genes, male sterility, and chromosome-pairing mechanism. Extensive genetic and then molecular analyses of large numbers of induced specific-locus mutants resulted in fine-structure physical and correlated functional mapping of significant portions of the mouse genome and constituted a valuable

Optimizing models for production and inventory control using a genetic algorithm

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Dragan S. Pamučar

2012-01-01

Full Text Available In order to make the Economic Production Quantity (EPQ model more applicable to real-world production and inventory control problems, in this paper we expand this model by assuming that some imperfect items of different product types being produced such as reworks are allowed. In addition, we may have more than one product and supplier along with warehouse space and budget limitation. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, a design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. In the end, a numerical example is presented to demonstrate the application of the proposed methodology.

Use of genomic models to study genetic control of environmental variance

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

. The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

Conserving genetic diversity in the honeybee: comments on Harpur et al. (2012).

Science.gov (United States)

De la Rúa, Pilar; Jaffé, Rodolfo; Muñoz, Irene; Serrano, José; Moritz, Robin F A; Kraus, F Bernhard

2013-06-01

The article by Harpur et al. (2012) 'Management increases genetic diversity of honey bees via admixture' concludes that '…honey bees do not suffer from reduced genetic diversity caused by management and, consequently, that reduced genetic diversity is probably not contributing to declines of managed Apis mellifera populations'. In the light of current honeybee and beekeeping declines and their consequences for honeybee conservation and the pollination services they provide, we would like to express our concern about the conclusions drawn from the results of Harpur et al. (2012). While many honeybee management practices do not imply admixture, we are convinced that the large-scale genetic homogenization of admixed populations could drive the loss of valuable local adaptations. We also point out that the authors did not account for the extensive gene flow that occurs between managed and wild/feral honeybee populations and raise concerns about the data set used. Finally, we caution against underestimating the importance of genetic diversity for honeybee colonies and highlight the importance of promoting the use of endemic honeybee subspecies in apiculture. © 2013 John Wiley & Sons Ltd.

Fatal Prion Disease in a Mouse Model of Genetic E200K Creutzfeldt-Jakob Disease

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Friedman-Levi, Yael; Meiner, Zeev; Canello, Tamar; Frid, Kati; Kovacs, Gabor G.; Budka, Herbert; Avrahami, Dana; Gabizon, Ruth

2011-01-01

Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K), causing genetic Creutzfeldt-Jakob disease (gCJD) in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M) E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5–6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments. PMID:22072968

Fatal prion disease in a mouse model of genetic E200K Creutzfeldt-Jakob disease.

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Yael Friedman-Levi

2011-11-01

Full Text Available Genetic prion diseases are late onset fatal neurodegenerative disorders linked to pathogenic mutations in the prion protein-encoding gene, PRNP. The most prevalent of these is the substitution of Glutamate for Lysine at codon 200 (E200K, causing genetic Creutzfeldt-Jakob disease (gCJD in several clusters, including Jews of Libyan origin. Investigating the pathogenesis of genetic CJD, as well as developing prophylactic treatments for young asymptomatic carriers of this and other PrP mutations, may well depend upon the availability of appropriate animal models in which long term treatments can be evaluated for efficacy and toxicity. Here we present the first effective mouse model for E200KCJD, which expresses chimeric mouse/human (TgMHu2M E199KPrP on both a null and a wt PrP background, as is the case for heterozygous patients and carriers. Mice from both lines suffered from distinct neurological symptoms as early as 5-6 month of age and deteriorated to death several months thereafter. Histopathological examination of the brain and spinal cord revealed early gliosis and age-related intraneuronal deposition of disease-associated PrP similarly to human E200K gCJD. Concomitantly we detected aggregated, proteinase K resistant, truncated and oxidized PrP forms on immunoblots. Inoculation of brain extracts from TgMHu2ME199K mice readily induced, the first time for any mutant prion transgenic model, a distinct fatal prion disease in wt mice. We believe that these mice may serve as an ideal platform for the investigation of the pathogenesis of genetic prion disease and thus for the monitoring of anti-prion treatments.

MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.

Science.gov (United States)

Wang, Julia; Al-Ouran, Rami; Hu, Yanhui; Kim, Seon-Young; Wan, Ying-Wooi; Wangler, Michael F; Yamamoto, Shinya; Chao, Hsiao-Tuan; Comjean, Aram; Mohr, Stephanie E; Perrimon, Norbert; Liu, Zhandong; Bellen, Hugo J

2017-06-01

One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection.

Science.gov (United States)

Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

2013-11-20

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage

Elaboration of the Reciprocal-Engagement Model of Genetic Counseling Practice: a Qualitative Investigation of Goals and Strategies.

Science.gov (United States)

Redlinger-Grosse, Krista; Veach, Patricia McCarthy; LeRoy, Bonnie S; Zierhut, Heather

2017-12-01

As the genetic counseling field evolves, a comprehensive model of practice is critical. The Reciprocal-Engagement Model (REM) consists of 5 tenets and 17 goals. Lacking in the REM, however, are well-articulated counselor strategies and behaviors. The purpose of the present study was to further elaborate and provide supporting evidence for the REM by identifying and mapping genetic counseling strategies to the REM goals. A secondary, qualitative analysis was conducted on data from two prior studies: 1) focus group results of genetic counseling outcomes (Redlinger-Grosse et al., Journal of Genetic Counseling, 2015); and 2) genetic counselors' examples of successful and unsuccessful genetic counseling sessions (Geiser et al. 2009). Using directed content analysis, 337 unique strategies were extracted from focus group data. A Q-sort of the 337 strategies yielded 15 broader strategy domains that were then mapped to the successful and unsuccessful session examples. Differing prevalence of strategy domains identified in successful sessions versus the prevalence of domains identified as lacking in unsuccessful sessions provide further support for the REM goals. The most prevalent domains for successful sessions were Information Giving and Use Psychosocial Skills and Strategies; and for unsuccessful sessions, Information Giving and Establish Working Alliance. Identified strategies support the REM's reciprocal nature, especially with regard to addressing patients' informational and psychosocial needs. Patients' contributions to success (or lack thereof) of sessions was also noted, supporting a REM tenet that individual characteristics and the counselor-patient relationship are central to processes and outcomes. The elaborated REM could be used as a framework for certain graduate curricular objectives, and REM components could also inform process and outcomes research studies to document and further characterize genetic counselor strategies.

Metagenomes provide valuable comparative information on soil microeukaryotes

DEFF Research Database (Denmark)

Jacquiod, Samuel Jehan Auguste; Stenbæk, Jonas; Santos, Susana

2016-01-01

has been identified. Our analyses suggest that publicly available metagenome data can provide valuable information on soil microeukaryotes for comparative purposes when handled appropriately, complementing the current view provided by ribosomal amplicon sequencing methods......., providing microbiologists with substantial amounts of accessible information. We took advantage of public metagenomes in order to investigate microeukaryote communities in a well characterized grassland soil. The data gathered allowed the evaluation of several factors impacting the community structure......, including the DNA extraction method, the database choice and also the annotation procedure. While most studies on soil microeukaryotes are based on sequencing of PCR-amplified taxonomic markers (18S rRNA genes, ITS regions), this work represents, to our knowledge, the first report based solely...

Multilocus genetic models of handedness closely resemble single-locus models in explaining family data and are compatible with genome-wide association studies.

Science.gov (United States)

McManus, I C; Davison, Angus; Armour, John A L

2013-06-01

Right- and left-handedness run in families, show greater concordance in monozygotic than dizygotic twins, and are well described by single-locus Mendelian models. Here we summarize a large genome-wide association study (GWAS) that finds no significant associations with handedness and is consistent with a meta-analysis of GWASs. The GWAS had 99% power to detect a single locus using the conventional criterion of P < 5 × 10(-8) for the single locus models of McManus and Annett. The strong conclusion is that handedness is not controlled by a single genetic locus. A consideration of the genetic architecture of height, primary ciliary dyskinesia, and intelligence suggests that handedness inheritance can be explained by a multilocus variant of the McManus DC model, classical effects on family and twins being barely distinguishable from the single locus model. Based on the ENGAGE meta-analysis of GWASs, we estimate at least 40 loci are involved in determining handedness. © 2013 New York Academy of Sciences.

Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient

Directory of Open Access Journals (Sweden)

Rossetto Maurizio

2012-08-01

Full Text Available Abstract Background Four of the five species of Telopea (Proteaceae are distributed in a latitudinal replacement pattern on the south-eastern Australian mainland. In similar circumstances, a simple allopatric speciation model that identifies the origins of genetic isolation within temporal geographic separation is considered as the default model. However, secondary contact between differentiated lineages can result in similar distributional patterns to those arising from a process of parapatric speciation (where gene flow between lineages remains uninterrupted during differentiation. Our aim was to use the characteristic distributional patterns in Telopea to test whether it reflected the evolutionary models of allopatric or parapatric speciation. Using a combination of genetic evidence and environmental niche modelling, we focused on three main questions: do currently described geographic borders coincide with genetic and environmental boundaries; are there hybrid zones in areas of secondary contact between closely related species; did species distributions contract during the last glacial maximum resulting in distributional gaps even where overlap and hybridisation currently occur? Results Total genomic DNA was extracted from 619 individuals sampled from 36 populations representing the four species. Seven nuclear microsatellites (nSSR and six chloroplast microsatellites (cpSSR were amplified across all populations. Genetic structure and the signature of admixture in overlap zones was described using the Bayesian clustering methods implemented in STUCTURE and NewHybrids respectively. Relationships between chlorotypes were reconstructed as a median-joining network. Environmental niche models were produced for all species using environmental parameters from both the present day and the last glacial maximum (LGM. The nSSR loci amplified a total of 154 alleles, while data for the cpSSR loci produced a network of six chlorotypes. STRUCTURE revealed

Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

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Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

2012-02-01

The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

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Briley, Daniel A.; Tucker-Drob, Elliot M.

2017-01-01

The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

A genetic algorithm-based job scheduling model for big data analytics.

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Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

SERS-based detection methods for screening of genetically modified bacterial strains

DEFF Research Database (Denmark)

Morelli, Lidia

factories vary largely, including industrial production of valuable compounds for biofuels, polymer synthesis and food, cosmetic and pharmaceutical industry. The improvement of computational and biochemical tools has revolutionized the synthesis of novel modified microbial strains, opening up new......The importance of metabolic engineering has been growing over the last decades, establishing the use of genetically modified microbial strains for overproduction of metabolites at industrial scale as an innovative, convenient and biosustainable method. Nowadays, application areas of microbial...

Genetic technologies for extremely thermophilic microorganisms of Sulfolobus, the only genetically tractable genus of crenarchaea.

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Peng, Nan; Han, Wenyuan; Li, Yingjun; Liang, Yunxiang; She, Qunxin

2017-04-01

Archaea represents the third domain of life, with the information-processing machineries more closely resembling those of eukaryotes than the machineries of the bacterial counterparts but sharing metabolic pathways with organisms of Bacteria, the sister prokaryotic phylum. Archaeal organisms also possess unique features as revealed by genomics and genome comparisons and by biochemical characterization of prominent enzymes. Nevertheless, diverse genetic tools are required for in vivo experiments to verify these interesting discoveries. Considerable efforts have been devoted to the development of genetic tools for archaea ever since their discovery, and great progress has been made in the creation of archaeal genetic tools in the past decade. Versatile genetic toolboxes are now available for several archaeal models, among which Sulfolobus microorganisms are the only genus representing Crenarchaeota because all the remaining genera are from Euryarchaeota. Nevertheless, genetic tools developed for Sulfolobus are probably the most versatile among all archaeal models, and these include viral and plasmid shuttle vectors, conventional and novel genetic manipulation methods, CRISPR-based gene deletion and mutagenesis, and gene silencing, among which CRISPR tools have been reported only for Sulfolobus thus far. In this review, we summarize recent developments in all these useful genetic tools and discuss their possible application to research into archaeal biology by means of Sulfolobus models.

The value of small habitat islands for the conservation of genetic variability in a steppe grass species

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Wódkiewicz, Maciej; Dembicz, Iwona; Moysiyenko, Ivan I.

2016-10-01

The habitat loss and fragmentation due to agricultural land-conversion affected the steppe throughout its range. In Ukraine, 95% of steppe was destroyed in the last two centuries. Remaining populations are confined to few refuges, like nature reserves, loess ravines, and kurgans (small burial mounds), the latter being often subject to destruction by archeological excavations. Stipa capillata L. is a typical grass species of Eurasian steppes and extrazonal dry grasslands, that was previously used as a model species in studies on steppe ecology. The aim of our research was to assess genetic diversity of S. capillata populations within different types of steppe refuges (loess ravines, biosphere reserve, kurgan) and to evaluate the value of the latter group for the preservation of genetic diversity in the study species. We assessed genetic diversity of 266 individuals from 15 populations (nine from kurgans, three from loess ravines and three from Askania-Nova Biosphere Reserve) with eight Universal Rice Primers (URPs). Studied populations showed high intra-population variability (I: 0.262-0.419, PPB: 52.08-82.64%). Populations from kurgans showed higher genetic differentiation (ΦST = 0.247) than those from loess ravines (ΦST = 0.120) and the biosphere reserve (ΦST = 0.142). Although the diversity metrics were to a small extent lower for populations from kurgans than from larger refugia we conclude that all studied populations of the species still preserve high genetic variability and are valuable for protection. To what extent this pattern holds true under continuous fragmentation in the future must be carefully monitored.

Using genetic algorithms to calibrate a water quality model.

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Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

2007-03-15

With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

Zebrafish models flex their muscles to shed light on muscular dystrophies.

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Berger, Joachim; Currie, Peter D

2012-11-01

Muscular dystrophies are a group of genetic disorders that specifically affect skeletal muscle and are characterized by progressive muscle degeneration and weakening. To develop therapies and treatments for these diseases, a better understanding of the molecular basis of muscular dystrophies is required. Thus, identification of causative genes mutated in specific disorders and the study of relevant animal models are imperative. Zebrafish genetic models of human muscle disorders often closely resemble disease pathogenesis, and the optical clarity of zebrafish embryos and larvae enables visualization of dynamic molecular processes in vivo. As an adjunct tool, morpholino studies provide insight into the molecular function of genes and allow rapid assessment of candidate genes for human muscular dystrophies. This unique set of attributes makes the zebrafish model system particularly valuable for the study of muscle diseases. This review discusses how recent research using zebrafish has shed light on the pathological basis of muscular dystrophies, with particular focus on the muscle cell membrane and the linkage between the myofibre cytoskeleton and the extracellular matrix.

Comparing ESC and iPSC—Based Models for Human Genetic Disorders

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Tomer Halevy

2014-10-01

Full Text Available Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs from patients’ somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn’t be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

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Halevy, Tomer; Urbach, Achia

2014-10-24

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics