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Sample records for genetic effects model

  1. 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.

  2. 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

  3. Modeling genetic imprinting effects of DNA sequences with multilocus polymorphism data

    Directory of Open Access Journals (Sweden)

    Staud Roland

    2009-08-01

    Full Text Available Abstract Single nucleotide polymorphisms (SNPs represent the most widespread type of DNA sequence variation in the human genome and they have recently emerged as valuable genetic markers for revealing the genetic architecture of complex traits in terms of nucleotide combination and sequence. Here, we extend an algorithmic model for the haplotype analysis of SNPs to estimate the effects of genetic imprinting expressed at the DNA sequence level. The model provides a general procedure for identifying the number and types of optimal DNA sequence variants that are expressed differently due to their parental origin. The model is used to analyze a genetic data set collected from a pain genetics project. We find that DNA haplotype GAC from three SNPs, OPRKG36T (with two alleles G and T, OPRKA843G (with alleles A and G, and OPRKC846T (with alleles C and T, at the kappa-opioid receptor, triggers a significant effect on pain sensitivity, but with expression significantly depending on the parent from which it is inherited (p = 0.008. With a tremendous advance in SNP identification and automated screening, the model founded on haplotype discovery and statistical inference may provide a useful tool for genetic analysis of any quantitative trait with complex inheritance.

  4. 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.

  5. 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.

  6. [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.

  7. Genetic effects of ionising radiation

    International Nuclear Information System (INIS)

    Saunders, P.

    1981-01-01

    The mutagenic effects of ionising radiation on germ cells with resulting genetic abnormalities in subsequent generations, are considered. Having examined a simple model to explain the interaction of ionising radiation with genetic material and discussed its limitations, the methods whereby mutations are transmitted are discussed. Methods of estimating genetic risks and the results of such studies are examined. (U.K.)

  8. Effect of Keishibukuryogan on Genetic and Dietary Obesity Models

    Directory of Open Access Journals (Sweden)

    Fengying Gao

    2015-01-01

    Full Text Available Obesity has been recognized as one of the most important risk factors for a variety of chronic diseases, such as diabetes, hypertension/cardiovascular diseases, steatosis/hepatitis, and cancer. Keishibukuryogan (KBG, Gui Zhi Fu Ling Wan in Chinese is a traditional Chinese/Japanese (Kampo medicine that has been known to improve blood circulation and is also known for its anti-inflammatory or scavenging effect. In this study, we evaluated the effect of KBG in two distinct rodent models of obesity driven by either a genetic (SHR/NDmcr-cp rat model or dietary (high-fat diet-induced mouse obesity model mechanism. Although there was no significant effect on the body composition in either the SHR rat or the DIO mouse models, KBG treatment significantly decreased the serum level of leptin and liver TG level in the DIO mouse, but not in the SHR rat model. Furthermore, a lower fat deposition in liver and a smaller size of adipocytes in white adipose tissue were observed in the DIO mice treated with KBG. Importantly, we further found downregulation of genes involved in lipid metabolism in the KBG-treated liver, along with decreased liver TG and cholesterol level. Our present data experimentally support in fact that KBG can be an attractive Kampo medicine to improve obese status through a regulation of systemic leptin level and/or lipid metabolism.

  9. 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...

  10. 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.

  11. Noise in Genetic Toggle Switch Models

    Directory of Open Access Journals (Sweden)

    Andrecut M.

    2006-06-01

    Full Text Available In this paper we study the intrinsic noise effect on the switching behavior of a simple genetic circuit corresponding to the genetic toggle switch model. The numerical results obtained from a noisy mean-field model are compared to those obtained from the stochastic Gillespie simulation of the corresponding system of chemical reactions. Our results show that by using a two step reaction approach for modeling the transcription and translation processes one can make the system to lock in one of the steady states for exponentially long times.

  12. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  13. Sex-specific genetic effects in physical activity: results from a quantitative genetic analysis.

    Science.gov (United States)

    Diego, Vincent P; de Chaves, Raquel Nichele; Blangero, John; de Souza, Michele Caroline; Santos, Daniel; Gomes, Thayse Natacha; dos Santos, Fernanda Karina; Garganta, Rui; Katzmarzyk, Peter T; Maia, José A R

    2015-08-01

    The objective of this study is to present a model to estimate sex-specific genetic effects on physical activity (PA) levels and sedentary behaviour (SB) using three generation families. The sample consisted of 100 families covering three generations from Portugal. PA and SB were assessed via the International Physical Activity Questionnaire short form (IPAQ-SF). Sex-specific effects were assessed by genotype-by-sex interaction (GSI) models and sex-specific heritabilities. GSI effects and heterogeneity were tested in the residual environmental variance. SPSS 17 and SOLAR v. 4.1 were used in all computations. The genetic component for PA and SB domains varied from low to moderate (11% to 46%), when analyzing both genders combined. We found GSI effects for vigorous PA (p = 0.02) and time spent watching television (WT) (p < 0.001) that showed significantly higher additive genetic variance estimates in males. The heterogeneity in the residual environmental variance was significant for moderate PA (p = 0.02), vigorous PA (p = 0.006) and total PA (p = 0.001). Sex-specific heritability estimates were significantly higher in males only for WT, with a male-to-female difference in heritability of 42.5 (95% confidence interval: 6.4, 70.4). Low to moderate genetic effects on PA and SB traits were found. Results from the GSI model show that there are sex-specific effects in two phenotypes, VPA and WT with a stronger genetic influence in males.

  14. Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

    International Nuclear Information System (INIS)

    Chung, K K; Do, D Q

    2010-01-01

    In order to model relationships between chemical structures and biological effects in quantitative structure–activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data

  15. Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens.

    Science.gov (United States)

    Jasouri, M; Zamani, P; Alijani, S

    2017-10-01

    1. A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared. 2. Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits. 3. Estimates of heritability (h 2 ) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28-32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d 2 ) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m 2 ) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c 2 ) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30. 4. Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and

  16. Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions

    Directory of Open Access Journals (Sweden)

    Alexandre eBureau

    2015-07-01

    Full Text Available Effects of genetic variants on the risk of complex diseases estimated from association studies are typically small. Nonetheless, variants may have important effects in presence of specific levels of environmental exposures, and when a trait related to the disease (endophenotype is either normal or impaired. We propose polytomous and transition models to represent the relationship between disease, endophenotype, genotype and environmental exposure in family studies. Model coefficients were estimated using generalized estimating equations and were used to derive gene-environment interaction effects and genotype effects at specific levels of exposure. In a simulation study, estimates of the effect of a genetic variant were substantially higher when both an endophenotype and an environmental exposure modifying the variant effect were taken into account, particularly under transition models, compared to the alternative of ignoring the endophenotype. Illustration of the proposed modeling with the metabolic syndrome, abdominal obesity, physical activity and polymorphisms in the NOX3 gene in the Quebec Family Study revealed that the positive association of the A allele of rs1375713 with the metabolic syndrome at high levels of physical activity was only detectable in subjects without abdominal obesity, illustrating the importance of taking into account the abdominal obesity endophenotype in this analysis.

  17. The effect of selection on genetic parameter estimates

    African Journals Online (AJOL)

    Unknown

    The South African Journal of Animal Science is available online at ... A simulation study was carried out to investigate the effect of selection on the estimation of genetic ... The model contained a fixed effect, random genetic and random.

  18. 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.

  19. Genetic Allee effects and their interaction with ecological Allee effects.

    Science.gov (United States)

    Wittmann, Meike J; Stuis, Hanna; Metzler, Dirk

    2018-01-01

    It is now widely accepted that genetic processes such as inbreeding depression and loss of genetic variation can increase the extinction risk of small populations. However, it is generally unclear whether extinction risk from genetic causes gradually increases with decreasing population size or whether there is a sharp transition around a specific threshold population size. In the ecological literature, such threshold phenomena are called 'strong Allee effects' and they can arise for example from mate limitation in small populations. In this study, we aim to (i) develop a meaningful notion of a 'strong genetic Allee effect', (ii) explore whether and under what conditions such an effect can arise from inbreeding depression due to recessive deleterious mutations, and (iii) quantify the interaction of potential genetic Allee effects with the well-known mate-finding Allee effect. We define a strong genetic Allee effect as a genetic process that causes a population's survival probability to be a sigmoid function of its initial size. The inflection point of this function defines the critical population size. To characterize survival-probability curves, we develop and analyse simple stochastic models for the ecology and genetics of small populations. Our results indicate that inbreeding depression can indeed cause a strong genetic Allee effect, but only if individuals carry sufficiently many deleterious mutations (lethal equivalents). Populations suffering from a genetic Allee effect often first grow, then decline as inbreeding depression sets in and then potentially recover as deleterious mutations are purged. Critical population sizes of ecological and genetic Allee effects appear to be often additive, but even superadditive interactions are possible. Many published estimates for the number of lethal equivalents in birds and mammals fall in the parameter range where strong genetic Allee effects are expected. Unfortunately, extinction risk due to genetic Allee effects

  20. Indirect genetic effects and kin recognition

    DEFF Research Database (Denmark)

    Alemu, Setegn Worku; Berg, Peer; Janss, Luc

    2014-01-01

    Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models. The tradi......Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models...... present a reduced model that yields estimates of the total heritable effects on kin, on non-kin and on all social partners of an individual, as well as the total heritable variance for response to selection. Finally we discuss the consequences of analysing data in which IGEs depend on relatedness using...

  1. A genome-wide survey of transgenerational genetic effects in autism.

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    Kathryn M Tsang

    Full Text Available Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10(-4 that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.

  2. 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...

  3. Graphical models for genetic analyses

    DEFF Research Database (Denmark)

    Lauritzen, Steffen Lilholt; Sheehan, Nuala A.

    2003-01-01

    This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas...... of graphical models and genetics. The potential of graphical models is explored and illustrated through a number of example applications where the genetic element is substantial or dominating....

  4. Direct and maternal genetic effects for birth weight in dorper and ...

    African Journals Online (AJOL)

    Variance components for birth (BWT) in Dorper and Mutton Merino sheep were estimated by Average Information Restricted Maximum Likelihood (AIREML). Animal model was fitted allowing for genetic maternal effects and a genetic covariance between direct and maternal effects. Estimates of heritability for direct genetic ...

  5. 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

  6. 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.

  7. Genetic effects

    International Nuclear Information System (INIS)

    Kato, Hiroo

    1975-01-01

    In 1948-1953 a large scale field survey was conducted to investigate the possible genetic effects of A-bomb radiation on over 70,000 pregnancy terminations in the cities of Hiroshima and Nagasaki. The indices of possible genetic effect including sex ratio, birth weight, frequency of malformation, stillbirth, neonatal death, deaths within 9 months and anthropometric measurements at 9 months of age for these children were investigated in relation to their parent's exposure status to the A-bomb. There were no detectable genetic effects in this sample, except for a slight change in sex ratio which was in the direction to be expected if exposure had induced sex-linked lethal mutations. However, continued study of the sex ratio, based upon birth certificates in Hiroshima and Nagasaki for 1954-1962, did not confirm the earlier trend. Mortality in these children of A-bomb survivors is being followed using a cohort of 54,000 subjects. No clearly significant effect of parental exposure on survival of the children has been demonstrated up to 1972 (age 17 on the average). On the basis of the regression data, the minimal genetic doubling dose of this type of radiation for mutations resulting in death is estimated at 46 rem for the father and 125 rem for the mother. (auth.)

  8. Effect of genetic polymorphisms on development of gout.

    Science.gov (United States)

    Urano, Wako; Taniguchi, Atsuo; Inoue, Eisuke; Sekita, Chieko; Ichikawa, Naomi; Koseki, Yumi; Kamatani, Naoyuki; Yamanaka, Hisashi

    2013-08-01

    To validate the association between genetic polymorphisms and gout in Japanese patients, and to investigate the cumulative effects of multiple genetic factors on the development of gout. Subjects were 153 Japanese male patients with gout and 532 male controls. The genotypes of 11 polymorphisms in the 10 genes that have been indicated to be associated with serum uric acid levels or gout were determined. The cumulative effects of the genetic polymorphisms were investigated using a weighted genotype risk score (wGRS) based on the number of risk alleles and the OR for gout. A model to discriminate between patients with gout and controls was constructed by incorporating the wGRS and clinical factors. C statistics method was applied to evaluate the capability of the model to discriminate gout patients from controls. Seven polymorphisms were shown to be associated with gout. The mean wGRS was significantly higher in patients with gout (15.2 ± 2.01) compared to controls (13.4 ± 2.10; p gout. A prediction model for gout that incorporates genetic and clinical factors may be useful for identifying individuals who are at risk of gout.

  9. Genetic Algorithms for Estimating Effective Parameters in a Lumped Reactor Model for Reactivity Predictions

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico

    2001-01-01

    The control system of a reactor should be able to predict, in real time, the amount of reactivity to be inserted (e.g., by control rod movements and boron injection and dilution) to respond to a given electrical load demand or to undesired, accidental transients. The real-time constraint renders impractical the use of a large, detailed dynamic reactor code. One has, then, to resort to simplified analytical models with lumped effective parameters suitably estimated from the reactor data.The simple and well-known Chernick model for describing the reactor power evolution in the presence of xenon is considered and the feasibility of using genetic algorithms for estimating the effective nuclear parameters involved and the initial nonmeasurable xenon and iodine conditions is investigated. This approach has the advantage of counterbalancing the inherent model simplicity with the periodic reestimation of the effective parameter values pertaining to each reactor on the basis of its recent history. By so doing, other effects, such as burnup, are automatically taken into account

  10. Behavior genetic modeling of human fertility

    DEFF Research Database (Denmark)

    Rodgers, J L; Kohler, H P; Kyvik, K O

    2001-01-01

    Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (First......Try) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males....... A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry....

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

    Science.gov (United States)

    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

  12. The Protective Effect of Minocycline in a Paraquat-Induced Parkinson's Disease Model in Drosophila is Modified in Altered Genetic Backgrounds

    Directory of Open Access Journals (Sweden)

    Arati A. Inamdar

    2012-01-01

    Full Text Available Epidemiological studies link the herbicide paraquat to increased incidence of Parkinson's disease (PD. We previously reported that Drosophila exposed to paraquat recapitulate PD symptoms, including region-specific degeneration of dopaminergic neurons. Minocycline, a tetracycline derivative, exerts ameliorative effects in neurodegenerative disease models, including Drosophila. We investigated whether our environmental toxin-based PD model could contribute to an understanding of cellular and genetic mechanisms of minocycline action and whether we could assess potential interference with these drug effects in altered genetic backgrounds. Cofeeding of minocycline with paraquat prolonged survival, rescued mobility defects, blocked generation of reactive oxygen species, and extended dopaminergic neuron survival, as has been reported previously for a genetic model of PD in Drosophila. We then extended this study to identify potential interactions of minocycline with genes regulating dopamine homeostasis that might modify protection against paraquat and found that deficits in GTP cyclohydrolase adversely affect minocycline rescue. We further performed genetic studies to identify signaling pathways that are necessary for minocycline protection against paraquat toxicity and found that mutations in the Drosophila genes that encode c-Jun N-terminal kinase (JNK and Akt/Protein kinase B block minocycline rescue.

  13. Measuring the genetic influence on human life span: gene-environment interaction and sex-specific genetic effects

    DEFF Research Database (Denmark)

    Tan, Qihua; De Benedictis, G; Yashin, Annatoli

    2001-01-01

    New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographicinf......New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic...

  14. The effect of level of feeding, genetic merit, body condition score and age on biological parameters of a mammary gland model.

    Science.gov (United States)

    Bryant, J R; Lopez-Villalobos, N; Holmes, C W; Pryce, J E; Pitman, G D; Davis, S R

    2007-03-01

    An evolutionary algorithm was applied to a mechanistic model of the mammary gland to find the parameter values that minimised the difference between predicted and actual lactation curves of milk yields in New Zealand Jersey cattle managed at different feeding levels. The effect of feeding level, genetic merit, body condition score at parturition and age on total lactation yields of milk, fat and protein, days in milk, live weight and evolutionary algorithm derived mammary gland parameters was then determined using a multiple regression model. The mechanistic model of the mammary gland was able to fit lactation curves that corresponded to actual lactation curves with a high degree of accuracy. The senescence rate of quiescent (inactive) alveoli was highest at the very low feeding level. The active alveoli population at peak lactation was highest at very low feeding levels, but lower nutritional status at this feeding level prevented high milk yields from being achieved. Genetic merit had a significant linear effect on the active alveoli population at peak and mid to late lactation, with higher values in animals, which had higher breeding values for milk yields. A type of genetic merit × feeding level scaling effect was observed for total yields of milk and fat, and total number of alveoli produced from conception until the end of lactation with the benefits of increases in genetic merit being greater at high feeding levels. A genetic merit × age scaling effect was observed for total lactation protein yields. Initial rates of differentiation of progenitor cells declined with age. Production levels of alveoli from conception to the end of lactation were lowest in 5- to 8-year-old animals; however, in these older animals, quiescent alveoli were reactivated more frequently. The active alveoli population at peak lactation and rates of active alveoli proceeding to quiescence were highest in animals of intermediate body condition scores of 4.0 to 5.0. The results

  15. Applicability of genetic algorithms to parameter estimation of economic models

    Directory of Open Access Journals (Sweden)

    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.

  16. An animal model of differential genetic risk for methamphetamine intake

    Directory of Open Access Journals (Sweden)

    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

  17. 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

  18. 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

  19. 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 ...

  20. 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.

  1. Genetic effects from internally deposited radionuclides

    International Nuclear Information System (INIS)

    Anon.

    1987-01-01

    It was learned in the late 1920's that ionizing radiation could produce genetic effects such as gene mutations and chromosome aberrations. However, at least until 1945, the focus on interest in radiation protection was primarily on somatic effects manifested in the individual exposed. Studies of the genetic effects of radiation using drosophila, however, refocused attention on effects transmitted to the exposed individuals offspring and concern over fallout in the 1950's resulted in efforts to estimate the genetic effects from exposure of human populations to internally deposited radionuclides. No human populations have been identified with burdens of internally deposited radioactive materials which have been shown to produce evidence of transmissible genetic damage. As a result, the research approach has been one in which macromolecular, cellular, and whole animal genetic studies have been combined to estimate genetic effects on humans following the deposition of radioactive materials in the body. The purpose of this report is to update the information available from animal and cellular experiments that relates genetic effects to deposited activity and dose from internally deposited radioactive materials

  2. Eco-genetic modeling of contemporary life-history evolution.

    Science.gov (United States)

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

    2009-10-01

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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. Somatic and genetic effects

    International Nuclear Information System (INIS)

    Broerse, J.J.; Barendsen, G.W.; Kal, H.B.; Kogel, A.J. van der

    1983-01-01

    This book contains the extended abstracts of the contributions of the poster workshop sessions on somatic and genetic effects of the 7th international congress of radiation research. They cover the following main topics: haematopoietic and immune systems, mechanisms of late effects in various tissues, endogenous and exogenous factors in radiation carcinogenesis, teratogenic effects, genetic effects, in vitro transformation, tumour induction in different tissues, carcinogenesis in incorporated tissues, cancer epidemology and risk assessment. refs.; figs.; tabs

  9. 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.

  10. Genetic coding and gene expression - new Quadruplet genetic coding model

    Science.gov (United States)

    Shankar Singh, Rama

    2012-07-01

    Successful demonstration of human genome project has opened the door not only for developing personalized medicine and cure for genetic diseases, but it may also answer the complex and difficult question of the origin of life. It may lead to making 21st century, a century of Biological Sciences as well. Based on the central dogma of Biology, genetic codons in conjunction with tRNA play a key role in translating the RNA bases forming sequence of amino acids leading to a synthesized protein. This is the most critical step in synthesizing the right protein needed for personalized medicine and curing genetic diseases. So far, only triplet codons involving three bases of RNA, transcribed from DNA bases, have been used. Since this approach has several inconsistencies and limitations, even the promise of personalized medicine has not been realized. The new Quadruplet genetic coding model proposed and developed here involves all four RNA bases which in conjunction with tRNA will synthesize the right protein. The transcription and translation process used will be the same, but the Quadruplet codons will help overcome most of the inconsistencies and limitations of the triplet codes. Details of this new Quadruplet genetic coding model and its subsequent potential applications including relevance to the origin of life will be presented.

  11. Context trees for privacy-preserving modeling of genetic data

    NARCIS (Netherlands)

    Kusters, C.J.; Ignatenko, T.

    2016-01-01

    In this work, we use context trees for privacypreserving modeling of genetic sequences. The resulting estimated models are applied for functional comparison of genetic sequences in a privacy preserving way. Here we define privacy as uncertainty about the genetic source sequence given its model and

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

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. Environmental and genetic effects on growth in Timahdite and crossbred lambs in Morocco

    Directory of Open Access Journals (Sweden)

    M. El Fadili

    2000-01-01

    Full Text Available Knowledge of genetic parameters for growth traits of economic importance is required for the development of sheep populations in Morocco. Records on 544 lambs of the Timahdite (T breed and of 756 D'man x Timahdite (DT lambs, all born from 1992 to 1998, were used to estimate genetic parameters for lamb weights at birth, at 30, 70 and 90 days and daily gains from 10-30 days, 30-70 days and 30-90 days for each trait. Separate REML (covariance component estimates were obtained assuming animal models that included the fixed effects of birth year, sex, age of dam, birth type or rearing types and the interaction of birth year by sex, the animal direct genetic effect and the maternal genetic effect. Genetic and phenotypic correlations between traits were estimated with models including the same fixed effects and only additive direct genetic effects. All fixed effects influenced growth traits. The direct heritability estimates for the various body weight and daily gain traits were low to medium and varied between 0.07 and 0.25 in T, and between 0.02 and 0.18 in DT. Maternal heritability ranged from 0.20 to 0.36 in DT, and from 0.01 to 0.10 in T lambs, except for the birth weight (0.53. For all traits the direct and maternal genetic correlations were high and negative in DT (-0.80 and -1.00 and in T (-0.90 and -1.00 lambs. However, the accuracy of such estimates is low due to the small data set used in the present study. The estimates of genetic and phenotypic correlations were positive for all traits, they were particularly high for genetic correlations between weights and weight gains after birth, both in DT and T lambs, and they showed no genetic antagonisms among the growth traits.

  18. 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.

  19. 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.

  20. Population genetics models of local ancestry.

    Science.gov (United States)

    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.

  1. Genetic effects

    International Nuclear Information System (INIS)

    Abrahamson, S.; Bender, M.; Denniston, C.; Schull, W.

    1985-01-01

    Modeling analyses are used to predict the outcomes for two nuclear power plant accident scenarios, the first in which the population received a chronic dose of 0.1 Gy (10 rad) over a 50 year period, the second in which an equivalent population receives acute dose of 2 Gy. In both cases the analyses are projected over a period of five generations. The risk analysis takes on two major forms: the increase in genetic disease that would be observed in the immediate offspring of the exposed population, and the subsequent transmission of the newly induced mutations through future generations. The classes of genetic diseases studied are: dominant gene mutation, X-linked gene mutation, chromosome disorders and multifactorial disorders which involve the interaction of many mutant genes and environmental factors. 28 references, 3 figures, 5 tables

  2. Social genetic effects for growth in pigs differ between boars and gilts

    DEFF Research Database (Denmark)

    Nielsen, Hanne M.; Ask, Birgitte; Madsen, Per

    2018-01-01

    between boars and gilts and that accounting for these differences will improve the predictive ability of a social genetic effects model (SGM). Our data consisted of ADG from 30 to 94 kg for 32,212 uncastrated males (boars) and 48,252 gilts that were raised in sex-specific pens. Data were analyzed using......Average daily gain (ADG) in pigs is affected by the so-called social (or indirect) genetic effects (SGE). However, SGE may differ between sexes because boars grow faster than gilts and their social behaviours differ. We hypothesized that direct genetic effects (DGE) and SGE for ADG in pigs differ...

  3. Including nonadditive genetic effects in mating programs to maximize dairy farm profitability.

    Science.gov (United States)

    Aliloo, H; Pryce, J E; González-Recio, O; Cocks, B G; Goddard, M E; Hayes, B J

    2017-02-01

    We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate

  4. 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 ...

  5. 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

  6. Genetic effects

    International Nuclear Information System (INIS)

    Bender, M.A.; Abrahamson, S.; Denniston, C.; Schull, W.J.

    1989-01-01

    In this chapter, we present a comprehensive analysis of the major classes of genetic diseases that would be increased as a result of an increased gonadal radiation exposure to a human population. The risk analysis takes on two major forms: the increase in genetic disease that would be observed in the immediate offspring of the exposed population, and the subsequent transmission of the newly induced mutations through future generations. The major classes of genetic disease will be induced at different frequencies, and will also impact differentially in terms of survivability and fertility on the affected individuals and their descendants. Some classes of disease will be expected to persist for only a few generations at most. Other types of genetic disease will persist through a longer period. The classes of genetic diseases studied are: dominant gene mutation, X-linked gene mutation, chromosome disorders and multifactorial disorders which involve the interaction of many mutant genes and environmental factors. For each of these classes we have derived the general equations of mutation induction for the male and female germ cells of critical importance in the mutation process. The frequency of induced mutations will be determined initially by the dose received, the type of radiation and, to some extent at high dose, by the manner in which the dose is received. We have used the modeling analyses to predict the outcomes for two nuclear power plant accident scenarios, the first in which the population receives a chronic dose of 0.1 Gy (10 rad) over a 50-year period, the second in which an equivalent population receives an acute dose of 2 Gy. In both cases the analyses are projected over a period of five generations

  7. 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.

  8. Genetic and perinatal effects of abused substances

    Energy Technology Data Exchange (ETDEWEB)

    Brande, M.C.; Zimmerman, A.M.

    1987-01-01

    This book provides an overview of the effects of several abused drugs, including opiates, cannabinoids, alcohol, nicotine, and cocaine, with special emphasis on the actions of these substances at the molecular and cellular levels. The first half deals with genetic effects, including molecular genetics, biochemical genetics, pharmacogenetics, cytogenetics, and genetic toxicity. The second half focuses on perinatal effects and covers: drug abuse during pregnancy; biochemical aspects of marihuana on male reproduction; and long-term behavioral and neuroendocrine effects of perinatal alcohol exposure.

  9. 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)

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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

  16. Genetic effects of radiation

    International Nuclear Information System (INIS)

    Selby, P.B.

    1977-01-01

    Many of the most important findings concerning the genetic effects of radiation have been obtained in the Biology Division of Oak Ridge National Laboratory. The paper focuses on some of the major discoveries made in the Biology Division and on a new method of research that assesses damage to the skeletons of mice whose fathers were irradiated. The results discussed have considerable influence upon estimates of genetic risk in humans from radiation, and an attempt is made to put the estimated amount of genetic damage caused by projected nuclear power development into its proper perspective

  17. Genetic effects of nonionizing electromagnetic fields

    International Nuclear Information System (INIS)

    Lai, Henry

    2001-01-01

    Due to the increased use of electricity and wireless communication devices, there is a concern on whether exposure to nonionizing electromagnetic fields (50/60 Hz fields and radiofrequency radiation) can lead to harmful health effects, particularly, genetic effects and cancer development. This presentation will review recent research on genetic effects of power line frequency and radiofrequency electromagnetic fields. Even though the mechanism of interaction is still unknown, there is increasing evidence that these electromagnetic fields at low intensities can cause genetic damage in cells. There is also evidence suggesting that the effects are caused by oxidative stress. (author)

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. Analyzing age-specific genetic effects on human extreme age survival in cohort-based longitudinal studies

    DEFF Research Database (Denmark)

    Tan, Qihua; Jacobsen, Rune; Sørensen, Mette

    2013-01-01

    The analysis of age-specific genetic effects on human survival over extreme ages is confronted with a deceleration pattern in mortality that deviates from traditional survival models and sparse genetic data available. As human late life is a distinct phase of life history, exploring the genetic...... effects on extreme age survival can be of special interest to evolutionary biology and health science. We introduce a non-parametric survival analysis approach that combines population survival information with individual genotype data in assessing the genetic effects in cohort-based longitudinal studies...

  4. 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.

  5. 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....

  6. 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

  7. Effects of UV radiation on genetic recombination

    International Nuclear Information System (INIS)

    Vlahovic, K.; Zahradka, D.; Petranovic, M.; Petranovic, D.

    1996-01-01

    We have used the model consisting of Escherichia coli cells and l phage to study the effects of UV radiation on genetic recombination. We found two radiation induced processes that reduce or inhibit genetic recombination. One such process leads to the inability of prophage to excise itself from the irradiated bacterial chromosome by the site-specific recombination. The other process was shown to inhibit a type of general recombination by which the prophage transfers one of its genetic markers to the infecting homologous phage. Loss of the prophage ability to take part in both site-specific and general recombination was shown to develop in recB + but not in recB cells. From this we infer that the loss of prophage recombinogenicity in irradiated cells is a consequence of one process in which RecBCD enzyme (the product of recB, recC and recD genes) plays an essential role. (author)

  8. 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-.

  9. 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...

  10. 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...

  11. Assessment of genetic results of ionizing radiation effect on hydrobionts population

    International Nuclear Information System (INIS)

    Pechkurenkov, V.L.; Pokrovskaya, L.G.; Fetisov, A.N.

    1987-01-01

    The effect of dose value and rate on genetic results of chronic radiation with the low dose rate is estimated. At such irradiation the yield of abberant anaphases of embryos is determined by the dose value and it does not depend on the dose rate. The threshold radiation dose rate of the developing fish roe equals 2-3 cGy/h when ignoring the medium modifying factors. The estimation of possible limits of modification of genetic effects of radiation with the low rate when changing environmental factors is given. The model allowing to forecast the appearance of genetic effects of radiation with the low dose rate is constructed. The correspondence between the data obtained in laboratory experiments using organisms living in water reservoirs contaminated experimentally by radionuclides is marked

  12. [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.

  13. 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

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

    Science.gov (United States)

    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

  15. 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

  16. 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.

  17. 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.

  18. Modelling effects of diquat under realistic exposure patterns in genetically differentiated populations of the gastropod Lymnaea stagnalis.

    Science.gov (United States)

    Ducrot, Virginie; Péry, Alexandre R R; Lagadic, Laurent

    2010-11-12

    Pesticide use leads to complex exposure and response patterns in non-target aquatic species, so that the analysis of data from standard toxicity tests may result in unrealistic risk forecasts. Developing models that are able to capture such complexity from toxicity test data is thus a crucial issue for pesticide risk assessment. In this study, freshwater snails from two genetically differentiated populations of Lymnaea stagnalis were exposed to repeated acute applications of environmentally realistic concentrations of the herbicide diquat, from the embryo to the adult stage. Hatching rate, embryonic development duration, juvenile mortality, feeding rate and age at first spawning were investigated during both exposure and recovery periods. Effects of diquat on mortality were analysed using a threshold hazard model accounting for time-varying herbicide concentrations. All endpoints were significantly impaired at diquat environmental concentrations in both populations. Snail evolutionary history had no significant impact on their sensitivity and responsiveness to diquat, whereas food acted as a modulating factor of toxicant-induced mortality. The time course of effects was adequately described by the model, which thus appears suitable to analyse long-term effects of complex exposure patterns based upon full life cycle experiment data. Obtained model outputs (e.g. no-effect concentrations) could be directly used for chemical risk assessment.

  19. 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.

  20. Effect of inclusion or non-inclusion of short lactations and cow and/or dam genetic group on genetic evaluation of Girolando dairy cattle.

    Science.gov (United States)

    Canaza-Cayo, A W; Silva, M V G B; Cobuci, J A; Martins, M F; Lopes, P S

    2016-04-04

    The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

  1. The significant effects of puberty on the genetic diathesis of binge eating in girls.

    Science.gov (United States)

    Klump, Kelly L; Culbert, Kristen M; O'Connor, Shannon; Fowler, Natasha; Burt, S Alexandra

    2017-08-01

    Recent data show significant phenotypic and genetic associations between ovarian hormones and binge eating in adulthood. Theories of hormonal risk focus on puberty and the possibility that hormone activation induces changes in genetic effects that then lead to differential risk for binge eating in postpuberty and adulthood. Although this theory is difficult to test in humans, an indirect test is to examine whether genetic influences on binge eating increase during the pubertal period in girls. Prior work has shown pubertal increases in genetic influences on overall disordered eating symptoms, but no study to date has examined binge eating. The present study was the first to examine these increases for binge eating. Participants included 1,568 female twins (aged 8-25 years) from the Michigan State University Twin Registry. Binge eating and pubertal development were assessed with self-report questionnaires. Twin moderation models showed significant linear increases in genetic effects from prepuberty (5%) to postpuberty (42%), even after controlling for the effects of age and body mass index. Results provide critical support for increased genetic influences on binge eating during puberty. Additional studies are needed to identify hormonal mechanisms and fully test contemporary models of ovarian hormone risk. © 2017 Wiley Periodicals, Inc.

  2. 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...

  3. Health effects model for nuclear power plant accident consequence analysis. Part I. Introduction, integration, and summary. Part II. Scientific basis for health effects models

    Energy Technology Data Exchange (ETDEWEB)

    Evans, J.S.; Moeller, D.W.; Cooper, D.W.

    1985-07-01

    Analysis of the radiological health effects of nuclear power plant accidents requires models for predicting early health effects, cancers and benign thyroid nodules, and genetic effects. Since the publication of the Reactor Safety Study, additional information on radiological health effects has become available. This report summarizes the efforts of a program designed to provide revised health effects models for nuclear power plant accident consequence modeling. The new models for early effects address four causes of mortality and nine categories of morbidity. The models for early effects are based upon two parameter Weibull functions. They permit evaluation of the influence of dose protraction and address the issue of variation in radiosensitivity among the population. The piecewise-linear dose-response models used in the Reactor Safety Study to predict cancers and thyroid nodules have been replaced by linear and linear-quadratic models. The new models reflect the most recently reported results of the follow-up of the survivors of the bombings of Hiroshima and Nagasaki and permit analysis of both morbidity and mortality. The new models for genetic effects allow prediction of genetic risks in each of the first five generations after an accident and include information on the relative severity of various classes of genetic effects. The uncertainty in modeloling radiological health risks is addressed by providing central, upper, and lower estimates of risks. An approach is outlined for summarizing the health consequences of nuclear power plant accidents. 298 refs., 9 figs., 49 tabs.

  4. Health effects model for nuclear power plant accident consequence analysis. Part I. Introduction, integration, and summary. Part II. Scientific basis for health effects models

    International Nuclear Information System (INIS)

    Evans, J.S.; Moeller, D.W.; Cooper, D.W.

    1985-07-01

    Analysis of the radiological health effects of nuclear power plant accidents requires models for predicting early health effects, cancers and benign thyroid nodules, and genetic effects. Since the publication of the Reactor Safety Study, additional information on radiological health effects has become available. This report summarizes the efforts of a program designed to provide revised health effects models for nuclear power plant accident consequence modeling. The new models for early effects address four causes of mortality and nine categories of morbidity. The models for early effects are based upon two parameter Weibull functions. They permit evaluation of the influence of dose protraction and address the issue of variation in radiosensitivity among the population. The piecewise-linear dose-response models used in the Reactor Safety Study to predict cancers and thyroid nodules have been replaced by linear and linear-quadratic models. The new models reflect the most recently reported results of the follow-up of the survivors of the bombings of Hiroshima and Nagasaki and permit analysis of both morbidity and mortality. The new models for genetic effects allow prediction of genetic risks in each of the first five generations after an accident and include information on the relative severity of various classes of genetic effects. The uncertainty in modeloling radiological health risks is addressed by providing central, upper, and lower estimates of risks. An approach is outlined for summarizing the health consequences of nuclear power plant accidents. 298 refs., 9 figs., 49 tabs

  5. 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.

  6. Health effects models for nuclear power plant accident consequence analysis: Low LET radiation: Part 2, Scientific bases for health effects models

    Energy Technology Data Exchange (ETDEWEB)

    Abrahamson, S.; Bender, M.; Book, S.; Buncher, C.; Denniston, C.; Gilbert, E.; Hahn, F.; Hertzberg, V.; Maxon, H.; Scott, B.

    1989-05-01

    This report provides dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Two-parameter Weibull hazard functions are recommended for estimating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary and gastrointestinal syndromes -- are considered. Linear and linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid and ''other''. The category, ''other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also provided. For most cancers, both incidence and mortality are addressed. Linear and linear-quadratic models are also recommended for assessing genetic risks. Five classes of genetic disease -- dominant, x-linked, aneuploidy, unbalanced translocation and multifactorial diseases --are considered. In addition, the impact of radiation-induced genetic damage on the incidence of peri-implantation embryo losses is discussed. The uncertainty in modeling radiological health risks is addressed by providing central, upper, and lower estimates of all model parameters. Data are provided which should enable analysts to consider the timing and severity of each type of health risk. 22 refs., 14 figs., 51 tabs.

  7. Health effects models for nuclear power plant accident consequence analysis: Low LET radiation: Part 2, Scientific bases for health effects models

    International Nuclear Information System (INIS)

    Abrahamson, S.; Bender, M.; Book, S.

    1989-05-01

    This report provides dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Two-parameter Weibull hazard functions are recommended for estimating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary and gastrointestinal syndromes -- are considered. Linear and linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid and ''other''. The category, ''other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also provided. For most cancers, both incidence and mortality are addressed. Linear and linear-quadratic models are also recommended for assessing genetic risks. Five classes of genetic disease -- dominant, x-linked, aneuploidy, unbalanced translocation and multifactorial diseases --are considered. In addition, the impact of radiation-induced genetic damage on the incidence of peri-implantation embryo losses is discussed. The uncertainty in modeling radiological health risks is addressed by providing central, upper, and lower estimates of all model parameters. Data are provided which should enable analysts to consider the timing and severity of each type of health risk. 22 refs., 14 figs., 51 tabs

  8. 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

  9. 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...

  10. 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

  11. 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.

  12. 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

  13. Genomic Model with Correlation Between Additive and Dominance Effects.

    Science.gov (United States)

    Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

    2018-05-09

    Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant

  14. 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

  15. 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.

  16. 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...

  17. 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 ...

  18. 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.

  19. 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.

  20. 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.

  1. Effectiveness of students worksheet based on mastery learning in genetics subject

    Science.gov (United States)

    Megahati, R. R. P.; Yanti, F.; Susanti, D.

    2018-05-01

    Genetics is one of the subjects that must be followed by students in Biology education department. Generally, students do not like the genetics subject because of genetics concepts difficult to understand and the unavailability of a practical students worksheet. Consequently, the complete learning process (mastery learning) is not fulfilled and low students learning outcomes. The aim of this study develops student worksheet based on mastery learning that practical in genetics subject. This research is a research and development using 4-D models. The data analysis technique used is the descriptive analysis that describes the results of the practicalities of students worksheets based on mastery learning by students and lecturer of the genetic subject. The result is the student worksheet based on mastery learning on genetics subject are to the criteria of 80,33% and 80,14%, which means that the students worksheet practical used by lecturer and students. Student’s worksheet based on mastery learning effective because it can increase the activity and student learning outcomes.

  2. Genetic effects of ionising radiation

    International Nuclear Information System (INIS)

    Saunders, P.A.H.

    1991-12-01

    Ionizing radiation effects on the gem cells, which can result in genetic abnormalities, are described. The basic mechanisms of radiation interactions with chromosomes, or specifically DNA, which can result in radiation induced mutation are discussed. Methods of estimating genetic risks, and some values for quantitative risk estimates are given. (U.K.). 13 refs., 2 figs., 1 tab

  3. Indirect Genetic Effects for group-housed animals

    DEFF Research Database (Denmark)

    Alemu, Setegn Worku

    This thesis investigated social interactions in group-housed animals. The main findings of this thesis: 1) Statistical methods to estimate indirect genetic effects when interactions differ between kin vs. non-kin were developed. 2) Indirect genetic effects contribute a substantial amount...... of heritable variation for bite mark traits in group-housed min. 3) Indirect genetic effects estimation needs to take into account systematic interactions due to sex or kin for bite mark trait in group-housed min. 4) Genomic selection can be used to increase the response to selection for survival time in Brown...

  4. Genetically uniform strains of fish as laboratory models for experimental studies of the effects of ionizing radiation

    International Nuclear Information System (INIS)

    Woodhead, A.D.; Setlow, R.B.; Hart, R.W.

    1979-01-01

    The advantages are discussed of using a genetically uniform test animal such as the amazon molly, Poecilia formosa, to reduce the biotic variability in experimental determination of the effects of ionizing radiation on aquatic ecosystems. Besides a cost reduction from using less organisms for these radiation-effect studies, another significant advantage of the higher precision responses due to homozygous genetic material is the assessment of radiation effects at the molecular and cellular levels. (author)

  5. Cost-effectiveness of MODY genetic testing: translating genomic advances into practical health applications.

    Science.gov (United States)

    Naylor, Rochelle N; John, Priya M; Winn, Aaron N; Carmody, David; Greeley, Siri Atma W; Philipson, Louis H; Bell, Graeme I; Huang, Elbert S

    2014-01-01

    OBJECTIVE To evaluate the cost-effectiveness of a genetic testing policy for HNF1A-, HNF4A-, and GCK-MODY in a hypothetical cohort of type 2 diabetic patients 25-40 years old with a MODY prevalence of 2%. RESEARCH DESIGN AND METHODS We used a simulation model of type 2 diabetes complications based on UK Prospective Diabetes Study data, modified to account for the natural history of disease by genetic subtype to compare a policy of genetic testing at diabetes diagnosis versus a policy of no testing. Under the screening policy, successful sulfonylurea treatment of HNF1A-MODY and HNF4A-MODY was modeled to produce a glycosylated hemoglobin reduction of -1.5% compared with usual care. GCK-MODY received no therapy. Main outcome measures were costs and quality-adjusted life years (QALYs) based on lifetime risk of complications and treatments, expressed as the incremental cost-effectiveness ratio (ICER) (USD/QALY). RESULTS The testing policy yielded an average gain of 0.012 QALYs and resulted in an ICER of 205,000 USD. Sensitivity analysis showed that if the MODY prevalence was 6%, the ICER would be ~50,000 USD. If MODY prevalence was >30%, the testing policy was cost saving. Reducing genetic testing costs to 700 USD also resulted in an ICER of ~50,000 USD. CONCLUSIONS Our simulated model suggests that a policy of testing for MODY in selected populations is cost-effective for the U.S. based on contemporary ICER thresholds. Higher prevalence of MODY in the tested population or decreased testing costs would enhance cost-effectiveness. Our results make a compelling argument for routine coverage of genetic testing in patients with high clinical suspicion of MODY.

  6. Bias, accuracy and impact of indirect genetic effects in infectious diseases

    Directory of Open Access Journals (Sweden)

    Debby eLipschutz-Powell

    2012-10-01

    Full Text Available Selection for improved host response to infectious disease offers a desirable alternative to chemical treatment but has proven difficult in practice, due to low heritability estimates of disease traits. Disease data from field studies is often binary, indicating whether an individual has become infected or not following exposure to an infectious disease. Numerous studies have shown that from this data one can infer genetic variation in individuals’ underlying susceptibility. In a previous study, we showed that with an Indirect Genetic Effect (IGE model it is possible to capture some genetic variation in infectivity, if present, as well as in susceptibility. Infectivity is the propensity of transmitting infection upon contact with a susceptible individual. It is an important factor determining the severity of an epidemic. However, there are severe shortcomings with the Standard IGE models as they do not accommodate the dynamic nature of disease data. Here we adjust the Standard IGE model to (1 make expression of infectivity dependent on the individuals’ disease status (Case Model and (2 to include timing of infection (Case-ordered Model. The models are evaluated by comparing impact of selection, bias and accuracy of each model using simulated binary disease data. These were generated for populations with known variation in susceptibility and infectivity thus allowing comparisons between estimated and true breeding values. Overall the Case Model provided better estimates for host genetic susceptibility and infectivity compared to the Standard Model in terms of bias, impact and accuracy. Furthermore, these estimates were strongly influenced by epidemiological characteristics. However, surprisingly, the Case Ordered model performed considerably worse than the Standard and the Case Models, pointing towards limitations in incorporating disease dynamics into conventional variance component estimation methodology and software used in animal breeding.

  7. Mechano-genetic DNA hydrogels as a simple, reconstituted model to probe the effect of active fluctuations on gene transcription

    Science.gov (United States)

    Nguyen, Dan; Saleh, Omar

    Active fluctuations - non-directed fluctuations attributable, not to thermal energy, but to non-equilibrium processes - are thought to influence biology by increasing the diffusive motion of biomolecules. Dense DNA regions within cells (i.e. chromatin) are expected to exhibit such phenomena, as they are cross-linked networks that continually experience propagating forces arising from dynamic cellular activity. Additional agitation within these gene-encoding DNA networks could have potential genetic consequences. By changing the local mobility of transcriptional machinery and regulatory proteins towards/from their binding sites, and thereby influencing transcription rates, active fluctuations could prove to be a physical means of modulating gene expression. To begin probing this effect, we construct genetic DNA hydrogels, as a simple, reconstituted model of chromatin, and quantify transcriptional output from these hydrogels in the presence/absence of active fluctuations.

  8. Plasticity effect of rider-horse interaction on genetic evaluations for Show Jumping discipline in sport horses.

    Science.gov (United States)

    Bartolomé, E; Menéndez-Buxadera, A; Molina, A; Valera, M

    2018-04-01

    To obtain a sport horse that excels in the highest levels of competition, breeders must take into account certain genetic and environmental factors that could influence the sport horse's performance, such as the rider-horse interaction (RHI). The main aim of this study was to describe this interaction in a genetic model by modelling it in relation to the horse's age. A total of 31,129 sport results from Spanish Sport Horses were used from a total of 1,101 animals evaluated, and these were grouped in three age levels and had been ridden by 606 different riders. Only riders who had ridden more than one horse (and vice-versa) were considered for the analyses. Five linear models with different random effects were analysed according to the covariates, the homogeneity/heterogeneity of the RHI and the relevant residual random effects. The model of best fit was then selected for the genetic evaluation of the animal. In general, models including the RHI effect (M2, M4 and M5) fitted better than the other models, and the best fit was obtained for M4 (with heterogeneous residual variance). The genetic variance increased constantly with age, whereas heritability showed a response on three intervals. This study revealed the varied evolution of the RHI with age, showing the different "plastic abilities" of this relationship. © 2018 Blackwell Verlag GmbH.

  9. Effect of genetic variation in a Drosophila model of diabetes-associated misfolded human proinsulin.

    Science.gov (United States)

    He, Bin Z; Ludwig, Michael Z; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Vilhjálmsson, Bjarni J; Jiang, Pengyao; Park, Soo-Young; Tamarina, Natalia A; Selleck, Scott B; Wittkopp, Patricia J; Bell, Graeme I; Kreitman, Martin

    2014-02-01

    The identification and validation of gene-gene interactions is a major challenge in human studies. Here, we explore an approach for studying epistasis in humans using a Drosophila melanogaster model of neonatal diabetes mellitus. Expression of the mutant preproinsulin (hINS(C96Y)) in the eye imaginal disc mimics the human disease: it activates conserved stress-response pathways and leads to cell death (reduction in eye area). Dominant-acting variants in wild-derived inbred lines from the Drosophila Genetics Reference Panel produce a continuous, highly heritable distribution of eye-degeneration phenotypes in a hINS(C96Y) background. A genome-wide association study (GWAS) in 154 sequenced lines identified a sharp peak on chromosome 3L, which mapped to a 400-bp linkage block within an intron of the gene sulfateless (sfl). RNAi knockdown of sfl enhanced the eye-degeneration phenotype in a mutant-hINS-dependent manner. RNAi against two additional genes in the heparan sulfate (HS) biosynthetic pathway (ttv and botv), in which sfl acts, also modified the eye phenotype in a hINS(C96Y)-dependent manner, strongly suggesting a novel link between HS-modified proteins and cellular responses to misfolded proteins. Finally, we evaluated allele-specific expression difference between the two major sfl-intronic haplotypes in heterozygtes. The results showed significant heterogeneity in marker-associated gene expression, thereby leaving the causal mutation(s) and its mechanism unidentified. In conclusion, the ability to create a model of human genetic disease, map a QTL by GWAS to a specific gene, and validate its contribution to disease with available genetic resources and the potential to experimentally link the variant to a molecular mechanism demonstrate the many advantages Drosophila holds in determining the genetic underpinnings of human disease.

  10. THE EFFECT OF PHANTOM GROUPS ON GENETIC TREND

    African Journals Online (AJOL)

    Helena Theron

    In an animal model evaluation of breeding values it is assumed that the base animals are all at the .... these values over the daughters of a sire reduces the stochastic component and represents a genetic ... To test whether the genetic trend is over- or underestimated, a regression model is fitted to the DYD ... parameter.

  11. 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.

  12. Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Canetta, Raffaele

    2004-01-01

    In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved

  13. Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Marseguerra, Marzio E-mail: marzio.marseguerra@polimi.it; Zio, Enrico E-mail: enrico.zio@polimi.it; Canetta, Raffaele

    2004-07-01

    In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved.

  14. 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.

  15. 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.

  16. 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.

  17. Strategies for MCMC computation in quantitative genetics

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  18. Estimating effective landscape distances and movement corridors: Comparison of habitat and genetic data

    Science.gov (United States)

    Maria C. Mateo-Sanchez; Niko Balkenhol; Samuel Cushman; Trinidad Perez; Ana Dominguez; Santiago Saura

    2015-01-01

    Resistance models provide a key foundation for landscape connectivity analyses and are widely used to delineate wildlife corridors. Currently, there is no general consensus regarding the most effective empirical methods to parameterize resistance models, but habitat data (species’ presence data and related habitat suitability models) and genetic data are the...

  19. 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.

  20. Indirect Genetic Effects and the Spread of Infectious Disease: Are We Capturing the Full Heritable Variation Underlying Disease Prevalence?

    Science.gov (United States)

    Lipschutz-Powell, Debby; Woolliams, John A.; Bijma, Piter; Doeschl-Wilson, Andrea B.

    2012-01-01

    Reducing disease prevalence through selection for host resistance offers a desirable alternative to chemical treatment. Selection for host resistance has proven difficult, however, due to low heritability estimates. These low estimates may be caused by a failure to capture all the relevant genetic variance in disease resistance, as genetic analysis currently is not taylored to estimate genetic variation in infectivity. Host infectivity is the propensity of transmitting infection upon contact with a susceptible individual, and can be regarded as an indirect effect to disease status. It may be caused by a combination of physiological and behavioural traits. Though genetic variation in infectivity is difficult to measure directly, Indirect Genetic Effect (IGE) models, also referred to as associative effects or social interaction models, allow the estimation of this variance from more readily available binary disease data (infected/non-infected). We therefore generated binary disease data from simulated populations with known amounts of variation in susceptibility and infectivity to test the adequacy of traditional and IGE models. Our results show that a conventional model fails to capture the genetic variation in infectivity inherent in populations with simulated infectivity. An IGE model, on the other hand, does capture some of the variation in infectivity. Comparison with expected genetic variance suggests that there is scope for further methodological improvement, and that potential responses to selection may be greater than values presented here. Nonetheless, selection using an index of estimated direct and indirect breeding values was shown to have a greater genetic selection differential and reduced future disease risk than traditional selection for resistance only. These findings suggest that if genetic variation in infectivity substantially contributes to disease transmission, then breeding designs which explicitly incorporate IGEs might help reduce disease

  1. Shared genetic effects between hepatic steatosis and fibrosis: A prospective twin study

    Science.gov (United States)

    Cui, Jeffrey; Chen, Chi-Hua; Lo, Min-Tzu; Schork, Nicholas; Bettencourt, Ricki; Gonzalez, Monica P; Bhatt, Archana; Hooker, Jonathan; Shaffer, Katherine; Nelson, Karen E; Long, Michelle T; Brenner, David A; Sirlin, Claude B; Loomba, Rohit

    2016-01-01

    Introduction Nonalcoholic fatty liver disease (NAFLD) is associated with metabolic risk factors including hypertension and dyslipidemia, and may progress to liver fibrosis. Previous studies have shown that hepatic steatosis and fibrosis are heritable but whether they have a significant shared gene effect is unknown. This study aimed to examine the shared gene effects between hepatic steatosis, fibrosis, and their associations with metabolic risk factors. Methods This is a cross-sectional analysis of a prospective cohort of well-characterized, community-dwelling twins (45 monozygotic, 20 dizygotic twin pairs, 130 total subjects) from Southern California. Hepatic steatosis was assessed with MRI-proton density fat fraction (MRI-PDFF) and hepatic fibrosis was assessed with magnetic resonance elastography (MRE). A standard bivariate twin AE model was used to estimate the proportion of phenotypic variance between two phenotypes accounted for by additive genetic effects (A) and individual-specific environmental effects (E). Genetic correlations (rG) estimated from this model represent the degree to which the genetic determinants of two phenotypes overlap. Results The mean (±SD) age and BMI were 47.1 (±21.9) years and 26.9 (±6.5) kg/m2, respectively. 20% (26/130) of the cohort had hepatic steatosis (MRI-PDFF ≥5%) and 8.2% (10/122) had hepatic fibrosis (MRE ≥3Kpa). Blood pressure (systolic and diastolic), triglycerides, glucose, homeostatic model assessment of insulin resistance (HOMA-IR), insulin, hemoglobin A1c (HbA1c), and low high-density lipoprotein (HDL) had significant shared gene effects with hepatic steatosis. Triglycerides, glucose, HOMA-IR, insulin, HbA1c, and low HDL had significant shared gene effects with hepatic fibrosis. Hepatic steatosis and fibrosis had a highly significant shared gene effect of 0.756 (95% CI: 0.716–1, psteatosis pathogenesis may also be involved with fibrosis pathogenesis. PMID:27315352

  2. 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.

  3. Genetic instability model for cancer risk in A-bomb survivors

    International Nuclear Information System (INIS)

    Niwa, Ohtsura

    1998-01-01

    This review was written rather against Mendelsohn's reductionist model for cancer risk in A-bomb survivors in following chapters. Assumptions for carcinogenic process: mutation of a cell to the cancer cell and its proliferation. Multi-step theory for carcinogenesis and age of crisis: induction of cancer by accumulation of cancer-related gene mutations which being linear to time (age). Effect of exogenous hit in the multi-step theory: radiation as an exogenous hit to damage DNA. Dose-effect relationship for cancer risk in the survivors and the problem for the latent period: for solid tumors, dose-effect relationship is linear and shortening of the latent period is not observed. Considerations on cancer data in adulthood exposure/Indirect effect model in radiation carcinogenesis: solid cancer data supporting the indirect effect model. Possible mechanism for radiation-induced long-term increase of natural mutation frequency: genetic instability remaining in the irradiated cells which being a basis of the indirect effect model. Notes for considerations of carcinogenicity in exposed people/Difference in carcinogenic mechanisms due to age. The author concluded that the radiation-induced carcinogenesis is deeply related with the natural carcinogenesis and particularly for solid cancers, it can not be explained by the classic reductionist model. (K.H.)

  4. 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.

  5. 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.

  6. 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

  7. 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.

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

    Science.gov (United States)

    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

  9. Genetic effects of low-level irradiation

    International Nuclear Information System (INIS)

    Selby, P.B.

    1980-01-01

    Recent estimates of the genetic effects of radiation by two widely recognized committees (BEIR III and UNSCEAR 1977) are based to a large extent on data collected in mice using either the specific-locus method or the approach of empirically determining the nature and extent of radiation-induced genetic damage to the skeleton. Both committees made use of doubling-dose and direct methods of estimating genetic hazard. Their estimates can be applied to assessments of risk resulting from medical irradiation in terms both of risk to the population at large and to the individual

  10. Effectiveness of an online curriculum for medical students on genetics, genetic testing and counseling

    Directory of Open Access Journals (Sweden)

    Mary P. Metcalf

    2010-01-01

    Full Text Available Background: It is increasingly important that physicians have a thorough understanding of the basic science of human genetics and the ethical, legal and social implications (ELSI associated with genetic testing and counseling. Methods: The authors developed a series of web-based courses for medical students on these topics. The course modules are interactive, emphasize clinical case studies, and can easily be incorporated into existing medical school curricula. Results: Results of a ‘real world’ effectiveness trial indicate that the courses have a statistically significant effect on knowledge, attitude, intended behavior and self-efficacy related to genetic testing (p<0.001; N varies between 163 and 596 for each course. Conclusions: The results indicate that this curriculum is an effective tool for educating medical students on the ELSI associated with genetic testing and for promoting positive changes in students' confidence, counseling attitudes and behaviors.

  11. 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

  12. A comparative study on genetic effects of artificial and natural habitat fragmentation on Loropetalum chinense (Hamamelidaceae) in Southeast China.

    Science.gov (United States)

    Yuan, N; Comes, H P; Cao, Y N; Guo, R; Zhang, Y H; Qiu, Y X

    2015-06-01

    Elucidating the demographic and landscape features that determine the genetic effects of habitat fragmentation has become fundamental to research in conservation and evolutionary biology. Land-bridge islands provide ideal study areas for investigating the genetic effects of habitat fragmentation at different temporal and spatial scales. In this context, we compared patterns of nuclear microsatellite variation between insular populations of a shrub of evergreen broad-leaved forest, Loropetalum chinense, from the artificially created Thousand-Island Lake (TIL) and the Holocene-dated Zhoushan Archipelago of Southeast China. Populations from the TIL region harboured higher levels of genetic diversity than those from the Zhoushan Archipelago, but these differences were not significant. There was no correlation between genetic diversity and most island features, excepting a negative effect of mainland-island distance on allelic richness and expected heterozygosity in the Zhoushan Archipelago. In general, levels of gene flow among island populations were moderate to high, and tests of alternative models of population history strongly favoured a gene flow-drift model over a pure drift model in each region. In sum, our results showed no obvious genetic effects of habitat fragmentation due to recent (artificial) or past (natural) island formation. Rather, they highlight the importance of gene flow (most likely via seed) in maintaining genetic variation and preventing inter-population differentiation in the face of habitat 'insularization' at different temporal and spatial scales.

  13. 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.

  14. 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...

  15. Using human genetics to predict the effects and side-effects of drugs

    DEFF Research Database (Denmark)

    Stender, Stefan; Tybjærg-Hansen, Anne

    2016-01-01

    PURPOSE OF REVIEW: 'Genetic proxies' are increasingly being used to predict the effects of drugs. We present an up-to-date overview of the use of human genetics to predict effects and adverse effects of lipid-targeting drugs. RECENT FINDINGS: LDL cholesterol lowering variants in HMG-Coenzyme A re...

  16. 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

  17. 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.

  18. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    Science.gov (United States)

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

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

    Science.gov (United States)

    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…

  20. Effects of methylphenidate on attentional set-shifting in a genetic model of attention-deficit/hyperactivity disorder.

    Science.gov (United States)

    Cao, Ai-hua; Yu, Lin; Wang, Yu-wei; Wang, Jun-mei; Yang, Le-jin; Lei, Ge-Fei

    2012-02-28

    Although deficits of attentional set-shifting have been reported in individuals with attention deficit/hyperactivity disorder (ADHD), it is rarely examined in animal models. This study compared spontaneously hypertensive rats (SHRs; a genetic animal model of ADHD) and Wistar-Kyoto (WKY) and Sprague-Dawley (SD) rats (normoactive control strains), on attentional set-shifting task (ASST) performance. Furthermore, the dose-effects of methylphenidate (MPH) on attentional set-shifting of SHR were investigated. In experiment 1, ASST procedures were conducted in SHR, WKY and SD rats of 8 each at the age of 5 weeks. Mean latencies at the initial phase, error types and numbers, and trials to criteria at each stage were recorded. In experiment 2, 24 SHR rats were randomly assigned to 3 groups of 8 each-- MPH-L (lower dose), MPH-H (higher dose), and SHR-vehicle groups. From 3 weeks, they were administered 2.5 mg/kg or 5 mg/kg MPH or saline respectively for 14 consecutive days. All rats were tested in the ASST at the age of 5 weeks. The SHRs generally exhibited poorer performance on ASST than the control WKY and SD rats. Significant strain effects on mean latency [F (2, 21) = 639.636, p attentional set-shifting. Our study provides evidence that MPH may improve the SHR's performance on attentional set-shifting and lower dose is more effective than higher dose.

  1. 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.

  2. Influence of different dose irradiation on genetic effect in mice somatic and germ cells

    International Nuclear Information System (INIS)

    Kostrova, L.N.; Molofej, V.P.; Mosseh, I.B.

    2007-01-01

    Comparison of clastogenic effects of different radiation doses in somatic and germ cells of one the same animals has been studied. Correlation analysis allows to extrapolate genetic effects from somatic cells to germ ones. This can be useful for human model elaboration. (authors)

  3. 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.

  4. Enhanced computational methods for quantifying the effect of geographic and environmental isolation on genetic differentiation

    NARCIS (Netherlands)

    Botta, Filippo; Eriksen, Casper; Fontaine, Michael Christophe; Guillot, Gilles

    2015-01-01

    In a recent paper, Bradburd et al. (2013) proposed a model to quantify the relative effect ofgeographic and environmental distance on genetic differentiation. Here, we enhance this method in several ways. 1. We modify the covariance model so as to fit better with mainstream geostatistical models and

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

    Science.gov (United States)

    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.

  6. 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.

  7. 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.

  8. Genetic and chromosomal effects of ionizing radiation

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    The genetic and chromosomal effects of ionizing radiations deal with those effects in the descendants of the individuals irradiated. The information base concerning genetic and chromosomal injury to humans from radiation is less adequate than is the information base for cancer and leukemia. As a result, it is not possible to make the kinds of quantitative estimates that have been made for carcinogenesis in previous chapters of this book. The chapter includes a detailed explanation of various types of genetic injuries such as chromosomal diseases, x-linked diseases, autosomal dominant diseases, recessive diseases, and irregularly inherited diseases. Quantitative estimates of mutation rates and incidences are given based on atomic bomb survivors data

  9. Genetic effects of radiation. Annex I

    International Nuclear Information System (INIS)

    1982-01-01

    This Annex is aimed at an updating of the 1977 UNSCEAR report, which presented a detailed review of the genetic effects of ionizing radiation, especially those parts that require significant revisions in the light of new data. There is an extensive bibliography with over 1000 references. Particular emphasis is given to those data that are relevant to the evaluation of genetic radiation hazards in man.

  10. Biophysical models of radiobiological effects

    International Nuclear Information System (INIS)

    Obaturov, G.M.

    1987-01-01

    Radiobiological effect models at different organization levels, developed by the author, are presented. Classification and analysis of concepts and biophysical models at molecular, genetic and cellular levels, developed by Soviet and foreign authors in comparison to inherent models, are conducted from the viewpoint of system approach to radiobiological processes and of modelling principles. Models are compared with each other, limits of their applicability and drawbacks are determined. Evaluation of the model truthfulness is conducted according to a number of criteria, ways of further investigations and experimental examination of some models are proposed

  11. Conservation of biodiversity in sugar pine: effects of the blister rust epidemic on genetic diversity

    Science.gov (United States)

    Constance I. Millar; Bohun B. Kinloch; Robert D. Westfall

    1992-01-01

    Genetic diversity in sugar plne will be severely reduced by the blister rust pandemic predicted within the next 50 to 75 years. We model effects of the epidemic on genetic diversity at the stand and landscape levels for both natural and artificial regeneration. In natural stands, because natural frequencies of the dominant gene (R) for resistance are low, the most...

  12. 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.

  13. Estimation of Genetic Effects from Generation Means in Maize (Zea mays L.)

    International Nuclear Information System (INIS)

    Ligeyo, D.O.; Ayiecho, P.O.

    1999-01-01

    Estimates of mean, additive, dominance, additive * additive, additive * dominance and dominance * dominance genetic effects were obtained for six crosses from four inbred lines of maize for grain yield. All the genetic effects contributed to the inheritance of yield. However not all genetic effects are present in all crosses at all locations. Both additive dominance genetic effects were responsible for the manifestation variability in grain yield, though the dominance genetic effect was preponderant in all cases. In most cases additive * additive and additive * dominance effects were more important contributors to inheritance than dominance * dominance gene effects at all locations.In all cases the manifestation of various genetic effects varied according to crosses and experimental sites

  14. 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...

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  17. Education reduces the effects of genetic susceptibilities to poor physical health

    DEFF Research Database (Denmark)

    Johnson, Wendy; Kyvik, Kirsten Ohm; Mortensen, Erik L

    2010-01-01

    BACKGROUND: Greater education is associated with better physical health. This has been of great concern to public health officials. Most demonstrations show that education influences mean levels of health. Little is known about the influence of education on variance in health status, or about how...... this influence may impact the underlying genetic and environmental sources of health problems. This study explored these influences. METHODS: In a 2002 postal questionnaire, 21 522 members of same-sex pairs in the Danish Twin Registry born between 1931 and 1982 reported physical health in the 12-item Short Form...... Health Survey. We used quantitative genetic models to examine how genetic and environmental variance in physical health differed with level of education, adjusting for birth-year effects. RESULTS: and Conclusions As expected, greater education was associated with better physical health. Greater education...

  18. 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

  19. 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

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

    Science.gov (United States)

    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

  1. Non-genetic effects on growth characteristics of Brahman cattle

    Directory of Open Access Journals (Sweden)

    Nicacia Hernández-Hernández

    2015-01-01

    Full Text Available Objective. To determine how some non-genetic factors influence weights at birth (BW, weaning (WW and yearling (YW of Brahman calves. Materials and methods. Data corresponding to 58257, 57045 and 40364 for BW, WW and YW, respectively, were analyzed. The models included the effects of year and season of birth and sex, and were considered simple interactions. Results. All effects were significant (p0.05 on WW. The average general BW, WW and YW were 32±3.2, 188±37.7 and 291±56.8 kg, respectively. Variables evaluated that take into account the year of birth show a trend to increase weight each year. In relation to the birth season on BW and YW, it was observed that calves born during the rainy season were heavier than those born during the dry season. Similarly, male calves were heavier than females at birth, weaning and one year of age. The effects of the analyzed interactions were significant (p0.05 for BW and WW. Conclusions. The studied non-genetic factors were important and should be taken into account in management strategies when striving to increase the efficiency of the productive system.

  2. 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.

  3. Genome-wide association study of handedness excludes simple genetic models

    Science.gov (United States)

    Armour, J AL; Davison, A; McManus, I C

    2014-01-01

    Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183

  4. 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.

  5. 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.

  6. Genetic parameters of body weight and ascites in broilers: effect of different incidence rates of ascites syndrome.

    Science.gov (United States)

    Ahmadpanah, J; Ghavi Hossein-Zadeh, N; Shadparvar, A A; Pakdel, A

    2017-02-01

    1. The objectives of the current study were to investigate the effect of incidence rate (5%, 10%, 20%, 30% and 50%) of ascites syndrome on the expression of genetic characteristics for body weight at 5 weeks of age (BW5) and AS and to compare different methods of genetic parameter estimation for these traits. 2. Based on stochastic simulation, a population with discrete generations was created in which random mating was used for 10 generations. Two methods of restricted maximum likelihood and Bayesian approach via Gibbs sampling were used for the estimation of genetic parameters. A bivariate model including maternal effects was used. The root mean square error for direct heritabilities was also calculated. 3. The results showed that when incidence rates of ascites increased from 5% to 30%, the heritability of AS increased from 0.013 and 0.005 to 0.110 and 0.162 for linear and threshold models, respectively. 4. Maternal effects were significant for both BW5 and AS. Genetic correlations were decreased by increasing incidence rates of ascites in the population from 0.678 and 0.587 at 5% level of ascites to 0.393 and -0.260 at 50% occurrence for linear and threshold models, respectively. 5. The RMSE of direct heritability from true values for BW5 was greater based on a linear-threshold model compared with the linear model of analysis (0.0092 vs. 0.0015). The RMSE of direct heritability from true values for AS was greater based on a linear-linear model (1.21 vs. 1.14). 6. In order to rank birds for ascites incidence, it is recommended to use a threshold model because it resulted in higher heritability estimates compared with the linear model and that BW5 could be one of the main components of selection goals.

  7. Effects of genetically modified T2A-1 rice on the GI health of rats after 90-day supplement.

    Science.gov (United States)

    Yuan, Yanfang; Xu, Wentao; He, Xiaoyun; Liu, Haiyan; Cao, Sishuo; Qi, Xiaozhe; Huang, Kunlun; Luo, Yunbo

    2013-01-01

    Bacillus thuringiensis insecticidal toxin (Bt) rice will be commercialized as a main food source. Traditional safety assessments on genetically modified products pay little attention on gastrointestinal (GI) health. More data about GI health of Bt rice must be provided to dispel public' doubts about the potential effects on human health. We constructed an improved safety assessment animal model using a basic subchronic toxicity experiment, measuring a range of parameters including microflora composition, intestinal permeability, epithelial structure, fecal enzymes, bacterial activity, and intestinal immunity. Significant differences were found between rice-fed groups and AIN93G-fed control groups in several parameters, whereas no differences were observed between genetically modified and non-genetically modified groups. No adverse effects were found on GI health resulting from genetically modified T2A-1 rice. In conclusion, this study may offer a systematic safety assessment model for GM material with respect to the effects on GI health.

  8. An Intelligent Model for Pairs Trading Using Genetic Algorithms.

    Science.gov (United States)

    Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

    2015-01-01

    Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

  9. 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,

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

    Science.gov (United States)

    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.

  11. Evaluation of cytoplasmic genetic effects for production and ...

    African Journals Online (AJOL)

    uvp

    2014-12-03

    Dec 3, 2014 ... Cytoplasmic genetic effects are transmitted directly only from mother to offspring through mitochondrial DNA. Normal genetic .... inheritance in three synthetic lines of beef cattle differing in mature size. J. Anim. Sci. 69, 745.

  12. 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.

  13. lme4qtl: linear mixed models with flexible covariance structure for genetic studies of related individuals.

    Science.gov (United States)

    Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel

    2018-02-27

    Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .

  14. Genetic and environmental effects on body mass index from infancy to the onset of adulthood

    DEFF Research Database (Denmark)

    Silventoinen, Karri; Jelenkovic, Aline; Sund, Reijo

    2016-01-01

    BACKGROUND: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking. OBJECTIVES: We analyzed the genetic and environmental contributions to BMI variation from infancy...... were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling. RESULTS: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive...... environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained...

  15. Selecting the Best Forecasting-Implied Volatility Model Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    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.

  16. Genetic parameters and environmental effects on temperament score and reproductive traits of Nellore cattle.

    Science.gov (United States)

    Barrozo, D; Buzanskas, M E; Oliveira, J A; Munari, D P; Neves, H H R; Queiroz, S A

    2012-01-01

    Animal temperament is a trait of economic relevance and its use as a selection criterion requires the identification of environmental factors that influence this trait, as well as the estimation of its genetic variability and interrelationship with other traits. The objectives of this study were to evaluate the effect of the covariates dam age at calving (ADC), long yearling age (YA) and long yearling weight (YW) on temperament score (T) and to estimate genetic parameters for T, scrotal circumference (SC) at long YA and age at first calving (AFC) in Nellore cattle participating in a selection program. The traits were analyzed by the restricted maximum likelihood method under a multiple-trait animal model. For all traits, contemporary group was included as a fixed effect and additive genetic and residual as random effects. In addition to these effects, YA, YW and ADC were considered for analyzing T. In the case of SC and AFC, the effect of long YW was included as a covariate. Genetic parameters were estimated for and between traits. The three covariates significantly influenced T. The heritability estimates for T, SC and AFC were 0.18 ± 0.02, 0.53 ± 0.04 and 0.23 ± 0.08, respectively. The genetic correlations between T and SC, and T and AFC were -0.07 ± 0.17 and -0.06 ± 0.19, respectively. The genetic correlation estimated between SC and AFC was -0.57 ± 0.16. In conclusion, a response to selection for T, SC and AFC is expected and selection for T does not imply correlated responses with the other traits.

  17. Genetic and environmental influence on asthma

    DEFF Research Database (Denmark)

    Skadhauge, L.R.; Christensen, Kaare; Kyvik, Kirsten Ohm

    1999-01-01

    The aim of this study was to estimate the relative influence of genetic and environmental factors on the aetiology of asthma. The classic twin study design was used to analyse data on self-reported asthma obtained by a questionnaire mailed to 34,076 individuals, aged 12-41 yrs and originating from...... in the monozygotic than in the dizygotic twins. Using biometric modelling, a model including additive genetic and nonshared environmental effects provided the best overall fit to the data. According to this model, 73% of the variation in liability to asthma was explained by genetic factors. No sex difference or age......-dependency in the magnitude of genetic effects was observed. The biometric analysis emphasized a major influence of genetic factors in the aetiology of asthma. However, a substantial part of the variation in liability to asthma is due to the impact of environmental factors specific to the individual. There is no evidence...

  18. Genetic radiation effects and natural radioactivity of human population in Brazil

    International Nuclear Information System (INIS)

    Freire-Maia, A.

    1972-01-01

    A study on areas of natural radioactivity is done, covering the genetic effects on human population. The study is done in depth dealing with aspecto such as radioactive area involved, discussion of materials and methods, errors and fallacies, influential factors, models, buildup and natural radioactivity, hypotheses, results and perspectives, etc. It covers 24 localites, 8.572 couples and 43.930 pregnancy cases [pt

  19. 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...

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

    Science.gov (United States)

    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.

  1. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  2. Simulating natural selection in landscape genetics

    Science.gov (United States)

    E. L. Landguth; S. A. Cushman; N. Johnson

    2012-01-01

    Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

  3. A Rational Model In Theoretical Genetics

    Directory of Open Access Journals (Sweden)

    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

  4. Effects of complex life cycles on genetic diversity: cyclical parthenogenesis.

    Science.gov (United States)

    Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

    2016-11-01

    Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks).

  5. 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

  6. Genetic parameter estimates for weaning weight and Kleiber ratio in goats

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    China Supakorn

    2012-04-01

    Full Text Available The research was conducted to evaluate the factors affecting on weaning weight (WW and Kleiber ratio (KR and toestimate genetic parameters for two traits in goats. The fixed factors affecting both traits indicated that year-season of birth,sex, birth type and regression of the Thai Native (TN, Boer (BO and Saanen (SA influenced on WW and KR (P<0.05. Malesin this population were heavier (P<0.05 than females. Weaning weights and KR of single kid were significantly higher (P<0.05 than other birth rearing types. Bivariate analysis of three models (Model 1: without maternal genetic effect, Model 2:with maternal genetic effect and am = 0, and Model 3: with maternal genetic effect and am  0 were used to estimate geneticparameters for this research. Estimated direct heritabilities from all models were 0.26 to 0.38 for WW, and 0.22 to 0.35 for KR.Estimated maternal heritabilities from Model 2 and 3 were 0.09 and 0.12 for WW and 0.08 and 0.11 for KR, respectively. Thedirect genetic and phenotypic correlations between WW and KR were positive and moderate values. Maternal genetic correlationsbetween them were positive and of low values. An antagonistic direct-maternal correlations from Model 3 withintraits and between traits indicated that offspring of does with superior maternal abilities probably may provide an inferiordirect genetic effect in the same trait and between traits. It was therefore possible to rapidly improve WW and KR in thisgoat population through selection, while the adverse effects of direct-maternal correlation within and between traits shouldbe considered. The best fit model would be a model including maternal genetic effect without a direct-maternal genetic covariance.

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

    Science.gov (United States)

    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.

  8. 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

  9. Estimating genetic covariance functions assuming a parametric correlation structure for environmental effects

    Directory of Open Access Journals (Sweden)

    Meyer Karin

    2001-11-01

    Full Text Available Abstract A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects.

  10. 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.

  11. Plant genetic variation mediates an indirect ecological effect between belowground earthworms and aboveground aphids.

    Science.gov (United States)

    Singh, Akanksha; Braun, Julia; Decker, Emilia; Hans, Sarah; Wagner, Agnes; Weisser, Wolfgang W; Zytynska, Sharon E

    2014-10-21

    Interactions between aboveground and belowground terrestrial communities are often mediated by plants, with soil organisms interacting via the roots and aboveground organisms via the shoots and leaves. Many studies now show that plant genetics can drive changes in the structure of both above and belowground communities; however, the role of plant genetic variation in mediating aboveground-belowground interactions is still unclear. We used an earthworm-plant-aphid model system with two aphid species (Aphis fabae and Acyrthosiphon pisum) to test the effect of host-plant (Vicia faba) genetic variation on the indirect interaction between the belowground earthworms (Eisenia veneta) on the aboveground aphid populations. Our data shows that host-plant variety mediated an indirect ecological effect of earthworms on generalist black bean aphids (A. fabae), with earthworms increasing aphid growth rate in three plant varieties but decreasing it in another variety. We found no effect of earthworms on the second aphid species, the pea aphid (A. pisum), and no effect of competition between the aphid species. Plant biomass was increased when earthworms were present, and decreased when A. pisum was feeding on the plant (mediated by plant variety). Although A. fabae aphids were influenced by the plants and worms, they did not, in turn, alter plant biomass. Previous work has shown inconsistent effects of earthworms on aphids, but we suggest these differences could be explained by plant genetic variation and variation among aphid species. This study demonstrates that the outcome of belowground-aboveground interactions can be mediated by genetic variation in the host-plant, but depends on the identity of the species involved.

  12. Bayesian inference on genetic merit under uncertain paternity

    Directory of Open Access Journals (Sweden)

    Tempelman Robert J

    2003-09-01

    Full Text Available Abstract A hierarchical animal model was developed for inference on genetic merit of livestock with uncertain paternity. Fully conditional posterior distributions for fixed and genetic effects, variance components, sire assignments and their probabilities are derived to facilitate a Bayesian inference strategy using MCMC methods. We compared this model to a model based on the Henderson average numerator relationship (ANRM in a simulation study with 10 replicated datasets generated for each of two traits. Trait 1 had a medium heritability (h2 for each of direct and maternal genetic effects whereas Trait 2 had a high h2 attributable only to direct effects. The average posterior probabilities inferred on the true sire were between 1 and 10% larger than the corresponding priors (the inverse of the number of candidate sires in a mating pasture for Trait 1 and between 4 and 13% larger than the corresponding priors for Trait 2. The predicted additive and maternal genetic effects were very similar using both models; however, model choice criteria (Pseudo Bayes Factor and Deviance Information Criterion decisively favored the proposed hierarchical model over the ANRM model.

  13. Effects of methylphenidate on attentional set-shifting in a genetic model of attention-deficit/hyperactivity disorder

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    Cao Ai-hua

    2012-02-01

    Full Text Available Abstract Background Although deficits of attentional set-shifting have been reported in individuals with attention deficit/hyperactivity disorder (ADHD, it is rarely examined in animal models. Methods This study compared spontaneously hypertensive rats (SHRs; a genetic animal model of ADHD and Wistar-Kyoto (WKY and Sprague-Dawley (SD rats (normoactive control strains, on attentional set-shifting task (ASST performance. Furthermore, the dose-effects of methylphenidate (MPH on attentional set-shifting of SHR were investigated. In experiment 1, ASST procedures were conducted in SHR, WKY and SD rats of 8 each at the age of 5 weeks. Mean latencies at the initial phase, error types and numbers, and trials to criteria at each stage were recorded. In experiment 2, 24 SHR rats were randomly assigned to 3 groups of 8 each-- MPH-L (lower dose, MPH-H (higher dose, and SHR-vehicle groups. From 3 weeks, they were administered 2.5 mg/kg or 5 mg/kg MPH or saline respectively for 14 consecutive days. All rats were tested in the ASST at the age of 5 weeks. Results The SHRs generally exhibited poorer performance on ASST than the control WKY and SD rats. Significant strain effects on mean latency [F (2, 21 = 639.636, p p p p p Conclusions The SHR may be impaired in discrimination learning, reversal learning and attentional set-shifting. Our study provides evidence that MPH may improve the SHR's performance on attentional set-shifting and lower dose is more effective than higher dose.

  14. Revised nonstochastic health effects models

    International Nuclear Information System (INIS)

    Yaniv, S.S.; Scott, B.R.

    1991-01-01

    In 1989, the U.S. Nuclear Regulatory Commission (NRC) published a revision of the 1985 report, Health Effects Models for Nuclear Power Plant Accident Consequence Analysis, NUREG/CR-4214, that included models for early occurring and continuing nonstochastic effects, cancers and thyroid nodules, and genetic effects. This paper discusses specific models for lethality from early occurring and continuing effects. For brevity, hematopoietic-syndrome lethality is called hematopoietic death; pulmonary-syndrome lethality is called pulmonary death; and gastrointestinal syndrome lethality is called gastrointestinal death. Two-parameter Weibull risk functions are recommended for estimating the risk of hematopoietic, pulmonary, or gastrointestinal death. The risks are obtained indirectly by using hazard functions; as a result, this type of approach has been called hazard-function modeling and the models generated are called hazard-function models. In the 1989 NUREG/CR-4214 report, changes were made in the parameter values for a number of effects, and the models used to estimate hematopoietic and pulmonary deaths were substantially revised. Upper and lower estimates of model parameters are provided for all early health effects models. In this paper, we discuss the 1989 models for hematopoietic and pulmonary deaths, highlighting the differences between the 1989 and 1985 models. In addition, we give the reasons for which the 1985 models were modified

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

    Directory of Open Access Journals (Sweden)

    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.

  16. Genetic effects of low level radiation

    International Nuclear Information System (INIS)

    Sumner, D.

    1988-01-01

    The author outlines the evidence for genetic effects. The incidence of congenital abnormalities, stillbirths and child deaths has been examined in 70,000 pregnancies in Hiroshima and Nagasaki and compared with pregnancies in an unirradiated control group. No difference was detected in incidence of congenital abnormalities of stillbirths, but there was a small insignificant increase in child deaths when both parents were exposed. The number of children born with chromosome aberrations was slightly higher, but insignificant in the exposed group compared with controls. However, surveys of congenital malformations in children of radiologists and in children of Hanford workers suggest a genetic effect of radiation. Absolute and relative methods of calculating risks and the ICRP risk factor is also briefly discussed. (U.K.)

  17. Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

    Science.gov (United States)

    Steiner, Christopher F.

    2012-01-01

    The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

  18. Detrimental effect of selection for milk yield on genetic tolerance to heat stress in purebred Zebu cattle: Genetic parameters and trends.

    Science.gov (United States)

    Santana, M L; Pereira, R J; Bignardi, A B; Filho, A E Vercesi; Menéndez-Buxadera, A; El Faro, L

    2015-12-01

    In an attempt to determine the possible detrimental effects of continuous selection for milk yield on the genetic tolerance of Zebu cattle to heat stress, genetic parameters and trends of the response to heat stress for 86,950 test-day (TD) milk yield records from 14,670 first lactations of purebred dairy Gir cows were estimated. A random regression model with regression on days in milk (DIM) and temperature-humidity index (THI) values was applied to the data. The most detrimental effect of THI on milk yield was observed in the stage of lactation with higher milk production, DIM 61 to 120 (-0.099kg/d per THI). Although modest variations were observed for the THI scale, a reduction in additive genetic variance as well as in permanent environmental and residual variance was observed with increasing THI values. The heritability estimates showed a slight increase with increasing THI values for any DIM. The correlations between additive genetic effects across the THI scale showed that, for most of the THI values, genotype by environment interactions due to heat stress were less important for the ranking of bulls. However, for extreme THI values, this type of genotype by environment interaction may lead to an important error in selection. As a result of the selection for milk yield practiced in the dairy Gir population for 3 decades, the genetic trend of cumulative milk yield was significantly positive for production in both high (51.81kg/yr) and low THI values (78.48kg/yr). However, the difference between the breeding values of animals at high and low THI may be considered alarming (355kg in 2011). The genetic trends observed for the regression coefficients related to general production level (intercept of the reaction norm) and specific ability to respond to heat stress (slope of the reaction norm) indicate that the dairy Gir population is heading toward a higher production level at the expense of lower tolerance to heat stress. These trends reflect the genetic

  19. 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

  20. 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

    analytical formulations did not have positive effect in reducing prediction error. Unlike the previous observed trend, in case of predicting river flows with Q Q, the genetic programming method with root mean squared error of 3.3501 in comparison with M5 model trees with error of 3.8480 had more satisfied performance. Finally, in the case of predicting river flows with Q, Q,Q, the genetic programming method with root mean squared error of 3.3094 in comparison with M5 model trees with error of 3.5514 presented better predictions. As a result, it can be stated that genetic programming by the best mathematical functions and considering the input parameters of Q,Q,Q, by resulting less root mean squared error and high correlation coefficients had the best performances among others. Also, the results showed that adding more trigonometric functions did not improve the precisions of the predictions. Conclusion: In this research, the intelligent models such as genetic programming and M5 model trees have been used for prediction of monthly flows of Shaharchay River located in East Azerbaijan, Iran. The obtained results showed that the genetic programming by the best mathematical functions and M5 model trees in case of considering the input parameters of Q,Q,Q, by less root mean squared error had the best performances in river flow predictions. As a conclusion, the genetic programming method by specific mathematical functions including four basic operations, logarithm, power and using input parameters of Q,Q,Q, has been proposed as the best and precise model for predicting Shaharchay River flows.

  1. Education reduces the effects of genetic susceptibilities to poor physical health.

    Science.gov (United States)

    Johnson, Wendy; Kyvik, Kirsten Ohm; Mortensen, Erik L; Skytthe, Axel; Batty, G David; Deary, Ian J

    2010-04-01

    Greater education is associated with better physical health. This has been of great concern to public health officials. Most demonstrations show that education influences mean levels of health. Little is known about the influence of education on variance in health status, or about how this influence may impact the underlying genetic and environmental sources of health problems. This study explored these influences. In a 2002 postal questionnaire, 21 522 members of same-sex pairs in the Danish Twin Registry born between 1931 and 1982 reported physical health in the 12-item Short Form Health Survey. We used quantitative genetic models to examine how genetic and environmental variance in physical health differed with level of education, adjusting for birth-year effects. and Conclusions As expected, greater education was associated with better physical health. Greater education was also associated with smaller variance in health status. In both sexes, 2 standard deviations (SDs) above mean educational level, variance in physical health was only about half that among those 2 SDs below. This was because fewer highly educated people reported poor health. There was less total variance in health primarily because there was less genetic variance. Education apparently reduced expression of genetic susceptibilities to poor health. The patterns of genetic and environmental correlations suggested that this might take place because more educated people manage their environments to protect their health. If so, fostering the personal charactieristics associated with educational attainment could be important in reducing the education-health gradient.

  2. How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects.

    Directory of Open Access Journals (Sweden)

    Christopher H Chandler

    2017-11-01

    Full Text Available For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis.

  3. 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)

  4. Ontogeny of additive and maternal genetic effects: lessons from domestic mammals.

    Science.gov (United States)

    Wilson, Alastair J; Reale, Denis

    2006-01-01

    Evolution of size and growth depends on heritable variation arising from additive and maternal genetic effects. Levels of heritable (and nonheritable) variation might change over ontogeny, increasing through "variance compounding" or decreasing through "compensatory growth." We test for these processes using a meta-analysis of age-specific weight traits in domestic ungulates. Generally, mean standardized variance components decrease with age, consistent with compensatory growth. Phenotypic convergence among adult sheep occurs through decreasing environmental and maternal genetic variation. Maternal variation similarly declines in cattle. Maternal genetic effects are thus reduced with age (both in absolute and relative terms). Significant trends in heritability (decreasing in cattle, increasing in sheep) result from declining maternal and environmental components rather than from changing additive variation. There was no evidence for increasing standardized variance components. Any compounding must therefore be masked by more important compensatory processes. While extrapolation of these patterns to processes in natural population is difficult, our results highlight the inadequacy of assuming constancy in genetic parameters over ontogeny. Negative covariance between direct and maternal genetic effects was common. Negative correlations with additive and maternal genetic variances indicate that antagonistic pleiotropy (between additive and maternal genetic effects) may maintain genetic variance and limit responses to selection.

  5. 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

  6. Estimating non-genetic and genetic parameters of pre-weaning growth traits in Raini Cashmere goat.

    Science.gov (United States)

    Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Mohammadabadi, Mohammadreza

    2012-04-01

    Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability (h(a)(2)) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c(2)) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.

  7. 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.

  8. Genetic effects of high LET radiations

    International Nuclear Information System (INIS)

    Grahn, D.; Garriott, M.L.; Farrington, B.H.; Lee, C.H.; Russell, J.J.

    1981-01-01

    The objectives of this project are: (1) to assess genetic hazards from testicular burdens of 239 Pu and determine its retention and microdistribution in the testis; (2) to compare effects of 239 Pu with single, weekly, and continuous 60 Co gamma irradiation and single and weekly fission neutron irradiation to develop a basis for estimating relative biological effectiveness (RBE); and (3) to develop detailed dose-response data for genetic end points of concern at low doses of neutrons and gamma rays. Comparatively short-term genetic end points are used, namely: (1) the dominant lethal mutation rate in premeiotic and postmeiotic cell stages; (2) the frequency of abnormal sperm head morphology measured at various times after irradiation; and (3) the frequency of reciprocal chromosome translocations induced in spermatogonia and measured at first meiotic metaphase. Male hybrid B6CF 1 mice, 120 days old, are used for all studies. Measures of the retention, microdistributionand pollutant related changes. Assessment of human risk associated with nuclearing collective dose commitment will result in more attention being paid to potential releases of radionuclides at relatively short times after disposal

  9. 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.

  10. Testing for constant nonparametric effects in general semiparametric regression models with interactions

    KAUST Repository

    Wei, Jiawei

    2011-07-01

    We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.

  11. Effect of Coping-Therapy on Mental Health of Mothers with Genetic and Non Genetic Mentally Retarded Children

    Directory of Open Access Journals (Sweden)

    M Alagheband

    2011-04-01

    Full Text Available Introdution: Presence of mentally retarded children as a source of pressure can jeopardize the general health of parents, especially mothers. The range of effect depends on the recognitive evaluation and the individual. The aim of this study was to investigate the effect of coping-therapy on mental health of mothers with genetically and non genetically mentally retarded children referring to Yazd clinical center. Methods: This study was semi experimental and included 40 mothers with mentally retarded children studying in schools supported by the welfare organization of Yazd in 2009- 2010 and were selected by available sampling method. They were divided to two groups; case and control. Before any therapy, all of the mothers answered a general health questionnaire(GHQ28. In the next step, coping-therapy was performed on the case group. In the end, all of the mothers answered the same questionnaire(GHQ28 and data were analyzed by covariance method and t test. Results: The research indicated that coping-therapy has a positive effect on the mental health of mothers with genetically mentally retarded children. This effect is similar on mothers of children with non genetically mental retarded children. Coping-therapy decreases the somatic signs of depression in mothers and improves their sleeping and social efficacy. There was no association of age and educational level of mothers with coping-therapy. Conclusion: Coping-therapy can improve the mental health of mothers of both genetically and non genetically mentally retarded children

  12. Genetic effects of ionizing radiation and repair processes

    International Nuclear Information System (INIS)

    Tuschl, H.

    1986-11-01

    Since DNA (=desoxyribonucleic acid) is the largest molecule within the cell it is the most important target for direct and indirect radiation effects. Within DNA the total genetic information is stored, thus damage to DNA in germ cells causes genetic disorders and damage in somatic cells is implicated in cancer and immunodeficiences. Alterations of DNA structure are not only due to ionizing radiation effects, but also to spontaneous DNA modifications and damage from interactions with environmental ultraviolet light and chemical agents. To maintain its genetic integrity, each organism had to develop different repair systems able to recognize and remove DNA damage. Repeated exposure to a DNA damaging agent can even lead to adaptation processes and increased resistance to the same agent. At normal function of repair systems it can be assumed that the capacity of those systems is adequate to scope with the effects of low radiation doses. (Author)

  13. 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

  14. Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

    Directory of Open Access Journals (Sweden)

    Omnia Gamal El-Dien

    2016-03-01

    Full Text Available The open-pollinated (OP family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure.

  15. The effect of dithiothreitol on radiation-induced genetic damage in Arabidopsis thaliana (L) Heynh

    International Nuclear Information System (INIS)

    Dellaert, L.M.W.

    1980-01-01

    A study was made on the effect of dithiothreitol (DTT; present during irradiation) on M 1 ovule sterility, M 2 embryonic lethals, M 2 chlorophyll mutants and M 2 viable mutants induced with fast neutrons or X-rays in Arabidopsis thaliana. DTT provides considerable protection against both fast-neutron and X-ray induced genetic damage. However, a higher protection was observed against M 1 ovule sterility, than against embryonic lethals, chlorophylls and viable mutants. This implies a significant DTT-induced spectral shift (0.01 < p < 0.05), i.e. a shift in the relative frequencies of the different genetic parameters. This spectral shift is explained on the basis of a specific DTT protection against radiation-induced strand breaks, and by differences in the ratio strand breaks/base damage for the genetic parameters concerned, i.e. a higher ratio for ovule sterility than for the other parameters. The induction of the genetic damage by ionizing radiation, either with or without DTT, is described by a mathematical model, which includes both strand breaks and base damage. The model shows that the resolving power of a test for a 'mutation'spectral shift depends on the relative values of the strandbreak reduction factor of -SH compounds and on the ratio strand breaks/base damage of the genetic parameters. For each genetic parameter the DTT damage reduction factor (DRF) is calculated per irradiation dose, and in addition the average (over-all doses) ratio strand breaks/base damage. (orig.)

  16. Genetic Algorithm Based Microscale Vehicle Emissions Modelling

    Directory of Open Access Journals (Sweden)

    Sicong Zhu

    2015-01-01

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

  17. Genetic and environmental effects on same-sex sexual behavior: a population study of twins in Sweden.

    Science.gov (United States)

    Långström, Niklas; Rahman, Qazi; Carlström, Eva; Lichtenstein, Paul

    2010-02-01

    There is still uncertainty about the relative importance of genes and environments on human sexual orientation. One reason is that previous studies employed self-selected, opportunistic, or small population-based samples. We used data from a truly population-based 2005-2006 survey of all adult twins (20-47 years) in Sweden to conduct the largest twin study of same-sex sexual behavior attempted so far. We performed biometric modeling with data on any and total number of lifetime same-sex sexual partners, respectively. The analyses were conducted separately by sex. Twin resemblance was moderate for the 3,826 studied monozygotic and dizygotic same-sex twin pairs. Biometric modeling revealed that, in men, genetic effects explained .34-.39 of the variance, the shared environment .00, and the individual-specific environment .61-.66 of the variance. Corresponding estimates among women were .18-.19 for genetic factors, .16-.17 for shared environmental, and 64-.66 for unique environmental factors. Although wide confidence intervals suggest cautious interpretation, the results are consistent with moderate, primarily genetic, familial effects, and moderate to large effects of the nonshared environment (social and biological) on same-sex sexual behavior.

  18. Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations.

    Directory of Open Access Journals (Sweden)

    Heather A Lawson

    2011-09-01

    Full Text Available Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS components (obesity, dyslipidemia, and diabetes-related traits. MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL in an F(16 advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002. Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

  19. Facial averageness and genetic quality: Testing heritability, genetic correlation with attractiveness, and the paternal age effect.

    Science.gov (United States)

    Lee, Anthony J; Mitchem, Dorian G; Wright, Margaret J; Martin, Nicholas G; Keller, Matthew C; Zietsch, Brendan P

    2016-01-01

    Popular theory suggests that facial averageness is preferred in a partner for genetic benefits to offspring. However, whether facial averageness is associated with genetic quality is yet to be established. Here, we computed an objective measure of facial averageness for a large sample ( N = 1,823) of identical and nonidentical twins and their siblings to test two predictions from the theory that facial averageness reflects genetic quality. First, we use biometrical modelling to estimate the heritability of facial averageness, which is necessary if it reflects genetic quality. We also test for a genetic association between facial averageness and facial attractiveness. Second, we assess whether paternal age at conception (a proxy of mutation load) is associated with facial averageness and facial attractiveness. Our findings are mixed with respect to our hypotheses. While we found that facial averageness does have a genetic component, and a significant phenotypic correlation exists between facial averageness and attractiveness, we did not find a genetic correlation between facial averageness and attractiveness (therefore, we cannot say that the genes that affect facial averageness also affect facial attractiveness) and paternal age at conception was not negatively associated with facial averageness. These findings support some of the previously untested assumptions of the 'genetic benefits' account of facial averageness, but cast doubt on others.

  20. Genetic effects of organic mercury compounds

    Energy Technology Data Exchange (ETDEWEB)

    Ramel, C

    1967-01-01

    Studies on the genetic and developmental effects of organic mercury compounds on lilies, drosophila, and ice were carried out. It was found that chromosomal and developmental abnormalities were correlated with the administration of mercury compounds.

  1. [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.

  2. 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.

  3. 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

  4. A serial founder effect model for human settlement out of Africa

    OpenAIRE

    Deshpande, Omkar; Batzoglou, Serafim; Feldman, Marcus W.; Luca Cavalli-Sforza, L.

    2008-01-01

    The increasing abundance of human genetic data has shown that the geographical patterns of worldwide genetic diversity are best explained by human expansion out of Africa. This expansion is modelled well by prolonged migration from a single origin in Africa with multiple subsequent serial founding events. We discuss a new simulation model for the serial founder effect out of Africa and compare it with results from previous studies. Unlike previous models, we distinguish colonization events fr...

  5. 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

  6. 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...

  7. 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.

  8. 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.

  9. 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

    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....

  10. 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...

  11. Proceedings of the 15. Berzelius symposium on somatic and genetic effects of ionizing radiation

    International Nuclear Information System (INIS)

    Stigbrand, T.

    1989-01-01

    The symposium begins with a brush up on the physics of ionizing radiation and a background to the natural and man-made source of radiation to which we are exposed. The next section deals with the origin and nature of radiation-induced damage to DNA. The somatic effects of ionizing radiation span from DNA lesions to various effects on cell structure and cell function and effects on whole organs. The somatic effects are immediate as well as long-term, with mental impairment and an increased risk for carcinogenesis as consequences of main concern. The genetic effects of ionizing radiation can result in: infertility, spontaneous abortions, genetic diseases and malformations and increased risk for cancer. This leads over to the problems of risk estimation. Risk estimation which is mainly based on experimental data using animal models, human cell lines and epidemiological studies of exposed and unexposed populations

  12. 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.

  13. General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

    Science.gov (United States)

    de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

    2016-11-01

    Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

  14. Enhanced genetic characterization of influenza A(H3N2) viruses and vaccine effectiveness by genetic group, 2014–2015

    Science.gov (United States)

    Flannery, Brendan; Zimmerman, Richard K.; Gubareva, Larisa V.; Garten, Rebecca J.; Chung, Jessie R.; Nowalk, Mary Patricia; Jackson, Michael L.; Jackson, Lisa A.; Monto, Arnold S.; Ohmit, Suzanne E.; Belongia, Edward A.; McLean, Huong Q.; Gaglani, Manjusha; Piedra, Pedro A.; Mishin, Vasiliy P.; Chesnokov, Anton P.; Spencer, Sarah; Thaker, Swathi N.; Barnes, John R.; Foust, Angie; Sessions, Wendy; Xu, Xiyan; Katz, Jacqueline; Fry, Alicia M.

    2018-01-01

    Background During the 2014–15 US influenza season, expanded genetic characterization of circulating influenza A(H3N2) viruses was used to assess the impact of genetic variability of influenza A(H3N2) viruses on influenza vaccine effectiveness (VE). Methods A novel pyrosequencing assay was used to determine genetic group based on hemagglutinin (HA) gene sequences of influenza A(H3N2) viruses from patients enrolled US Flu Vaccine Effectiveness network sites. Vaccine effectiveness was estimated using a test-negative design comparing vaccination among patients infected with influenza A(H3N2) viruses and uninfected patients. Results Among 9710 enrollees, 1868 (19%) tested positive for influenza A(H3N2); genetic characterization of 1397 viruses showed 1134 (81%) belonged to one HA genetic group (3C.2a) of antigenically drifted H3N2 viruses. Effectiveness of 2014–15 influenza vaccination varied by A(H3N2) genetic group from 1% (95% confidence interval [CI], −14% to 14%) against illness caused by antigenically drifted A(H3N2) group 3C.2a viruses versus 44% (95% CI, 16% to 63%) against illness caused by vaccine-like A(H3N2) group 3C.3b viruses. Conclusion Effectiveness of 2014–15 influenza vaccination varied by genetic group of influenza A(H3N2) virus. Changes in hemagglutinin genes related to antigenic drift were associated with reduced vaccine effectiveness. PMID:27190176

  15. 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.

  16. Genetic interactions matter more in less-optimal environments: a focused review

    Directory of Open Access Journals (Sweden)

    Dustin A. Landers

    2014-08-01

    Full Text Available An increase in the distribution of data points indicates the presence of genetic or environmental modifiers. Mapping of the genetic control of the spread of points, the uniformity, allows us to allocate genetic difference in point distribution to adjacent, cis effects or to independently segregating, trans genetic effects. Our genetic architecture-mapping experiment elucidated the ‘environmental context specificity’ of modifiers, the number and effect size of positive and negative alleles important for uniformity in single and combined stress, and the extent of additivity in estimated allele effects in combined stress environments. We found no alleles for low uniformity in combined stress treatments in the maize mapping population we examined.The major advances in this research area since early 2011 have been in improved methods for modeling of distributions and means and detection of important loci. Double hierarchical general linear models and, more recently, a likelihood ratio formulation have been developed to better model and estimate the genetic and environmental effects in populations. These new methods have been applied to real data sets by the method authors and we now encourage additional development of the software and wider application of the methods. We also propose that simulations of genetic regulatory network models to examine differences in uniformity and systematic exploration of models using shared simulations across communities of researchers would be constructive avenues for developing further insight into the genetic mechanisms of variation control.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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...

  4. 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...

  5. Modelling the Interplay between Lifestyle Factors and Genetic Predisposition on Markers of Type 2 Diabetes Mellitus Risk.

    Science.gov (United States)

    Walker, Celia G; Solis-Trapala, Ivonne; Holzapfel, Christina; Ambrosini, Gina L; Fuller, Nicholas R; Loos, Ruth J F; Hauner, Hans; Caterson, Ian D; Jebb, Susan A

    2015-01-01

    The risk of developing type 2 diabetes mellitus (T2DM) is determined by a complex interplay involving lifestyle factors and genetic predisposition. Despite this, many studies do not consider the relative contributions of this complex array of factors to identify relationships which are important in progression or prevention of complex diseases. We aimed to describe the integrated effect of a number of lifestyle changes (weight, diet and physical activity) in the context of genetic susceptibility, on changes in glycaemic traits in overweight or obese participants following 12-months of a weight management programme. A sample of 353 participants from a behavioural weight management intervention were included in this study. A graphical Markov model was used to describe the impact of the intervention, by dividing the effects into various pathways comprising changes in proportion of dietary saturated fat, physical activity and weight loss, and a genetic predisposition score (T2DM-GPS), on changes in insulin sensitivity (HOMA-IR), insulin secretion (HOMA-B) and short and long term glycaemia (glucose and HbA1c). We demonstrated the use of graphical Markov modelling to identify the importance and interrelationships of a number of possible variables changed as a result of a lifestyle intervention, whilst considering fixed factors such as genetic predisposition, on changes in traits. Paths which led to weight loss and change in dietary saturated fat were important factors in the change of all glycaemic traits, whereas the T2DM-GPS only made a significant direct contribution to changes in HOMA-IR and plasma glucose after considering the effects of lifestyle factors. This analysis shows that modifiable factors relating to body weight, diet, and physical activity are more likely to impact on glycaemic traits than genetic predisposition during a behavioural intervention.

  6. Exploring Genetic and Environmental Effects in Dysphonia: A Twin Study

    Science.gov (United States)

    Simberg, Susanna; Santtila, Pekka; Soveri, Anna; Varjonen, Markus; Sala, Eeva; Sandnabba, N. Kenneth

    2009-01-01

    Purpose: To explore the existence of genetic effects as well as the interaction between potential genetic effects and a voice-demanding occupation on dysphonia. Method: One thousand seven hundred and twenty-eight Finnish twins (555 male; 1,173 female) born between 1961 and 1989 completed a questionnaire concerning vocal symptoms and occupation.…

  7. Genetic and environmental effects of mortality before age 70 years

    DEFF Research Database (Denmark)

    Petersen, Liselotte; Andersen, Per Kragh; Sørensen, Thorkild I.A.

    2008-01-01

    BACKGROUND:: There is a familial influence on risk of many diseases and on mortality in general, which, according to studies of twins, is due to a combination of genetic and environmental effects. Adoption studies, which rest on different assumptions, may also be used to estimate separately...... the genetic and environmental effects on rate of dying. METHODS:: The genetic influence on the rate of dying before age 70 years was investigated by estimation of the associations in total and cause-specific mortality of Danish adoptees and their biologic full and half siblings. Familial environmental...

  8. The Effects of Meiosis/Genetics Integration and Instructional Sequence on College Biology Student Achievement in Genetics.

    Science.gov (United States)

    Browning, Mark

    The purpose of the research was to manipulate two aspects of genetics instruction in order to measure their effects on college, introductory biology students' achievement in genetics. One instructional sequence that was used dealt first with monohybrid autosomal inheritance patterns, then sex-linkage. The alternate sequence was the reverse.…

  9. 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...

  10. Genetic Analysis of Embryo, Cytoplasm and Maternal Effects and Their Environment Interactions for Isoflavone Content in Soybean [Glycine max(L.) Merr.

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Soybean seed products contain isoflavones (genistein, daidzein, and glycitein) that display biological effects when ingested by humans and animals. These effects are species, dose and age dependent. Therefore, the content and quality of isoflavones in soybeans is a key factor to the biological effect. Our objective was to identify the genetic effects that underlie the isoflavone content in soybean seeds. A genetic model for quantitative traits of seeds in diploid plants was applied to estimate the genetic main effects and genotype × environment (GE) interaction effects for the isoflavone content (IC) of soybean seeds by using two years experimental data with an incomplete diallel mating design of six parents. Results showed that the IC of soybean seeds was simultaneously controlled by the genetic effects of maternal,embryo, and cytoplasm, of which maternal genetic effects were most important, followed by embryo and cytoplasmic genetic effects. The main effects of different genetic systems on IC trait were more important than environment interaction effects. The strong dominance effects on isoflavone from residual was made easily by environment conditions. Therefore,the improvement of the IC of soybean seeds would be more efficient when selection is based on maternal plants than that on the single seed. Maternal heritability (65.73%) was most important for IC, followed by embryo heritability (25.87%) and cytoplasmic heritability (8.39%). Based on predicated genetic effects, Yudou 29 and Zheng 90007 were better than other parents for increasing IC in the progeny and improving the quality of soybean. The significant effects of maternal and embryo dominance effects in variance show that the embryo heterosis and maternal heterosis are existent and uninfluenced by environment interaction effects.

  11. Genetic and Environmental Effects on Vocal Symptoms and Their Intercorrelations

    Science.gov (United States)

    Nybacka, Ida; Simberg, Susanna; Santtila, Pekka; Sala, Eeva; Sandnabba, N. Kenneth

    2012-01-01

    Purpose: Recently, Simberg et al. (2009) found genetic effects on a composite variable consisting of 6 vocal symptom items measuring dysphonia. The purpose of the present study was to determine genetic and environmental effects on the individual vocal symptoms in a population-based sample of Finnish twins. Method: The sample comprised 1,728 twins…

  12. PDE Modeling of a Microfluidic Thermal Process for Genetic Analysis Application

    Directory of Open Access Journals (Sweden)

    Reza Banaei Khosroushahi

    2013-01-01

    Full Text Available This paper details the infinite dimensional dynamics of a prototype microfluidic thermal process that is used for genetic analysis purposes. Highly effective infinite dimensional dynamics, in addition to collocated sensor and actuator architecture, require the development of a precise control framework to meet the very tight performance requirements of this system, which are not fully attainable through conventional lumped modeling and controller design approaches. The general partial differential equations describing the dynamics of the system are separated into steady-state and transient parts which are derived for a carefully chosen three-dimensional axisymmetric model. These equations are solved analytically, and the results are verified using an experimentally verified precise finite element method (FEM model. The final combined result is a framework for designing a precise tracking controller applicable to the selected lab-on-a-chip device.

  13. 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.

  14. Genetic basis and detection of unintended effects in genetically modified crop plants

    NARCIS (Netherlands)

    Ladics, G.S.; Bartholomaeus, A.; Bregitzer, P.; Doerrer, N.G.; Gray, A.; Holzhauzer, T.; Jordan, M.; Keese, P.; Kok, E.J.; Macdonald, P.; Parrott, W.; Privalle, L.; Raybould, A.; Rhee, S.Y.; Rice, E.; Romeis, J.; Vaughn, J.; Wal, J.M.; Glenn, K.

    2015-01-01

    In January 2014, an international meeting sponsored by the International Life Sciences Institute/Health and Environmental Sciences Institute and the Canadian Food Inspection Agency titled “Genetic Basis of Unintended Effects in Modified Plants” was held in Ottawa, Canada, bringing together over 75

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

    Directory of Open Access Journals (Sweden)

    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

  16. Applying genetic algorithms for calibrating a hexagonal cellular automata model for the simulation of debris flows characterised by strong inertial effects

    Science.gov (United States)

    Iovine, G.; D'Ambrosio, D.; Di Gregorio, S.

    2005-03-01

    In modelling complex a-centric phenomena which evolve through local interactions within a discrete time-space, cellular automata (CA) represent a valid alternative to standard solution methods based on differential equations. Flow-type phenomena (such as lava flows, pyroclastic flows, earth flows, and debris flows) can be viewed as a-centric dynamical systems, and they can therefore be properly investigated in CA terms. SCIDDICA S 4a is the last release of a two-dimensional hexagonal CA model for simulating debris flows characterised by strong inertial effects. S 4a has been obtained by progressively enriching an initial simplified model, originally derived for simulating very simple cases of slow-moving flow-type landslides. Using an empirical strategy, in S 4a, the inertial character of the flowing mass is translated into CA terms by means of local rules. In particular, in the transition function of the model, the distribution of landslide debris among the cells is obtained through a double cycle of computation. In the first phase, the inertial character of the landslide debris is taken into account by considering indicators of momentum. In the second phase, any remaining debris in the central cell is distributed among the adjacent cells, according to the principle of maximum possible equilibrium. The complexities of the model and of the phenomena to be simulated suggested the need for an automated technique of evaluation for the determination of the best set of global parameters. Accordingly, the model is calibrated using a genetic algorithm and by considering the May 1998 Curti-Sarno (Southern Italy) debris flow. The boundaries of the area affected by the debris flow are simulated well with the model. Errors computed by comparing the simulations with the mapped areal extent of the actual landslide are smaller than those previously obtained without genetic algorithms. As the experiments have been realised in a sequential computing environment, they could be

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

    Directory of Open Access Journals (Sweden)

    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.

  18. A Drosophila model for toxicogenomics: Genetic variation in susceptibility to heavy metal exposure.

    Directory of Open Access Journals (Sweden)

    Shanshan Zhou

    2017-07-01

    Full Text Available The genetic factors that give rise to variation in susceptibility to environmental toxins remain largely unexplored. Studies on genetic variation in susceptibility to environmental toxins are challenging in human populations, due to the variety of clinical symptoms and difficulty in determining which symptoms causally result from toxic exposure; uncontrolled environments, often with exposure to multiple toxicants; and difficulty in relating phenotypic effect size to toxic dose, especially when symptoms become manifest with a substantial time lag. Drosophila melanogaster is a powerful model that enables genome-wide studies for the identification of allelic variants that contribute to variation in susceptibility to environmental toxins, since the genetic background, environmental rearing conditions and toxic exposure can be precisely controlled. Here, we used extreme QTL mapping in an outbred population derived from the D. melanogaster Genetic Reference Panel to identify alleles associated with resistance to lead and/or cadmium, two ubiquitous environmental toxins that present serious health risks. We identified single nucleotide polymorphisms (SNPs associated with variation in resistance to both heavy metals as well as SNPs associated with resistance specific to each of them. The effects of these SNPs were largely sex-specific. We applied mutational and RNAi analyses to 33 candidate genes and functionally validated 28 of them. We constructed networks of candidate genes as blueprints for orthologous networks of human genes. The latter not only provided functional contexts for known human targets of heavy metal toxicity, but also implicated novel candidate susceptibility genes. These studies validate Drosophila as a translational toxicogenomics gene discovery system.

  19. 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.

  20. GENETIC CONTRIBUTION OF RAM ON LITTER SIZE IN ŠUMAVA SHEEP

    Directory of Open Access Journals (Sweden)

    Jitka Schmidová

    2015-09-01

    Full Text Available The objective of the present study was to quantify the service sire effect in terms of (co variance components of born and weaned lambs number and to propose models for the potential inclusion of this effect in the linear equations for breeding value estimation. The database with 21,324 lambings in Šumava sheep from 1992- 2013 was used. The basic model equation for the analysis of variance of litter size contained effects of ewe´s age at lambing, contemporary group, permanent environmental effect of ewe and direct additive genetic effect of ewe. Two modifications of the basic model were used for estimation of service sire effect. The proportions of variance for the service sire effect for number of born and weaned lambs were 2.1% and 2.0%, when service sire was not included into relationship matrix; while included into the relationship matrix and dividing effect into genetic contribution and permanent environment effect refer that nongenetic effect seems to be bigger than genetic (0.013 vs. 0.009 for number of born and 0.017 vs. 0.004 for number of weaned. Changes in other variance components were relatively low, except of contemporary group. Model including service sire effect as a simple random effect without genetic relationship matrix inclusion is recommended for genetic evaluation of litter size traits.

  1. Genetic effects of heavy ion irradiation in maize and soybean

    International Nuclear Information System (INIS)

    Yatou, Osamu; Amano, Etsuo; Takahashi, Tan.

    1992-01-01

    Somatic mutation on leaves of maize and soybean were observed to investigate genetic effects of heavy ion irradiation. Maize seeds were irradiated with N, Fe and U ions and soybean seeds were irradiated with N ions. This is a preliminary report of the experiment, 1) to examine the mutagenic effects of the heavy ion irradiation, and 2) to evaluate the genetic effects of cosmic ray exposure in a space ship outside the earth. (author)

  2. On the genetic effects of low-level tritium

    International Nuclear Information System (INIS)

    Hori, Tada-aka; Nakai, Sayaka

    1976-01-01

    Genetic risk assessment for potential hazard from environmental tritium to man becomes important with increasing nuclear-power industry. The purpose of this short review is to discuss the possible genetic effects of tritium from a view of genetic risk estimation. The discussion is based mainly on our experimental results on the chromosome aberrations induced in human lymphocytes by tritium at the very low-level. The types of chromosome aberrations induced by radiation from tritium incorporated into the cells are mostly chromatid types. The most interesting finding is that the dose-response relationship observed in both tritiated-water and tritiated-thymidine is composed of two phases. The examination on the nature of two-phase dose-response relationship is very important not only for the mechanisms of chromosome aberrations, but also for the evaluation of genetic risk from low-level radiation. (auth.)

  3. Effects of herd origin, AI stud and sire identification on genetic evaluation of Holstein Friesian bulls

    Directory of Open Access Journals (Sweden)

    Giovanni Bittante

    2010-01-01

    Full Text Available The purpose of this study was to estimate the effects of herd origin of bull, AI stud and sire identification number (ID  on official estimated breeding values (EBV for production traits of Holstein Friesian proven bulls. The data included 1,005  Italian Holstein-Friesian bulls, sons of 76 sires, born in 100 herds and progeny tested by 10 AI studs. Bulls were required  to have date of first proof between September 1992 and September 1997, to be born in a herd with at least one other  bull and to have sire and dam with official EBV when bull was selected for progeny testing. Records of sires with only one  son were also discarded. The dependent variable analyzed was the official genetic evaluation for a “quantity and quality  of milk” index (ILQ. The linear model to predict breeding values of bulls included the fixed class effects of herd origin of  bull, AI testing organization, birth year of bull, and estimated breeding values of sire and dam, both as linear covariates.  The R2of the model was 45% and a significant effect was found for genetic merit of sire (P   for herd origin of bull (P   nificant. The range of herd origin effect was 872 kg of ILQ. However, in this study, the causes of this result were not  clear; it may be due to numerous factors, one of which may be preferential treatment on dams of bulls. Analyses of resid-  uals on breeding value of proven bulls for ILQ showed a non significant effect of sire ID, after adjusting for parent aver-  age, herd origin effect and birth year effect. Although the presence of bias in genetic evaluation of dairy bulls is not evi-  dent, further research is recommended firstly to understand the reasons of the significant herd origin effect, secondly to  monitor and guarantee the greatest accuracy and reliability of genetic evaluation procedures. 

  4. 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

  5. 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

  6. Estimation of genetic effects in the presence of multicollinearity in multibreed beef cattle evaluation.

    Science.gov (United States)

    Roso, V M; Schenkel, F S; Miller, S P; Schaeffer, L R

    2005-08-01

    Breed additive, dominance, and epistatic loss effects are of concern in the genetic evaluation of a multibreed population. Multiple regression equations used for fitting these effects may show a high degree of multicollinearity among predictor variables. Typically, when strong linear relationships exist, the regression coefficients have large SE and are sensitive to changes in the data file and to the addition or deletion of variables in the model. Generalized ridge regression methods were applied to obtain stable estimates of direct and maternal breed additive, dominance, and epistatic loss effects in the presence of multicollinearity among predictor variables. Preweaning weight gains of beef calves in Ontario, Canada, from 1986 to 1999 were analyzed. The genetic model included fixed direct and maternal breed additive, dominance, and epistatic loss effects, fixed environmental effects of age of the calf, contemporary group, and age of the dam x sex of the calf, random additive direct and maternal genetic effects, and random maternal permanent environment effect. The degree and the nature of the multicollinearity were identified and ridge regression methods were used as an alternative to ordinary least squares (LS). Ridge parameters were obtained using two different objective methods: 1) generalized ridge estimator of Hoerl and Kennard (R1); and 2) bootstrap in combination with cross-validation (R2). Both ridge regression methods outperformed the LS estimator with respect to mean squared error of predictions (MSEP) and variance inflation factors (VIF) computed over 100 bootstrap samples. The MSEP of R1 and R2 were similar, and they were 3% less than the MSEP of LS. The average VIF of LS, R1, and R2 were equal to 26.81, 6.10, and 4.18, respectively. Ridge regression methods were particularly effective in decreasing the multicollinearity involving predictor variables of breed additive effects. Because of a high degree of confounding between estimates of maternal

  7. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

    Science.gov (United States)

    Veerkamp, R F; Koenen, E P; De Jong, G

    2001-10-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

  8. 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.

  9. Comparative evaluation of fuzzy logic and genetic algorithms models for portfolio optimization

    Directory of Open Access Journals (Sweden)

    Heidar Masoumi Soureh

    2017-03-01

    Full Text Available Selection of optimum methods which have appropriate speed and precision for planning and de-cision-making has always been a challenge for investors and managers. One the most important concerns for them is investment planning and optimization for acquisition of desirable wealth under controlled risk with the best return. This paper proposes a model based on Markowitz the-orem by considering the aforementioned limitations in order to help effective decisions-making for portfolio selection. Then, the model is investigated by fuzzy logic and genetic algorithms, for the optimization of the portfolio in selected active companies listed in Tehran Stock Exchange over the period 2012-2016 and the results of the above models are discussed. The results show that the two studied models had functional differences in portfolio optimization, its tools and the possibility of supplementing each other and their selection.

  10. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM considering different order of Legendre polynomial for the additive genetic effect (4th order and the permanent environmental effect (5th order. Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11 to 0.99 (TD-4 and TD-5. The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.

  11. Effects of genetic distance on heterosis in a Drosophila melanogaster model system

    DEFF Research Database (Denmark)

    Jensen, Charlotte; Ørsted, Michael; Kristensen, Torsten Nygaard

    2018-01-01

    Habitat fragmentation and small population sizes can lead to inbreeding and loss of genetic variation, which can potentially cause inbreeding depression and decrease the ability of populations to adapt to altered environmental conditions. One solution to these genetic problems is the implementation...... of genetic rescue, which re-establishes gene flow between separated populations. Similar techniques are being used in animal and plant breeding to produce superior production animals and plants. To optimize fitness benefits in genetic rescue programs and to secure high yielding domestic varieties in animal...... exceptions to this pattern. The best predictor of heterosis was performance of parental lines with poorly performing parental lines showing higher hybrid vigour when crossed, i.e. the potential for heterosis was proportional to the level of inbreeding depression. Overall, our results show that outcrossing...

  12. Genetic and somatic effects of ionizing radiation

    International Nuclear Information System (INIS)

    1986-01-01

    This is the ninth substantive report of the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) to the General Assembly. This report contains reviews on three special topics in the field of biological effects of ionizing radiation that are among those presently under consideration by the Committee: genetic effects of radiation, dose-response relationships for radiation-induced cancer and biological effects of pre-natal irradiation

  13. The long-term effects of methamphetamine exposure during pre-adolescence on depressive-like behaviour in a genetic animal model of depression.

    Science.gov (United States)

    Mouton, Moné; Harvey, Brian H; Cockeran, Marike; Brink, Christiaan B

    2016-02-01

    Methamphetamine (METH) is a psychostimulant and drug of abuse, commonly used early in life, including in childhood and adolescence. Adverse effects include psychosis, anxiety and mood disorders, as well as increased risk of developing a mental disorder later in life. The current study investigated the long-term effects of chronic METH exposure during pre-adolescence in stress-sensitive Flinders Sensitive Line (FSL) rats (genetic model of depression) and control Flinders Resistant Line (FRL) rats. METH or vehicle control was administered twice daily from post-natal day 19 (PostND19) to PostND34, followed by behavioural testing at either PostND35 (early effects) or long-lasting after withdrawal at PostND60 (early adulthood). Animals were evaluated for depressive-like behaviour, locomotor activity, social interaction and object recognition memory. METH reduced depressive-like behaviour in both FSL and FRL rats at PostND35, but enhanced this behaviour at PostND60. METH also reduced locomotor activity on PostND35 in both FSL and FRL rats, but without effect at PostND60. Furthermore, METH significantly lowered social interaction behaviour (staying together) in both FRL and FSL rats at PostND35 and PostND60, whereas self-grooming time was significantly reduced only at PostND35. METH treatment enhanced exploration of the familiar vs. novel object in the novel object recognition test (nORT) in FSL and FRL rats on PostND35 and PostND60, indicative of reduced cognitive performance. Thus, early-life METH exposure induce social and cognitive deficits. Lastly, early-life exposure to METH may result in acute antidepressant-like effects immediately after chronic exposure, whereas long-term effects after withdrawal are depressogenic. Data also supports a role for genetic predisposition as with FSL rats.

  14. Environmental enrichment imparts disease-modifying and transgenerational effects on genetically-determined epilepsy and anxiety.

    Science.gov (United States)

    Dezsi, Gabi; Ozturk, Ezgi; Salzberg, Michael R; Morris, Margaret; O'Brien, Terence J; Jones, Nigel C

    2016-09-01

    The absence epilepsies are presumed to be caused by genetic factors, but the influence of environmental exposures on epilepsy development and severity, and whether this influence is transmitted to subsequent generations, is not well known. We assessed the effects of environmental enrichment on epilepsy and anxiety outcomes in multiple generations of GAERS - a genetic rat model of absence epilepsy that manifests comorbid elevated anxiety-like behaviour. GAERS were exposed to environmental enrichment or standard housing beginning either prior to, or after epilepsy onset, and underwent EEG recordings and anxiety testing. Then, we exposed male GAERS to early enrichment or standard housing and generated F1 progeny, which also underwent EEG recordings. Hippocampal CRH mRNA expression and DNA methylation were assessed using RT-PCR and pyrosequencing, respectively. Early environmental enrichment delayed the onset of epilepsy in GAERS, and resulted in fewer seizures in adulthood, compared with standard housed GAERS. Enrichment also reduced the frequency of seizures when initiated in adulthood. Anxiety levels were reduced by enrichment, and these anti-epileptogenic and anxiolytic effects were heritable into the next generation. We also found reduced expression of CRH mRNA in GAERS exposed to enrichment, but this was not due to changes in DNA methylation. Environmental enrichment produces disease-modifying effects on genetically determined absence epilepsy and anxiety, and these beneficial effects are transferable to the subsequent generation. Reduced CRH expression was associated with these phenotypic improvements. Environmental stimulation holds promise as a naturalistic therapy for genetically determined epilepsy which may benefit subsequent generations. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Assumed genetic effects of low level irradiation on man

    International Nuclear Information System (INIS)

    Dutrillaux, B.

    1976-01-01

    The significance of human genetic pathology is stated and a study is made of the assumed effect of low level ionizing radiations. The theoretical notions thus derived are compared to experimental data which are poor. A quick survey of the literature shows that is has not yet been possible to establish a direct relationship between an increase of exposure and any genetic effect on man. However, this must not lead to conclude on the innoxiousness of radiation but rather shows how such analyses are difficult in as much as the effect investigated is necessarily low [fr

  16. Integrating the landscape epidemiology and genetics of RNA viruses: rabies in domestic dogs as a model.

    Science.gov (United States)

    Brunker, K; Hampson, K; Horton, D L; Biek, R

    2012-12-01

    Landscape epidemiology and landscape genetics combine advances in molecular techniques, spatial analyses and epidemiological models to generate a more real-world understanding of infectious disease dynamics and provide powerful new tools for the study of RNA viruses. Using dog rabies as a model we have identified how key questions regarding viral spread and persistence can be addressed using a combination of these techniques. In contrast to wildlife rabies, investigations into the landscape epidemiology of domestic dog rabies requires more detailed assessment of the role of humans in disease spread, including the incorporation of anthropogenic landscape features, human movements and socio-cultural factors into spatial models. In particular, identifying and quantifying the influence of anthropogenic features on pathogen spread and measuring the permeability of dispersal barriers are important considerations for planning control strategies, and may differ according to cultural, social and geographical variation across countries or continents. Challenges for dog rabies research include the development of metapopulation models and transmission networks using genetic information to uncover potential source/sink dynamics and identify the main routes of viral dissemination. Information generated from a landscape genetics approach will facilitate spatially strategic control programmes that accommodate for heterogeneities in the landscape and therefore utilise resources in the most cost-effective way. This can include the efficient placement of vaccine barriers, surveillance points and adaptive management for large-scale control programmes.

  17. 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

  18. Genetic effects of ionizing radiations in Eucaryocytes

    International Nuclear Information System (INIS)

    Jullien, Pierre

    1976-01-01

    The litterature on the genetic effects of ionizing radiations is reviewed, especially as concerns specific loci or chromosome mutations. Extrapolation from one species to another is considered as well as extra-nuclear mutations [fr

  19. Effect of Duplicate Genes on Mouse Genetic Robustness: An Update

    Directory of Open Access Journals (Sweden)

    Zhixi Su

    2014-01-01

    Full Text Available In contrast to S. cerevisiae and C. elegans, analyses based on the current knockout (KO mouse phenotypes led to the conclusion that duplicate genes had almost no role in mouse genetic robustness. It has been suggested that the bias of mouse KO database toward ancient duplicates may possibly cause this knockout duplicate puzzle, that is, a very similar proportion of essential genes (PE between duplicate genes and singletons. In this paper, we conducted an extensive and careful analysis for the mouse KO phenotype data and corroborated a strong effect of duplicate genes on mouse genetics robustness. Moreover, the effect of duplicate genes on mouse genetic robustness is duplication-age dependent, which holds after ruling out the potential confounding effect from coding-sequence conservation, protein-protein connectivity, functional bias, or the bias of duplicates generated by whole genome duplication (WGD. Our findings suggest that two factors, the sampling bias toward ancient duplicates and very ancient duplicates with a proportion of essential genes higher than that of singletons, have caused the mouse knockout duplicate puzzle; meanwhile, the effect of genetic buffering may be correlated with sequence conservation as well as protein-protein interactivity.

  20. Multi-objective genetic algorithm parameter estimation in a reduced nuclear reactor model

    Energy Technology Data Exchange (ETDEWEB)

    Marseguerra, M.; Zio, E.; Canetta, R. [Polytechnic of Milan, Dept. of Nuclear Engineering, Milano (Italy)

    2005-07-01

    The fast increase in computing power has rendered, and will continue to render, more and more feasible the incorporation of dynamics in the safety and reliability models of complex engineering systems. In particular, the Monte Carlo simulation framework offers a natural environment for estimating the reliability of systems with dynamic features. However, the time-integration of the dynamic processes may render the Monte Carlo simulation quite burdensome so that it becomes mandatory to resort to validated, simplified models of process evolution. Such models are typically based on lumped effective parameters whose values need to be suitably estimated so as to best fit to the available plant data. In this paper we propose a multi-objective genetic algorithm approach for the estimation of the effective parameters of a simplified model of nuclear reactor dynamics. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest to the actual evolution profiles. A case study is reported in which the real reactor is simulated by the QUAndry based Reactor Kinetics (Quark) code available from the Nuclear Energy Agency and the simplified model is based on the point kinetics approximation to describe the neutron balance in the core and on thermal equilibrium relations to describe the energy exchange between the different loops. (authors)

  1. Multi-objective genetic algorithm parameter estimation in a reduced nuclear reactor model

    International Nuclear Information System (INIS)

    Marseguerra, M.; Zio, E.; Canetta, R.

    2005-01-01

    The fast increase in computing power has rendered, and will continue to render, more and more feasible the incorporation of dynamics in the safety and reliability models of complex engineering systems. In particular, the Monte Carlo simulation framework offers a natural environment for estimating the reliability of systems with dynamic features. However, the time-integration of the dynamic processes may render the Monte Carlo simulation quite burdensome so that it becomes mandatory to resort to validated, simplified models of process evolution. Such models are typically based on lumped effective parameters whose values need to be suitably estimated so as to best fit to the available plant data. In this paper we propose a multi-objective genetic algorithm approach for the estimation of the effective parameters of a simplified model of nuclear reactor dynamics. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest to the actual evolution profiles. A case study is reported in which the real reactor is simulated by the QUAndry based Reactor Kinetics (Quark) code available from the Nuclear Energy Agency and the simplified model is based on the point kinetics approximation to describe the neutron balance in the core and on thermal equilibrium relations to describe the energy exchange between the different loops. (authors)

  2. Genetic effects of ionizing radiation

    International Nuclear Information System (INIS)

    Myers, D.K.; Childs, J.D.

    1980-01-01

    The genetic material in living organisms is susceptible to damage from a wide variety of causes including radiation exposure. Most of this damage is repaired by the organism; the residual damage and damage which is not correctly repaired can lead to genetic changes such as mutations. In lower organisms, most offspring carry an unaltered copy of the genetic information that was present in the parental organism, most of the genetic changes which do occur are not caused by natural background radiation, and the increase in frequency of genetic changes after irradiation at low-dose rates is directly proportional to total radiation dose. The same principles appear to be valid in mammals and other higher organisms. About 105 out of every 1000 humans born suffer from some genetic or partly-genetic condition requiring medical attention at some time. It has been estimated that approximately 1 person in every 2000 born carry a deleterious genetic mutation that was caused by the continued exposure of many generations of our ancestors to natural background radiation. On the same basis, it is predicted that the incidence of genetic diseases would be increased to 106 per 1000 in the children and grandchildren of radiation workers who were exposed to 1 rem per year commencing at age 18. However, there was no detectable change in the health and fitness of mice whose male ancestors were repeatedly exposed to high radiation doses up to 900 rem per generation. (auth)

  3. Using genetic algorithms to calibrate a water quality model.

    Science.gov (United States)

    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.

  4. 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.

  5. A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants.

    Science.gov (United States)

    Goedhart, Paul W; van der Voet, Hilko; Baldacchino, Ferdinando; Arpaia, Salvatore

    2014-04-01

    Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non-target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess-zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.

  6. 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

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

    Science.gov (United States)

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

    2010-10-01

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

  8. Landscape resistance and habitat combine to provide an optimal model of genetic structure and connectivity at the range margin of a small mammal.

    Science.gov (United States)

    Marrotte, R R; Gonzalez, A; Millien, V

    2014-08-01

    We evaluated the effect of habitat and landscape characteristics on the population genetic structure of the white-footed mouse. We develop a new approach that uses numerical optimization to define a model that combines site differences and landscape resistance to explain the genetic differentiation between mouse populations inhabiting forest patches in southern Québec. We used ecological distance computed from resistance surfaces with Circuitscape to infer the effect of the landscape matrix on gene flow. We calculated site differences using a site index of habitat characteristics. A model that combined site differences and resistance distances explained a high proportion of the variance in genetic differentiation and outperformed models that used geographical distance alone. Urban and agriculture-related land uses were, respectively, the most and the least resistant landscape features influencing gene flow. Our method detected the effect of rivers and highways as highly resistant linear barriers. The density of grass and shrubs on the ground best explained the variation in the site index of habitat characteristics. Our model indicates that movement of white-footed mouse in this region is constrained along routes of low resistance. Our approach can generate models that may improve predictions of future northward range expansion of this small mammal. © 2014 John Wiley & Sons Ltd.

  9. Stocking the genetic supermarket: reproductive genetic technologies and collective action problems.

    Science.gov (United States)

    Gyngell, Chris; Douglas, Thomas

    2015-05-01

    Reproductive genetic technologies (RGTs) allow parents to decide whether their future children will have or lack certain genetic predispositions. A popular model that has been proposed for regulating access to RGTs is the 'genetic supermarket'. In the genetic supermarket, parents are free to make decisions about which genes to select for their children with little state interference. One possible consequence of the genetic supermarket is that collective action problems will arise: if rational individuals use the genetic supermarket in isolation from one another, this may have a negative effect on society as a whole, including future generations. In this article we argue that RGTs targeting height, innate immunity, and certain cognitive traits could lead to collective action problems. We then discuss whether this risk could in principle justify state intervention in the genetic supermarket. We argue that there is a plausible prima facie case for the view that such state intervention would be justified and respond to a number of arguments that might be adduced against that view. © 2014 The Authors. Bioethics published by John Wiley & Sons Ltd.

  10. 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

  11. Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

    Science.gov (United States)

    Wen, Yalu; Shen, Xiaoxi; Lu, Qing

    2018-05-31

    With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

  12. 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.

  13. 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.

  14. 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

  15. 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...

  16. Health effects models for nuclear power plant accident consequence analysis

    International Nuclear Information System (INIS)

    Evans, J.S.; Abrahmson, S.; Bender, M.A.; Boecker, B.B.; Scott, B.R.; Gilbert, E.S.

    1993-10-01

    This report is a revision of NUREG/CR-4214, Rev. 1, Part 1 (1990), Health Effects Models for Nuclear Power Plant Accident Consequence Analysis. This revision has been made to incorporate changes to the Health Effects Models recommended in two addenda to the NUREG/CR-4214, Rev. 1, Part 11, 1989 report. The first of these addenda provided recommended changes to the health effects models for low-LET radiations based on recent reports from UNSCEAR, ICRP and NAS/NRC (BEIR V). The second addendum presented changes needed to incorporate alpha-emitting radionuclides into the accident exposure source term. As in the earlier version of this report, models are provided for early and continuing effects, cancers and thyroid nodules, and genetic effects. Weibull dose-response functions are recommended for evaluating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary, and gastrointestinal syndromes are considered. Linear and linear-quadratic models are recommended for estimating the risks of seven types of cancer in adults - leukemia, bone, lung, breast, gastrointestinal, thyroid, and ''other''. For most cancers, both incidence and mortality are addressed. Five classes of genetic diseases -- dominant, x-linked, aneuploidy, unbalanced translocations, and multifactorial diseases are also considered. Data are provided that should enable analysts to consider the timing and severity of each type of health risk

  17. 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....

  18. Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. I. Genetic parameters

    Directory of Open Access Journals (Sweden)

    Legault Christian

    2000-01-01

    Full Text Available Abstract Genetic parameters of body weight at 4 (W4 w, 8 (W8 w and 22 (W22 w weeks of age, days from 20 to 100 kg (DT, average backfat thickness at 100 kg (ABT, teat number (TEAT, number of good teats (GTEAT, total number of piglets born (TNB, born alive (NBA and weaned (NW per litter, and birth to weaning survival rate (SURV were estimated in the Chinese × European Tiameslan composite line using restricted maximum likelihood methodology applied to a multiple trait animal model. Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. Different models were fitted to the data in order to estimate the importance of maternal effects on production traits, as well as genetic correlations between male and female performance. The results showed the existence of significant maternal effects on W4w, W8w and ABT and of variance heterogeneity between sexes for W22w, DT, ABT and GTEAT. Genetic correlations between sexes were 0.79, 0.71 and 0.82, respectively, for W22w, DT and ABT and above 0.90 for the other traits. Heritability estimates were larger than (ABT and TEAT or similar to (other traits average literature values. Some genetic antagonism was evidenced between production traits, particularly W4w, W8w and ABT, and reproductive traits.

  19. 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.

  20. 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

  1. 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

  2. Modification of genetic effect of gamma-irradiation by electric current

    International Nuclear Information System (INIS)

    Grigor'eva, N.N.; Shakhbazov, V.G.

    1983-01-01

    The effect of direct current of different polarity on genetic sequels of #betta#-radiation of Vicia faba seedlings is studied. It is established that weak current might modify genetic sequels of #betta#-radiation. Protective current effect on irradiated meristem cells of seedlings manifests at negative polarization of the meristem before radiation and at positive polarization-after radiation. Modifying effect of electric current is brought about at the expense of redistribution of anions and cations between the meristem and other root zones

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  5. Effects of genetic distance on heterosis in a Drosophila melanogaster model system

    DEFF Research Database (Denmark)

    Jensen, Charlotte; Ørsted, Michael; Kristensen, Torsten Nygaard

    2018-01-01

    Habitat fragmentation and small population sizes can lead to inbreeding and loss of genetic variation, which can potentially cause inbreeding depression and decrease the ability of populations to adapt to altered environmental conditions. One solution to these genetic problems is the implementati...

  6. 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.

  7. 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...

  8. The Effects of Predator Evolution and Genetic Variation on Predator-Prey Population-Level Dynamics.

    Science.gov (United States)

    Cortez, Michael H; Patel, Swati

    2017-07-01

    This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator-prey systems. We do this by analyzing a general eco-evolutionary predator-prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator-prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator-prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.

  9. 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)

  10. STRESS, RELATIONSHIP SATISFACTION, AND HEALTH AMONG AFRICAN AMERICAN WOMEN: GENETIC MODERATION OF EFFECTS

    Science.gov (United States)

    Lei, Man-Kit; Beach, Steven R. H.; Simons, Ronald L.; Barr, Ashley B.; Cutrona, Carolyn E.; Philibert, Robert A.

    2015-01-01

    We examined whether romantic relationship satisfaction would serve as a link between early and later stressors which in turn would influence the Thyroid Function Index (TFI), an indicator of physiological stress response. Using the framework of genetic susceptibility theory combined with hypotheses derived from the vulnerability-stress-adaptation and stress-generation models, we tested whether the hypothesized mediational model would be conditioned by 5-HTTLPR genotype, with greater effects and stronger evidence of mediation among carriers of the “s” allele. In a sample of African American women in romantic relationships (n = 270), we found that 5-HTTLPR moderated each stage of the hypothesized mediational model in a “for better or for worse” manner. That is genetic polymorphisms function to exacerbate not only the detrimental impact of negative environments (i.e. “for worse effects”) but also the beneficial impact of positive environments (i.e. “for better effects”). The effect of early stress on relationship satisfaction was greater among carriers of the “short” allele than among those who did not carry the short allele, and was significantly different in both the “for better” and “for worse” direction. Likewise, the effect of relationship satisfaction on later stressors was moderated in a “for better” or “for worse” manner. Finally, impact on physiological stress, indexed using TFI level, indicated that the impact of later stressors on TFI level was greater in the presence of the short allele, and also followed a “for better” or “for worse” pattern. As expected, the proposed mediational model provided a better fit for “s” allele carriers. PMID:26376424

  11. Genetic determination of mortality rate in Danish dairy cows

    DEFF Research Database (Denmark)

    Maia, Rafael Pimentel; Ask, Birgitte; Madsen, Per

    2014-01-01

    : a sire random component with pedigree representing the sire genetic effects and a herd-year-season component. Moreover, the level of heterozygosity and the sire breed proportions were included in the models as covariates in order to account for potential non-additive genetic effects due to the massive...... introduction of genetic material from other populations. The correlations between the sire components for death rate and slaughter rate were negative and small for the 3 populations, suggesting the existence of specific genetic mechanisms for each culling reason and common concurrent genetic mechanisms...

  12. Effects of censoring on parameter estimates and power in genetic modeling

    NARCIS (Netherlands)

    Derks, Eske M.; Dolan, Conor V.; Boomsma, Dorret I.

    2004-01-01

    Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We

  13. Effects of censoring on parameter estimates and power in genetic modeling.

    NARCIS (Netherlands)

    Derks, E.M.; Dolan, C.V.; Boomsma, D.I.

    2004-01-01

    Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We

  14. Landscape characteristics influencing the genetic structure of greater sage-grouse within the stronghold of their range: a holistic modeling approach

    Science.gov (United States)

    Row, Jeff R; Oyler-McCance, Sara J.; Fike, Jennifer; O'Donnell, Michael; Doherty, Kevin E.; Aldridge, Cameron L.; Bowen, Zachary H.; Fedy, Brad C.

    2015-01-01

    Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape

  15. 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

  16. 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

  17. 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

  18. A maternal-effect genetic incompatibility in Caenorhabditis elegans

    OpenAIRE

    Burga, Alejandro; Ben-David, Eyal; Kruglyak, Leonid

    2017-01-01

    Selfish genetic elements spread in natural populations and have an important role in genome evolution. We discovered a selfish element causing a genetic incompatibility between strains of the nematode Caenorhabditis elegans . The element is made up of sup-35 , a maternal-effect toxin that kills developing embryos, and pha-1 , its zygotically expressed antidote. pha-1 has long been considered essential for pharynx development based on its mutant phenotype, but this phenotype in fact arises fro...

  19. Variance components and genetic parameters for body weight and ...

    African Journals Online (AJOL)

    model included a direct as well as a maternal additive genetic effect, while only the direct additive genetic eff'ect had a sig- .... deviations from the log likelihood value obtained under the ... (1995).lt would therefore be fair to assume that a.

  20. How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

    Science.gov (United States)

    Yashin, Anatoliy I.; Arbeev, Konstantin G.; Wu, Deqing; Arbeeva, Liubov; Kulminski, Alexander; Kulminskaya, Irina; Akushevich, Igor; Ukraintseva, Svetlana V.

    2016-01-01

    Background and Objective To clarify mechanisms of genetic regulation of human aging and longevity traits, a number of genome-wide association studies (GWAS) of these traits have been performed. However, the results of these analyses did not meet expectations of the researchers. Most detected genetic associations have not reached a genome-wide level of statistical significance, and suffered from the lack of replication in the studies of independent populations. The reasons for slow progress in this research area include low efficiency of statistical methods used in data analyses, genetic heterogeneity of aging and longevity related traits, possibility of pleiotropic (e.g., age dependent) effects of genetic variants on such traits, underestimation of the effects of (i) mortality selection in genetically heterogeneous cohorts, (ii) external factors and differences in genetic backgrounds of individuals in the populations under study, the weakness of conceptual biological framework that does not fully account for above mentioned factors. One more limitation of conducted studies is that they did not fully realize the potential of longitudinal data that allow for evaluating how genetic influences on life span are mediated by physiological variables and other biomarkers during the life course. The objective of this paper is to address these issues. Data and Methods We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control (QC) procedures and used one subset of selected genetic variants for further analyses. We used simulation study to show that approach to combining data improves the quality of GWAS. We used FHS longitudinal data to compare average age trajectories of physiological variables in carriers and non-carriers of selected genetic variants. We used stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging

  1. Genetic determinants of cardiometabolic risk: a proposed model for phenotype association and interaction.

    Science.gov (United States)

    Blackett, Piers R; Sanghera, Dharambir K

    2013-01-01

    This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes, and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus, it follows that the genetics of dyslipidemia, obesity, and nonalcoholic fatty liver disease are central in triggering progression of the syndrome to overt expression of disease traits and have become a key focus of interest for early detection and for designing prevention and treatments. To support the "birds' eye view" approach, we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacologic targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. Copyright © 2013 National Lipid Association. Published by Elsevier Inc. All rights reserved.

  2. Interactions between Genetic and Ecological Effects on the Evolution of Life Cycles.

    Science.gov (United States)

    Rescan, Marie; Lenormand, Thomas; Roze, Denis

    2016-01-01

    Sexual reproduction leads to an alternation between haploid and diploid phases, whose relative length varies widely across taxa. Previous genetical models showed that diploid or haploid life cycles may be favored, depending on dominance interactions and on effective recombination rates. By contrast, niche differentiation between haploids and diploids may favor biphasic life cycles, in which development occurs in both phases. In this article, we explore the interplay between genetical and ecological factors, assuming that deleterious mutations affect the competitivity of individuals within their ecological niche and allowing different effects of mutations in haploids and diploids (including antagonistic selection). We show that selection on a modifier gene affecting the relative length of both phases can be decomposed into a direct selection term favoring the phase with the highest mean fitness (due to either ecological differences or differential effects of mutations) and an indirect selection term favoring the phase in which selection is more efficient. When deleterious alleles occur at many loci and in the presence of ecological differentiation between haploids and diploids, evolutionary branching often occurs and leads to the stable coexistence of alleles coding for haploid and diploid cycles, while temporal variations in niche sizes may stabilize biphasic cycles.

  3. Technical note: Equivalent genomic models with a residual polygenic effect.

    Science.gov (United States)

    Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R

    2016-03-01

    Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  4. 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.

  5. 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...

  6. 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)

  7. Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics

    Science.gov (United States)

    Beaumont, Robin N; Warrington, Nicole M; Cavadino, Alana; Tyrrell, Jessica; Nodzenski, Michael; Horikoshi, Momoko; Geller, Frank; Myhre, Ronny; Richmond, Rebecca C; Paternoster, Lavinia; Bradfield, Jonathan P; Kreiner-Møller, Eskil; Huikari, Ville; Metrustry, Sarah; Lunetta, Kathryn L; Painter, Jodie N; Hottenga, Jouke-Jan; Allard, Catherine; Barton, Sheila J; Espinosa, Ana; Marsh, Julie A; Potter, Catherine; Zhang, Ge; Ang, Wei; Berry, Diane J; Bouchard, Luigi; Das, Shikta; Hakonarson, Hakon; Heikkinen, Jani; Helgeland, Øyvind; Hocher, Berthold; Hofman, Albert; Inskip, Hazel M; Jones, Samuel E; Kogevinas, Manolis; Lind, Penelope A; Marullo, Letizia; Medland, Sarah E; Murray, Anna; Murray, Jeffrey C; Njølstad, Pål R; Nohr, Ellen A; Reichetzeder, Christoph; Ring, Susan M; Ruth, Katherine S; Santa-Marina, Loreto; Scholtens, Denise M; Sebert, Sylvain; Sengpiel, Verena; Tuke, Marcus A; Vaudel, Marc; Weedon, Michael N; Willemsen, Gonneke; Wood, Andrew R; Yaghootkar, Hanieh; Muglia, Louis J; Bartels, Meike; Relton, Caroline L; Pennell, Craig E; Chatzi, Leda; Estivill, Xavier; Holloway, John W; Boomsma, Dorret I; Montgomery, Grant W; Murabito, Joanne M; Spector, Tim D; Power, Christine; Järvelin, Marjo-Ritta; Bisgaard, Hans; Grant, Struan F A; Sørensen, Thorkild I A; Jaddoe, Vincent W; Jacobsson, Bo; Melbye, Mads; McCarthy, Mark I; Hattersley, Andrew T; Hayes, M Geoffrey; Frayling, Timothy M; Hivert, Marie-France; Felix, Janine F; Hyppönen, Elina; Lowe, William L; Evans, David M; Lawlor, Debbie A; Feenstra, Bjarke

    2018-01-01

    Abstract Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights. PMID:29309628

  8. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  9. Genetic effects of the atomic bombs: a reappraisal

    International Nuclear Information System (INIS)

    Schull, W.J.; Otake, M.; Neel, J.V.

    1981-01-01

    Data are presented on four indicators of genetic effects from studies of children born to survivors of the atomic bombings of Hiroshima and Nagasaki. The indicators are frequency of untoward pregnancy outcomes (stillbirth, major congenital defect, death during the first postnatal weak); occurrence of death in live-born children, through an average of life expectancy of 17 years; frequency of children with sex chromosome aneuploidy; and frequency of children with mutation resulting in an eletrophoretic variant. In no instance is there a statistically significant effect of parental exposure; but for all indicators the observed effect is in the direction suggested by the hypothesis that genetic damage resulted from the exposure. On the basis of assumptions concerning the contribution that spontaneous mutation in the preceding generation makes to the indicators in question, it is possible to estimate the genetic doubling dose for radiation for the first three indicators (the data base is still too small for the fourth). The average of these estimates is 156 rems. This is some four times higher than the results from experimental studies on the mouse with comparable radiation sources, which have been the principal guide to the presumed human sensitivities. The relevance of these data in setting permissible limits for human exposures is discussed briefly

  10. Genetic effects of the atomic bombs: a reappraisal

    International Nuclear Information System (INIS)

    Schull, W.J.; Otake, M.; Neel, J.V.

    1981-01-01

    Data are presented on four indicators of genetic effects from studies of children born to survivors of the atomic bombings of Hiroshima and Negasaki. The indicators are frequency of un toward pregnancy outcomes (stillbirth, major congenital defect, death during first postnatal week); occurrence of death in live-born children, through an average life expectancy of 17 years; frequency of children with sex chromosome aneuploidy; and frequency of children with mutation resulting in an electrophoretic variant. In no instance is there a statistically significant effect of parental exposure; but for all indicators the observed effect is in the direction suggested by the hypothesis that genetic damage resulted from the exposure. On the basis of assumptions concerning the contribution that spontaneous mutation in the preceding generation makes to the indicators in question, it is possible to estimate the genetic doubling dose for radiation for the first three indicators (the data base is still too small for the fourth). The average of these estimates is 156 rems. This is some four times higher than the results from experimental studies on the mouse with comparable radiation sources, which have been the principal guide to the presumed human sensitivities. The relevance of these data in setting permissible limits for human exposures is discussed briefly

  11. 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

  12. Genetic Determinants of Cardio-Metabolic Risk: A Proposed Model for Phenotype Association and Interaction

    Science.gov (United States)

    Blackett, Piers R; Sanghera, Dharambir K

    2012-01-01

    This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus it follows that the genetics of dyslipidemia, obesity, and non-alcoholic fatty liver (NAFLD) disease are central in triggering progression of the syndrome to overt expression of disease traits, and have become a key focus of interest for early detection and for designing prevention and treatments. To support the “birds’ eye view” approach we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacological targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. PMID:23351585

  13. Structural equation modeling in the genetically informative study of the covariation of intelligence, working memory and planning

    Directory of Open Access Journals (Sweden)

    Voronin I.

    2016-01-01

    Full Text Available Structural equation modelling (SEM has become an important tool in behaviour genetic research. The application of SEM for multivariate twin analysis allows revealing the structure of genetic and environmental factors underlying individual differences in human traits. We outline the framework of twin method and SEM, describe SEM implementation of a multivariate twin model and provide an example of a multivariate twin study. The study included 901 adolescent twin pairs from Russia. We measured general cognitive ability and characteristics of working memory and planning. The individual differences in working memory and planning were explained mostly by person-specific environment. The variability of intelligence is related to genes, family environment, and person specific environment. Moderate and weak associations between intelligence, working memory, and planning were entirely explained by shared environmental effects.

  14. Genetic and environmental effects on mortality before age 70 years

    DEFF Research Database (Denmark)

    Petersen, L.; Andersen, Per Kragh; Sørensen, Thorkild I.A.

    2008-01-01

    There is a familial influence on risk of many diseases and on mortality in general, which, according to studies of twins, is due to a combination of genetic and environmental effects. Adoption studies, which rest on different assumptions, may also be used to estimate separately the genetic...

  15. 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

  16. 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

  17. Identification of Treatment Targets in a Genetic Mouse Model of Voluntary Methamphetamine Drinking.

    Science.gov (United States)

    Phillips, T J; Mootz, J R K; Reed, C

    2016-01-01

    Methamphetamine has powerful stimulant and euphoric effects that are experienced as rewarding and encourage use. Methamphetamine addiction is associated with debilitating illnesses, destroyed relationships, child neglect, violence, and crime; but after many years of research, broadly effective medications have not been identified. Individual differences that may impact not only risk for developing a methamphetamine use disorder but also affect treatment response have not been fully considered. Human studies have identified candidate genes that may be relevant, but lack of control over drug history, the common use or coabuse of multiple addictive drugs, and restrictions on the types of data that can be collected in humans are barriers to progress. To overcome some of these issues, a genetic animal model comprised of lines of mice selectively bred for high and low voluntary methamphetamine intake was developed to identify risk and protective alleles for methamphetamine consumption, and identify therapeutic targets. The mu opioid receptor gene was supported as a target for genes within a top-ranked transcription factor network associated with level of methamphetamine intake. In addition, mice that consume high levels of methamphetamine were found to possess a nonfunctional form of the trace amine-associated receptor 1 (TAAR1). The Taar1 gene is within a mouse chromosome 10 quantitative trait locus for methamphetamine consumption, and TAAR1 function determines sensitivity to aversive effects of methamphetamine that may curb intake. The genes, gene interaction partners, and protein products identified in this genetic mouse model represent treatment target candidates for methamphetamine addiction. © 2016 Elsevier Inc. All rights reserved.

  18. Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: Phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus)

    Science.gov (United States)

    Vandergast, A.G.; Bohonak, A.J.; Weissman, D.B.; Fisher, R.N.

    2007-01-01

    Habitat loss and fragmentation due to urbanization are the most pervasive threats to biodiversity in southern California. Loss of habitat and fragmentation can lower migration rates and genetic connectivity among remaining populations of native species, reducing genetic variability and increasing extinction risk. However, it may be difficult to separate the effects of recent anthropogenic fragmentation from the genetic signature of prehistoric fragmentation due to previous natural geological and climatic changes. To address these challenges, we examined the phylogenetic and population genetic structure of a flightless insect endemic to cismontane southern California, Stenopelmatus 'mahogani' (Orthoptera: Stenopelmatidae). Analyses of mitochondrial DNA sequence data suggest that diversification across southern California began during the Pleistocene, with most haplotypes currently restricted to a single population. Patterns of genetic divergence correlate with contemporary urbanization, even after correcting for (geographical information system) GIS-based reconstructions of fragmentation during the Pleistocene. Theoretical simulations confirm that contemporary patterns of genetic structure could be produced by recent urban fragmentation using biologically reasonable assumptions about model parameters. Diversity within populations was positively correlated with current fragment size, but not prehistoric fragment size, suggesting that the effects of increased drift following anthropogenic fragmentation are already being seen. Loss of genetic connectivity and diversity can hinder a population's ability to adapt to ecological perturbations commonly associated with urbanization, such as habitat degradation, climatic changes and introduced species. Consequently, our results underscore the importance of preserving and restoring landscape connectivity for long-term persistence of low vagility native species. Journal compilation ?? 2006 Blackwell Publishing Ltd.

  19. The genetics of indirect ecological effects - plant parasites and aphid herbivores

    Directory of Open Access Journals (Sweden)

    Jennifer K Rowntree

    2014-04-01

    Full Text Available When parasitic plants and aphid herbivores share a host, both direct and indirect ecological effects (IEEs can influence evolutionary processes. We used a hemiparasitic plant (Rhinanthus minor, a grass host (Hordeum vulgare and a cereal aphid (Sitobion avenae to investigate the genetics of IEEs between the aphid and the parasitic plant, and looked to see how these might affect or be influenced by the genetic diversity of the host plants. Survival of R. minor depended on the parasite’s population of origin, the genotypes of the aphids sharing the host and the genetic diversity in the host plant community. Hence the indirect effects of the aphids on the parasitic plants depended on the genetic environment of the system. Here, we show that genetic variation can be important in determining the outcome of IEEs. Therefore, IEEs have the potential to influence evolutionary processes and the continuity of species interactions over time.

  20. Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

    Science.gov (United States)

    Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

    2011-01-01

    Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

  1. 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.

  2. Prediction of China's coal production-environmental pollution based on a hybrid genetic algorithm-system dynamics model

    International Nuclear Information System (INIS)

    Yu Shiwei; Wei Yiming

    2012-01-01

    This paper proposes a hybrid model based on genetic algorithm (GA) and system dynamics (SD) for coal production–environmental pollution load in China. GA has been utilized in the optimization of the parameters of the SD model to reduce implementation subjectivity. The chain of “Economic development–coal demand–coal production–environmental pollution load” of China in 2030 was predicted, and scenarios were analyzed. Results show that: (1) GA performs well in optimizing the parameters of the SD model objectively and in simulating the historical data; (2) The demand for coal energy continuously increases, although the coal intensity has actually decreased because of China's persistent economic development. Furthermore, instead of reaching a turning point by 2030, the environmental pollution load continuously increases each year even under the scenario where coal intensity decreased by 20% and investment in pollution abatement increased by 20%; (3) For abating the amount of “three types of wastes”, reducing the coal intensity is more effective than reducing the polluted production per tonne of coal and increasing investment in pollution control. - Highlights: ► We propos a GA-SD model for China's coal production-pollution prediction. ► Genetic algorithm (GA) can objectively and accurately optimize parameters of system dynamics (SD) model. ► Environmental pollution in China is projected to grow in our scenarios by 2030. ► The mechanism of reducing waste production per tonne of coal mining is more effective than others.

  3. A genetic algorithm solution for a nuclear power plant risk-cost maintenance model

    International Nuclear Information System (INIS)

    Tong Jiejuan; Mao Dingyuan; Xue Dazhi

    2004-01-01

    Reliability Centered Maintenance (RCM) is one of the popular maintenance optimization methods according to certain kinds of priorities. Traditional RCM usually analyzes and optimizes the maintenance strategy from the viewpoint of component instead of the whole maintenance program impact. Research presented in this paper is a pilot study using PSA techniques in RCM. How to reflect the effect on component unavailability by the maintenance activities such as surveillance testing and preventive maintenance in PSA model is discussed firstly. Based on the discussion, a maintenance risk-cost model is established for global maintenance optimization in a nuclear power plant, and a genetic algorithm (GA) is applied to solve such a model to get the global optimized maintenance strategy. Finally, the result got from a simple test case based on a risk-cost model consisting of 10 components is presented

  4. Within a smoking-cessation program, what impact does genetic information on lung cancer need to have to demonstrate cost-effectiveness?

    Directory of Open Access Journals (Sweden)

    Gordon Louisa G

    2010-09-01

    Full Text Available Abstract Background Many smoking-cessation programs and pharmaceutical aids demonstrate substantial health gains for a relatively low allocation of resources. Genetic information represents a type of individualized or personal feedback regarding the risk of developing lung cancer, and hence the potential benefits from stopping smoking, may motivate the person to remain smoke-free. The purpose of this study was to explore what the impact of a genetic test needs to have within a typical smoking-cessation program aimed at heavy smokers in order to be cost-effective. Methods Two strategies were modelled for a hypothetical cohort of heavy smokers aged 50 years; individuals either received or did not receive a genetic test within the course of a usual smoking-cessation intervention comprising nicotine replacement therapy (NRT and counselling. A Markov model was constructed using evidence from published randomized controlled trials and meta-analyses for estimates on 12-month quit rates and long-term relapse rates. Epidemiological data were used for estimates on lung cancer risk stratified by time since quitting and smoking patterns. Extensive sensitivity analyses were used to explore parameter uncertainty. Results The discounted incremental cost per QALY was AU$34,687 (95% CI $12,483, $87,734 over 35 years. At a willingness-to-pay of AU$20,000 per QALY gained, the genetic testing strategy needs to produce a 12-month quit rate of at least 12.4% or a relapse rate 12% lower than NRT and counselling alone for it to be equally cost-effective. The likelihood that adding a genetic test to the usual smoking-cessation intervention is cost-effective was 20.6% however cost-effectiveness ratios were favourable in certain situations (e.g., applied to men only, a 60 year old cohort. Conclusions The findings were sensitive to small changes in critical variables such as the 12-month quit rates and relapse rates. As such, the cost-effectiveness of the genetic testing

  5. 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…

  6. Childhood socioeconomic status amplifies genetic effects on adult intelligence.

    Science.gov (United States)

    Bates, Timothy C; Lewis, Gary J; Weiss, Alexander

    2013-10-01

    Studies of intelligence in children reveal significantly higher heritability among groups with high socioeconomic status (SES) than among groups with low SES. These interaction effects, however, have not been examined in adults, when between-families environmental effects are reduced. Using 1,702 adult twins (aged 24-84) for whom intelligence assessment data were available, we tested for interactions between childhood SES and genetic effects, between-families environmental effects, and unique environmental effects. Higher SES was associated with higher mean intelligence scores. Moreover, the magnitude of genetic influences on intelligence was proportional to SES. By contrast, environmental influences were constant. These results suggest that rather than setting lower and upper bounds on intelligence, genes multiply environmental inputs that support intellectual growth. This mechanism implies that increasing SES may raise average intelligence but also magnifies individual differences in intelligence.

  7. Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

    Directory of Open Access Journals (Sweden)

    Mahmood A. Rashid

    2013-01-01

    Full Text Available Protein structure prediction (PSP is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20×20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

  8. 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.

  9. GRAVITATIONAL LENS MODELING WITH GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZERS

    International Nuclear Information System (INIS)

    Rogers, Adam; Fiege, Jason D.

    2011-01-01

    Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point-spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least-squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automatically, which represents the trade-off between the image χ 2 and regularization effects, and allows an estimate of the optimally regularized solution for each lens parameter set. In the final step of the optimization procedure, the lens model with the lowest χ 2 is used while the global optimizer solves for the source intensity distribution directly. This allows us to accurately determine the number of degrees of freedom in the problem to facilitate comparison between lens models and enforce positivity on the source profile. In practice, we find that the GA conducts a more thorough search of the parameter space than the PSO.

  10. 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.

  11. 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.

  12. Population genetics without intraspecific data

    DEFF Research Database (Denmark)

    Thorne, Jeffrey L; Choi, Sang Chul; Yu, Jiaye

    2007-01-01

    A central goal of computational biology is the prediction of phenotype from DNA and protein sequence data. Recent models of sequence change use in silico prediction systems to incorporate the effects of phenotype on evolutionary rates. These models have been designed for analyzing sequence data...... populations, and parameters of interspecific models should have population genetic interpretations. We show, with two examples, how population genetic interpretations can be assigned to evolutionary models. The first example considers the impact of RNA secondary structure on sequence change, and the second...... reflects the tendency for protein tertiary structure to influence nonsynonymous substitution rates. We argue that statistical fit to data should not be the sole criterion for assessing models of sequence change. A good interspecific model should also yield a clear and biologically plausible population...

  13. Causal models in epidemiology: past inheritance and genetic future

    Directory of Open Access Journals (Sweden)

    Kriebel David

    2006-07-01

    Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional

  14. Genetic Analysis of Milk Yield Using Random Regression Test Day Model in Tehran Province Holstein Dairy Cow

    Directory of Open Access Journals (Sweden)

    A. Seyeddokht

    2012-09-01

    Full Text Available In this research a random regression test day model was used to estimate heritability values and calculation genetic correlations between test day milk records. a total of 140357 monthly test day milk records belonging to 28292 first lactation Holstein cattle(trice time a day milking distributed in 165 herd and calved from 2001 to 2010 belonging to the herds of Tehran province were used. The fixed effects of herd-year-month of calving as contemporary group and age at calving and Holstein gene percentage as covariate were fitted. Orthogonal legendre polynomial with a 4th-order was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. RRM using Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data. The results showed that the average of heritability for the second half of lactation period was higher than that of the first half. The heritability value for the first month was lowest (0.117 and for the eighth month of the lactation was highest (0.230 compared to the other months of lactation. Because of genetic variation was increased gradually, and residual variance was high in the first months of lactation, heritabilities were different over the course of lactation. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. In this research estimation of genetic parameters, and calculation genetic correlations were implemented by random regression test day model, therefore using this method is the exact way to take account of parameters rather than the other ways.

  15. A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

    Directory of Open Access Journals (Sweden)

    Alireza TaheriMoghadam

    2014-05-01

    Full Text Available In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

  16. Genetic and environmental effects on performance traits of ...

    African Journals Online (AJOL)

    Genetic and environmental effects on performance traits of Simmentaler cattle on the Transvaal Highveld. Tina Rust*. Highveld Region Agricultural Development Institute, .... ef'fect of the mtt' management system (m = 1,2,3,4),. bW = linear regression of the appropriate deviation from the mean of individual age at weaning (in ...

  17. Genetic Aspects of Autism Spectrum Disorders: Insights from Animal Models

    Directory of Open Access Journals (Sweden)

    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.

  18. Genetics and ionizing radiations. 2. The genetic effects of ionizing radiations

    International Nuclear Information System (INIS)

    Dutrillaux, B.

    1980-01-01

    Ionizing radiations are the best known mutagenic agents. Their relative importance as compared to other mutagens cannot be determined. Experiments show that male germinal cells are more sensitive than female germinal cells. This sensitivity is determined by the cell phase at the time of agression. Acute X-exposure results in a mutation rate of about 1.7x10 -7 rad -1 per gamete and per gene in the male. This rate is lower in case of chronic exposure. Pathological effects will appear in the first (dominant genes, and unbalanced chromosomal anomalies) or n-th generation (recessive genes and balanced chromosomal rearrangements). Direct studies on humans have brought contradictory results. Only X or γ-emitters induce a true genetic risk, the other radiations being too little penetrating to reach the gonads. The doubling dose of the mutation rate is estimated at over 100 rad in males and over 1,000 rad in females. However, one cannot conclude that low doses are not harmless because their effects are difficult to demonstrate. The individual risk, that remains low, must be distinguished from the collective risk for which the safeguard of the quality of the genetic material of our species must remain our prime purpose [fr

  19. Cost-Effectiveness Analysis of Different Genetic Testing Strategies for Lynch Syndrome in Taiwan.

    Directory of Open Access Journals (Sweden)

    Ying-Erh Chen

    Full Text Available Patients with Lynch syndrome (LS have a significantly increased risk of developing colorectal cancer (CRC and other cancers. Genetic screening for LS among patients with newly diagnosed CRC aims to identify mutations in the disease-causing genes (i.e., the DNA mismatch repair genes in the patients, to offer genetic testing for relatives of the patients with the mutations, and then to provide early prevention for the relatives with the mutations. Several genetic tests are available for LS, such as DNA sequencing for MMR genes and tumor testing using microsatellite instability and immunohistochemical analyses. Cost-effectiveness analyses of different genetic testing strategies for LS have been performed in several studies from different countries such as the US and Germany. However, a cost-effectiveness analysis for the testing has not yet been performed in Taiwan. In this study, we evaluated the cost-effectiveness of four genetic testing strategies for LS described in previous studies, while population-specific parameters, such as the mutation rates of the DNA mismatch repair genes and treatment costs for CRC in Taiwan, were used. The incremental cost-effectiveness ratios based on discounted life years gained due to genetic screening were calculated for the strategies relative to no screening and to the previous strategy. Using the World Health Organization standard, which was defined based on Taiwan's Gross Domestic Product per capita, the strategy based on immunohistochemistry as a genetic test followed by BRAF mutation testing was considered to be highly cost-effective relative to no screening. Our probabilistic sensitivity analysis results also suggest that the strategy has a probability of 0.939 of being cost-effective relative to no screening based on the commonly used threshold of $50,000 to determine cost-effectiveness. To the best of our knowledge, this is the first cost-effectiveness analysis for evaluating different genetic testing

  20. Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening.

    Science.gov (United States)

    Quarterman, Josh; Kim, Soo Rin; Kim, Pan-Jun; Jin, Yong-Su

    2015-01-20

    In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

    Science.gov (United States)

    Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

    2017-11-04

    This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

  2. Genetic evaluations for growth heat tolerance in Angus cattle.

    Science.gov (United States)

    Bradford, H L; Fragomeni, B O; Bertrand, J K; Lourenco, D A L; Misztal, I

    2016-10-01

    The objectives were to assess the impact of heat stress and to develop a model for genetic evaluation of growth heat tolerance in Angus cattle. The American Angus Association provided weaning weight (WW) and yearling weight (YW) data, and records from the Upper South region were used because of the hot climatic conditions. Heat stress was characterized by a weaning (yearling) heat load function defined as the mean temperature-humidity index (THI) units greater than 75 (70) for 30 (150) d prior to the weigh date. Therefore, a weaning (yearling) heat load of 5 units corresponded to 80 (75) for the corresponding period prior to the weigh date. For all analyses, 82,669 WW and 69,040 YW were used with 3 ancestral generations in the pedigree. Univariate models were a proxy for the Angus growth evaluation, and reaction norms using 2 B-splines for heat load were fit separately for weaning and yearling heat loads. For both models, random effects included direct genetic, maternal genetic, maternal permanent environment (WW only), and residual. Fixed effects included a linear age covariate, age-of-dam class (WW only), and contemporary group for both models and fixed regressions on the B-splines in the reaction norm. Direct genetic correlations for WW were strong for modest heat load differences but decreased to less than 0.50 for large differences. Reranking of proven sires occurred for only WW direct effects for the reaction norms with extreme heat load differences. Conversely, YW results indicated little effect of heat stress on genetic merit. Therefore, weaning heat tolerance was a better candidate for developing selection tools. Maternal heritabilities were consistent across heat loads, and maternal genetic correlations were greater than 0.90 for nearly all heat load combinations. No evidence existed for a genotype × environment interaction for the maternal component of growth. Overall, some evidence exists for phenotypic plasticity for the direct genetic effects of WW

  3. Enhanced computational methods for quantifying the effect of geographic and environmental isolation on genetic differentiation

    DEFF Research Database (Denmark)

    Botta, Filippo; Eriksen, Casper; Fontaine, Michaël C.

    2015-01-01

    1. In a recent paper, Bradburd et al. (Evolution, 67, 2013, 3258) proposed a model to quantify the relative effect of geographic and environmental distance on genetic differentiation. Here, we enhance this method in several ways. 2. We modify the covariance model so as to fit better with mainstre...... available as an R package called sunder. It takes as input georeferenced allele counts at the individual or population level for co-dominant markers. Program homepage: http://www2.imm.dtu.dk/~gigu/Sunder/....

  4. Strategies for MCMC computation inquantitative genetics

    DEFF Research Database (Denmark)

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

    another extension of the linear mixed model introducing genetic random effects influencing the log residual variances of the observations thereby producing a genetically structured variance heterogeneity. Considerable computational problems arise when abandoning the standard linear mixed model. Maximum...... the various algorithms in the context of the heterogeneous variance model. Apart from being a model of great interest in its own right, this model has proven to be a hard test for MCMC methods. We compare the performances of the different algorithms when applied to three real datasets which differ markedly...... results of applying two MCMC schemes to data sets with pig litter sizes, rabbit litter sizes, and snail weights. Some concluding remarks are given in Section 5....

  5. Genetic Engineering and Human Mental Ecology: Interlocking Effects and Educational Considerations

    OpenAIRE

    Affifi, Ramsey

    2017-01-01

    This paper describes some likely semiotic consequences of genetic engineering on what Gregory Bateson has called ?the mental ecology? (1979) of future humans, consequences that are less often raised in discussions surrounding the safety of GMOs (genetically modified organisms). The effects are as follows: an increased 1) habituation to the presence of GMOs in the environment, 2) normalization of empirically false assumptions grounding genetic reductionism, 3) acceptance that humans are capabl...

  6. 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...

  7. 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.

  8. Use of PRIM code to analyze potential radiation-induced genetic and somatic effects to man from Jackpile-Paguate mines

    International Nuclear Information System (INIS)

    Momeni, M.H.

    1983-01-01

    Potential radiation-induced effects from inhalation and ingestion of land external exposure to radioactive materials at the Jackpile-Paguate uranium mine complex near Paguate, New Mexico, were analyzed. The Uranium Dispersion and Dosimetry (UDAD) computer code developed at Argonne National Laboratory was used to calculate the dose rates and the time-integrated doses to tissues at risk as a function of age and time for the population within 80 km of the mines. The ANL computer code Potential Radiation-Induced Biological Effects on Man (PRIM) then was used to calculate the potential radiation-induced somatic and genetic effects among the same population on the basis of absolute and relative risk models as a function of duration of exposure and age at time of exposure. The analyses were based on the recommendations in BEIR II and WASH-1400 and the lifetable method. The death rates were calculated for radiation exposure from the mines and for naturally induced effects for 19 age cohorts, 20 time intervals, and for each sex. The results indicated that under present conditions of the radiation environment at the mines, the number of potential fatal radiation-induced neoplasms that could occur among the regional population over the next 85 years would be 95 using the absolute risk model, and 243 using the relative risk model. Over the same period, there would be less than two radiation-induced genetic effects (dominant and multifactorials). After decommissioning f the mine site, these risks would decrease to less than 1 and less than 3 potential radiation-induced deaths under the relative and absolute risk models, respectively, and 0.001 genetic disorders. Because of various sources of error, the uncertainty in these predicted risks could be a factor of five

  9. Advanced technologies for genetically manipulating the silkworm Bombyx mori, a model Lepidopteran insect

    Science.gov (United States)

    Xu, Hanfu; O'Brochta, David A.

    2015-01-01

    Genetic technologies based on transposon-mediated transgenesis along with several recently developed genome-editing technologies have become the preferred methods of choice for genetically manipulating many organisms. The silkworm, Bombyx mori, is a Lepidopteran insect of great economic importance because of its use in silk production and because it is a valuable model insect that has greatly enhanced our understanding of the biology of insects, including many agricultural pests. In the past 10 years, great advances have been achieved in the development of genetic technologies in B. mori, including transposon-based technologies that rely on piggyBac-mediated transgenesis and genome-editing technologies that rely on protein- or RNA-guided modification of chromosomes. The successful development and application of these technologies has not only facilitated a better understanding of B. mori and its use as a silk production system, but also provided valuable experiences that have contributed to the development of similar technologies in non-model insects. This review summarizes the technologies currently available for use in B. mori, their application to the study of gene function and their use in genetically modifying B. mori for biotechnology applications. The challenges, solutions and future prospects associated with the development and application of genetic technologies in B. mori are also discussed. PMID:26108630

  10. Genetic and environmental influences on last-year major depression in adulthood: a highly heritable stable liability but strong environmental effects on 1-year prevalence.

    Science.gov (United States)

    Kendler, K S; Gardner, C O

    2017-07-01

    This study seeks to clarify the contribution of temporally stable and occasion-specific genetic and environmental influences on risk for major depression (MD). Our sample was 2153 members of female-female twin pairs from the Virginia Twin Registry. We examined four personal interview waves conducted over an 8-year period with MD in the last year defined by DSM-IV criteria. We fitted a structural equation model to the data using classic Mx. The model included genetic and environmental risk factors for a latent, stable vulnerability to MD and for episodes in each of the four waves. The best-fit model was simple and included genetic and unique environmental influences on the latent liability to MD and unique wave-specific environmental effects. The path from latent liability to MD in the last year was constant over time, moderate in magnitude (+0.65) and weaker than the impact of occasion-specific environmental effects (+0.76). Heritability of the latent stable liability to MD was much higher (78%) than that estimated for last-year MD (32%). Of the total unique environmental influences on MD, 13% reflected enduring consequences of earlier environmental insults, 17% diagnostic error and 70% wave-specific short-lived environmental stressors. Both genetic influences on MD and MD heritability are stable over middle adulthood. However, the largest influence on last-year MD is short-lived environmental effects. As predicted by genetic theory, the heritability of MD is increased substantially by measurement at multiple time points largely through the reduction of the effects of measurement error and short-term environmental risk factors.

  11. Erosion of Brassica incana Genetic Resources: Causes and Effects

    Science.gov (United States)

    Muscolo, A.; Settineri, G.; Mallamaci, C.; Papalia, T.; Sidari, M.

    2017-07-01

    Brassica incana Ten., possessing a number of useful agronomic traits, represents a precious genetic resource to be used in plant breeding programs to broaden the genetic base in most Brassica crop species. B. incana that grows on limestone cliffs is at risk of genetic erosion for environmental constraints and human activities. We studied the pedological conditions of a Calabrian site where the B. incana grows, and we correlated the soil properties to the physiological and biochemical aspects of B. incana to identify the causes and effects of the genetic erosion of this species. Our results evidenced that physical soil conditions did not affect B. incana growth and nutraceutical properties; conversely, biological soil properties modified its properties. We identified leaf pigments and secondary metabolites that can be used routinely as early warning indicators of plant threat, to evaluate in a short term the dynamic behavior of plants leading to species extinction.

  12. Genetic effects of low-dose irradiation in Drosophila Melanogaster

    International Nuclear Information System (INIS)

    Zajnulin, V.G.; Shaposhnikov, M.V.; Yuraneva, I.N.

    2000-01-01

    Influence of chronic γ-irradiation at the dose rate of 0.17 cGy/h on the rate of genetic variability in the laboratory strains of Drosophila Melanogaster with genotypic distinguishes by families of mobile genetic elements and of systems of hybrid disgenesis and also violations in reparation processes control mechanisms. It was shown that the rates of induction of recessive lethal mutations depended on genotype of investigated strains. In the different strains an increase as well as a decrease of the mutation rate were observed. Also in was established that irradiation leads to the increase in frequencies of the gonads sterility and mutability of the sn w and h(w + ) in the P-M and H-E dysgenic crosses. Obtained results suggest that mobile genetic elements play an important role in the forming of genetic effects in response to low dose irradiation [ru

  13. Adults' perceptions of genetic counseling and genetic testing.

    Science.gov (United States)

    Houfek, Julia Fisco; Soltis-Vaughan, Brigette S; Atwood, Jan R; Reiser, Gwendolyn M; Schaefer, G Bradley

    2015-02-01

    This study described the perceptions of genetic counseling and testing of adults (N = 116) attending a genetic education program. Understanding perceptions of genetic counseling, including the importance of counseling topics, will contribute to patient-focused care as clinical genetic applications for common, complex disorders evolve. Participants completed a survey addressing: the importance of genetic counseling topics, benefits and negative effects of genetic testing, and sharing test results. Topics addressing practical information about genetic conditions were rated most important; topics involving conceptual genetic/genomic principles were rated least important. The most frequently identified benefit and negative effect of testing were prevention/early detection/treatment and psychological distress. Participants perceived that they were more likely to share test results with first-degree than other relatives. Findings suggest providing patients with practical information about genetic testing and genetic contributions to disease, while also determining whether their self-care abilities would be enhanced by teaching genetic/genomic principles. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. A model to estimate effects of SNPs on host susceptibility and infectivity for an endemic infectious disease.

    Science.gov (United States)

    Biemans, Floor; de Jong, Mart C M; Bijma, Piter

    2017-06-30

    Infectious diseases in farm animals affect animal health, decrease animal welfare and can affect human health. Selection and breeding of host individuals with desirable traits regarding infectious diseases can help to fight disease transmission, which is affected by two types of (genetic) traits: host susceptibility and host infectivity. Quantitative genetic studies on infectious diseases generally connect an individual's disease status to its own genotype, and therefore capture genetic effects on susceptibility only. However, they usually ignore variation in exposure to infectious herd mates, which may limit the accuracy of estimates of genetic effects on susceptibility. Moreover, genetic effects on infectivity will exist as well. Thus, to design optimal breeding strategies, it is essential that genetic effects on infectivity are quantified. Given the potential importance of genetic effects on infectivity, we set out to develop a model to estimate the effect of single nucleotide polymorphisms (SNPs) on both host susceptibility and host infectivity. To evaluate the quality of the resulting SNP effect estimates, we simulated an endemic disease in 10 groups of 100 individuals, and recorded time-series data on individual disease status. We quantified bias and precision of the estimates for different sizes of SNP effects, and identified the optimum recording interval when the number of records is limited. We present a generalized linear mixed model to estimate the effect of SNPs on both host susceptibility and host infectivity. SNP effects were on average slightly underestimated, i.e. estimates were conservative. Estimates were less precise for infectivity than for susceptibility. Given our sample size, the power to estimate SNP effects for susceptibility was 100% for differences between genotypes of a factor 1.56 or more, and was higher than 60% for infectivity for differences between genotypes of a factor 4 or more. When disease status was recorded 11 times on each

  15. Differential effects of genetic - and diet - induced obesity on fertility, spermatogenesis and sperm epigenome in adult male rats

    Directory of Open Access Journals (Sweden)

    Sharvari Deshpande

    2017-10-01

    Full Text Available Obesity is a global health issue affecting millions of people of different age groups. The incidence of male obesity induced infertility is rising in couples undergoing ARTs suggesting that obesity is an established risk factor for male infertility. Recent studies demonstrate that paternal diet induced obesity could induce epigenetic disturbances in offspring. Obesity is a multifactorial disorder with predominantly genetic or environmental causes. No studies have compared the effect of genetic and diet induced obesity on male reproduction. The present study aims to delineate effects of obesity on male fertility, spermatogenesis and sperm epigenome using two rat models: genetically induced obese (GIO – WNIN/OB and diet induced obese (DIO – High fat diet. Body weights were similar in both groups, but, differential effects on hormonal profiles were observed. Fertility assessment showed decreased litter size mainly due to increased pre- and post-implantation loss in DIO group. However, GIO group were infertile due to decrease in libido. We observed a decrease in sperm counts in GIO group but not in DIO group despite the body weights being similar in both the groups. Flow cytometry and cell type specific marker expression studies in testis revealed that both DIO and GIO affect mitosis and differentiation process by increasing spermatogonial proliferation. In DIO group, no effect was observed on meiosis whereas in GIO group, we observed an effect on meiosis. Spermiogenesis process was affected in both the groups. In order to study the effect of genetic and diet induced obesity on different aspects of spermatogenesis, we performed qRT-PCR to study expression of genes involved in spermatocyte progression, spermiogenesis process, reproductive hormone receptors and leptin signaling in testis. Since epigenetic mechanisms are susceptible to environmental and genetic changes, we analyzed the methylation status of Igf2-H19 DMR in spermatozoa of both the

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

    Science.gov (United States)

    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.

  17. [Advances in understanding Drosophila salivary gland polytene chromosome and its applications in genetics teaching].

    Science.gov (United States)

    Li, Gang; Chen, Fan-guo

    2015-06-01

    Drosophila salivary gland polytene chromosome, one of the three classical chromosomes with remarkable characteristics, has been used as an outstanding model for a variety of genetic studies since 1934. The greatest contribution of this model to genetics has been providing extraordinary angle of view in studying interphase chromosome structure and gene expression regulation. Additionally, it has been extensively used to understand some special genetic phenomena, such as dosage compensation and position-effect variegation. In this paper, we briefly review the advances in the study of Drosophila salivary gland chromosome, and try to systematically and effectively introduce this model system into genetics teaching practice in order to steer and inspire students' interest in genetics.

  18. Population Genetics of Three Dimensional Range Expansions

    Science.gov (United States)

    Lavrentovich, Maxim; Nelson, David

    2014-03-01

    We develop a simple model of genetic diversity in growing spherical cell clusters, where the growth is confined to the cluster surface. This kind of growth occurs in cells growing in soft agar, and can also serve as a simple model of avascular tumors. Mutation-selection balance in these radial expansions is strongly influenced by scaling near a neutral, voter model critical point and by the inflating frontier. We develop a scaling theory to describe how the dynamics of mutation-selection balance is cut off by inflation. Genetic drift, i.e., local fluctuations in the genetic diversity, also plays an important role, and can lead to the extinction even of selectively advantageous strains. We calculate this extinction probability, taking into account the effect of rough population frontiers.

  19. Genetic Algorithms Principles Towards Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    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.

  20. The effect of multiple paternity on genetic diversity of small populations during and after colonisation.

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    Marina Rafajlović

    Full Text Available Genetic variation within and among populations is influenced by the genetic content of the founders and the migrants following establishment. This is particularly true if populations are small, migration rate low and habitats arranged in a stepping-stone fashion. Under these circumstances the level of multiple paternity is critical since multiply mated females bring more genetic variation into founder groups than single mated females. One such example is the marine snail Littorina saxatilis that during postglacial times has invaded mainland refuge areas and thereafter small islands emerging due to isostatic uplift by occasional rafting of multiply mated females. We modelled effects of varying degrees of multiple paternity on the genetic variation of island populations colonised by the founders spreading from the mainland, by quantifying the population heterozygosity during both the transient colonisation process, and after a steady state (with migration has been reached. During colonisation, multiple mating by [Formula: see text] males increased the heterozygosity by [Formula: see text] in comparison with single paternity, while in the steady state the increase was [Formula: see text] compared with single paternity. In the steady state the increase of heterozygosity due to multiple paternity is determined by a corresponding increase in effective population size. During colonisation, by contrast, the increase in heterozygosity is larger and it cannot be explained in terms of the effective population size alone. During the steady-state phase bursts of high genetic variation spread through the system, and far from the mainland this led to short periods of high diversity separated by long periods of low diversity. The size of these fluctuations was boosted by multiple paternity. We conclude that following glacial periods of extirpation, recolonization of isolated habitats by this species has been supported by its high level of multiple paternity.

  1. The Effect of Multiple Paternity on Genetic Diversity of Small Populations during and after Colonisation

    KAUST Repository

    Rafajlović, Marina

    2013-10-28

    Genetic variation within and among populations is influenced by the genetic content of the founders and the migrants following establishment. This is particularly true if populations are small, migration rate low and habitats arranged in a stepping-stone fashion. Under these circumstances the level of multiple paternity is critical since multiply mated females bring more genetic variation into founder groups than single mated females. One such example is the marine snail Littorina saxatilis that during postglacial times has invaded mainland refuge areas and thereafter small islands emerging due to isostatic uplift by occasional rafting of multiply mated females. We modelled effects of varying degrees of multiple paternity on the genetic variation of island populations colonised by the founders spreading from the mainland, by quantifying the population heterozygosity during both the transient colonisation process, and after a steady state (with migration) has been reached. During colonisation, multiple mating by 2-10 males increased the heterozygosity by 10-300% in comparison with single paternity, while in the steady state the increase was 10-50% compared with single paternity. In the steady state the increase of heterozygosity due to multiple paternity is determined by a corresponding increase in effective population size. During colonisation, by contrast, the increase in heterozygosity is larger and it cannot be explained in terms of the effective population size alone. During the steady-state phase bursts of high genetic variation spread through the system, and far from the mainland this led to short periods of high diversity separated by long periods of low diversity. The size of these fluctuations was boosted by multiple paternity. We conclude that following glacial periods of extirpation, recolonization of isolated habitats by this species has been supported by its high level of multiple paternity. 2013 Rafajlovi? et al.

  2. Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

    Directory of Open Access Journals (Sweden)

    Liqiang Zhang

    2013-01-01

    Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

  3. Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics

    Science.gov (United States)

    Welch, Stephen M.; White, Jeffrey W.; Thorp, Kelly R.; Bello, Nora M.

    2018-01-01

    Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP’s) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP’s as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10−6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP’s becomes a robust means to help solve the genotype-to-phenotype problem in crops. PMID:29672629

  4. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

    2015-01-01

    scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

  5. 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

  6. Estimation of Genetic Parameters of Kleiber Ratio and Growth Traits in Kurdish Sheep

    Directory of Open Access Journals (Sweden)

    Davoud Ali Saghi

    2016-11-01

    Full Text Available Introduction Kurdish sheep breed is one of the most important native breeds of Iran. They are fat-tailed, large-sized, well adapted to the mountainous regions in northern Khorasan province and mainly raising for meat production under pastoral production system (28. Feed efficiency is a major component in the profitability of the small ruminant enterprise, because quality of range and pasture is low in poor environmental conditions in Iran. Growth rate and feed efficiency are two traits of great economic importance in sheep production and also Kleiber ratio has been suggested to be a useful indicator for these traits (2. There was no information regarding genetic parameters for growth traits in Kurdish sheep. Thus, the main objective of the present research was to estimate (covariance components and genetic parameters for pre- and post-weaning growth traits and Kleiber ratio in Kurdish sheep. Material and Methods In this study, the records of growth traits from 5144 lambs (from 161 rams and 1982 ewes were used. The data were collected during a 17-year period (1996–2013 in Kurdish sheep Breeding Station located in Shirvan city of northern Khorasan province. Traits investigated were average daily gain from birth to weaning (ADG0-3, average daily gain from weaning to six months of age (ADG3-6, average daily gain from six to nine months of age (ADG6-9, average daily gain from nine to twelve months of age (ADG9-12 and Kleiber ratios (KR defined as: KR1=ADG0-3/(BW30.75 KR2=ADG3-6/(BW60.75 KR3=ADG6-9/(BW90.75 KR4=ADG9-12/(BW120.75 Test of significance for the fixed effects to be included in the final functional model for each trait and calculation of least squares means was accomplished using GLM procedure of SAS software (24. The considered fixed effects were year of lambing (1996-2013, sex of lamb (male and female, type of birth (single and twin and age of ewe (1–7 years old. (Co variance components and genetic parameters were estimated applying

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. Quantifying and modeling birth order effects in autism.

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    Tychele Turner

    Full Text Available Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models. We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.

  12. The genetic and economic effect of preliminary culling in the seedling orchard

    Science.gov (United States)

    Don E. Riemenschneider

    1977-01-01

    The genetic and economic effects of two stages of truncation selection in a white spruce seedling orchard were investigated by computer simulation. Genetic effects were computed by assuming a bivariate distribution of juvenile and mature traits and volume was used as the selection criterion. Seed production was assumed to rise in a linear fashion to maturity and then...

  13. Effects of hybridization and evolutionary constraints on secondary metabolites: the genetic architecture of phenylpropanoids in European populus species.

    Science.gov (United States)

    Caseys, Celine; Stritt, Christoph; Glauser, Gaetan; Blanchard, Thierry; Lexer, Christian

    2015-01-01

    The mechanisms responsible for the origin, maintenance and evolution of plant secondary metabolite diversity remain largely unknown. Decades of phenotypic studies suggest hybridization as a key player in generating chemical diversity in plants. Knowledge of the genetic architecture and selective constraints of phytochemical traits is key to understanding the effects of hybridization on plant chemical diversity and ecological interactions. Using the European Populus species P. alba (White poplar) and P. tremula (European aspen) and their hybrids as a model, we examined levels of inter- and intraspecific variation, heritabilities, phenotypic correlations, and the genetic architecture of 38 compounds of the phenylpropanoid pathway measured by liquid chromatography and mass spectrometry (UHPLC-MS). We detected 41 quantitative trait loci (QTL) for chlorogenic acids, salicinoids and flavonoids by genetic mapping in natural hybrid crosses. We show that these three branches of the phenylpropanoid pathway exhibit different geographic patterns of variation, heritabilities, and genetic architectures, and that they are affected differently by hybridization and evolutionary constraints. Flavonoid abundances present high species specificity, clear geographic structure, and strong genetic determination, contrary to salicinoids and chlorogenic acids. Salicinoids, which represent important defence compounds in Salicaceae, exhibited pronounced genetic correlations on the QTL map. Our results suggest that interspecific phytochemical differentiation is concentrated in downstream sections of the phenylpropanoid pathway. In particular, our data point to glycosyltransferase enzymes as likely targets of rapid evolution and interspecific differentiation in the 'model forest tree' Populus.

  14. Effects of hybridization and evolutionary constraints on secondary metabolites: the genetic architecture of phenylpropanoids in European populus species.

    Directory of Open Access Journals (Sweden)

    Celine Caseys

    Full Text Available The mechanisms responsible for the origin, maintenance and evolution of plant secondary metabolite diversity remain largely unknown. Decades of phenotypic studies suggest hybridization as a key player in generating chemical diversity in plants. Knowledge of the genetic architecture and selective constraints of phytochemical traits is key to understanding the effects of hybridization on plant chemical diversity and ecological interactions. Using the European Populus species P. alba (White poplar and P. tremula (European aspen and their hybrids as a model, we examined levels of inter- and intraspecific variation, heritabilities, phenotypic correlations, and the genetic architecture of 38 compounds of the phenylpropanoid pathway measured by liquid chromatography and mass spectrometry (UHPLC-MS. We detected 41 quantitative trait loci (QTL for chlorogenic acids, salicinoids and flavonoids by genetic mapping in natural hybrid crosses. We show that these three branches of the phenylpropanoid pathway exhibit different geographic patterns of variation, heritabilities, and genetic architectures, and that they are affected differently by hybridization and evolutionary constraints. Flavonoid abundances present high species specificity, clear geographic structure, and strong genetic determination, contrary to salicinoids and chlorogenic acids. Salicinoids, which represent important defence compounds in Salicaceae, exhibited pronounced genetic correlations on the QTL map. Our results suggest that interspecific phytochemical differentiation is concentrated in downstream sections of the phenylpropanoid pathway. In particular, our data point to glycosyltransferase enzymes as likely targets of rapid evolution and interspecific differentiation in the 'model forest tree' Populus.

  15. 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.

  16. Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria.

    Directory of Open Access Journals (Sweden)

    Max J Feldman

    2017-06-01

    Full Text Available Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber. The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.

  17. Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria.

    Science.gov (United States)

    Feldman, Max J; Paul, Rachel E; Banan, Darshi; Barrett, Jennifer F; Sebastian, Jose; Yee, Muh-Ching; Jiang, Hui; Lipka, Alexander E; Brutnell, Thomas P; Dinneny, José R; Leakey, Andrew D B; Baxter, Ivan

    2017-06-01

    Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.

  18. Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction

    Science.gov (United States)

    Engleman, Eric A.; Katner, Simon N.; Neal-Beliveau, Bethany S.

    2016-01-01

    Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH’s effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system–dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine

  19. Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction.

    Science.gov (United States)

    Engleman, Eric A; Katner, Simon N; Neal-Beliveau, Bethany S

    2016-01-01

    Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH's effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system-dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine neurotransmission

  20. 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.

  1. Genetic anticipation in BRCA1/2 families after controlling for ascertainment bias and cohort effect

    Science.gov (United States)

    Guindalini, Rodrigo Santa Cruz; Song, Andrew; Fackenthal, James D.; Olopade, Olufunmilayo I.; Huo, Dezheng

    2016-01-01

    Background Genetic anticipation, the earlier onset of disease in successive generations, has been reported in hereditary breast and ovarian cancer syndrome (HBOC), but little is known about its underlying mechanisms. Ascertainment bias is a reason that has been suggested in previous studies. Likewise, cohort effect, which may be due to environmental factors, can be misinterpreted as genetic anticipation. Methods We conducted a review of pedigrees in 176 kindreds segregating deleterious mutations in BRCA1/2 genes who had at least two consecutive generations of the same cancer (breast or ovarian). Using mutation probabilities as analytical weights in weighted random-effect models, we calculated generational differences in age of onset of breast/ovarian cancer. Then we further controlled for ascertainment bias by excluding probands and adjusted for birth cohort effect in the anticipation models. Results The mean age of breast cancer for the probands’ generation was 41.9 years, which was 6.8 years and 9.8 years earlier than the parents’ and grandparents’ generations, respectively. The anticipation effect for breast cancer remained significant after excluding probands. There was a birth cohort effect: patients born in 1930s and 1940s had breast cancer 5.0 and 7.6 years earlier than patients born before 1920. The difference in breast cancer age of onset across generations was no longer significant after adjusting for birth cohort effect. Conclusions The observed anticipation effect was mainly driven by a decrease in age of onset across birth cohorts, underscoring the need for risk reducing interventions that target changing environmental/lifestyle factors in BRCA1/2 carriers. PMID:26992017

  2. New approaches to evaluating the genetic effects of the atomic bombs

    International Nuclear Information System (INIS)

    Neel, J.V.

    1995-01-01

    In the aftermath of the atomic bombings of Hiroshima and Nagasaki fifty years ago, one of the compelling biomedical questions that arose concerned the genetic effects of this exposure. More recently, revelations of the extent of industrial or accidental exposures in the former Soviet Union and charges that employment in the Sellafield Nuclear Reprocessing Plant in West Cumbria, England has resulted in a gene-mediated increase in children of plant employees have served to keep in the public mind the issue of the genetic risks of exposure to ionizing radiation. The study of the genetic effects of the atomic bombs has moved from the gross morphological level of congenital malformations to the examination of DNA. However, were the need for such genetic studies to arise in the foreseeable future, despite this impressive progress in DNA-oriented systems, the documentation of congenital defect, genetic disease and child survival would still be an essential component of any future study. Whatever the geneticists may think, the phenotypic well-being and survival of children are still the primary indicators on which the public, who ultimately supports these studies, will base its judgement of risk. 28 refs

  3. 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.

  4. 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…

  5. Genetic Engineering and the Amelioration of Genetic Defect

    Science.gov (United States)

    Lederberg, Joshua

    1970-01-01

    Discusses the claims for a brave new world of genetic manipulation" and concludes that if we could agree upon applying genetic (or any other effective) remedies to global problems we probably would need no rescourse to them. Suggests that effective methods of preventing genetic disease are prevention of mutations and detection and…

  6. Trapped in the extinction vortex? Strong genetic effects in a declining vertebrate population

    Directory of Open Access Journals (Sweden)

    Larsson Mikael

    2010-02-01

    Full Text Available Abstract Background Inbreeding and loss of genetic diversity are expected to increase the extinction risk of small populations, but detailed tests in natural populations are scarce. We combine long-term population and fitness data with those from two types of molecular markers to examine the role of genetic effects in a declining metapopulation of southern dunlins Calidris alpina schinzii, an endangered shorebird. Results The decline is associated with increased pairings between related individuals, including close inbreeding (as revealed by both field observations of parentage and molecular markers. Furthermore, reduced genetic diversity seems to affect individual fitness at several life stages. Higher genetic similarity between mates correlates negatively with the pair's hatching success. Moreover, offspring produced by related parents are more homozygous and suffer from increased mortality during embryonic development and possibly also after hatching. Conclusions Our results demonstrate strong genetic effects in a rapidly declining population, emphasizing the importance of genetic factors for the persistence of small populations.

  7. Reward circuitry dysfunction in psychiatric and neurodevelopmental disorders and genetic syndromes: animal models and clinical findings.

    Science.gov (United States)

    Dichter, Gabriel S; Damiano, Cara A; Allen, John A

    2012-07-06

    This review summarizes evidence of dysregulated reward circuitry function in a range of neurodevelopmental and psychiatric disorders and genetic syndromes. First, the contribution of identifying a core mechanistic process across disparate disorders to disease classification is discussed, followed by a review of the neurobiology of reward circuitry. We next consider preclinical animal models and clinical evidence of reward-pathway dysfunction in a range of disorders, including psychiatric disorders (i.e., substance-use disorders, affective disorders, eating disorders, and obsessive compulsive disorders), neurodevelopmental disorders (i.e., schizophrenia, attention-deficit/hyperactivity disorder, autism spectrum disorders, Tourette's syndrome, conduct disorder/oppositional defiant disorder), and genetic syndromes (i.e., Fragile X syndrome, Prader-Willi syndrome, Williams syndrome, Angelman syndrome, and Rett syndrome). We also provide brief overviews of effective psychopharmacologic agents that have an effect on the dopamine system in these disorders. This review concludes with methodological considerations for future research designed to more clearly probe reward-circuitry dysfunction, with the ultimate goal of improved intervention strategies.

  8. 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)

  9. Effects of early life trauma are dependent on genetic predisposition: a rat study

    Directory of Open Access Journals (Sweden)

    Russell Vivienne A

    2011-05-01

    Full Text Available Abstract Background Trauma experienced early in life increases the risk of developing a number of psychological and/or behavioural disorders. It is unclear, however, how genetic predisposition to a behavioural disorder, such as attention-deficit/hyperactivity disorder (ADHD, modifies the long-term effects of early life trauma. There is substantial evidence from family and twin studies for susceptibility to ADHD being inherited, implying a strong genetic component to the disorder. In the present study we used an inbred animal model of ADHD, the spontaneously hypertensive rat (SHR, to investigate the long-term consequences of early life trauma on emotional behaviour in individuals predisposed to developing ADHD-like behaviour. Methods We applied a rodent model of early life trauma, maternal separation, to SHR and Wistar-Kyoto rats (WKY, the normotensive control strain from which SHR were originally derived. The effects of maternal separation (removal of pups from dam for 3 h/day during the first 2 weeks of life on anxiety-like behaviour (elevated-plus maze and depressive-like behaviour (forced swim test were assessed in prepubescent rats (postnatal day 28 and 31. Basal levels of plasma corticosterone were measured using radioimmunoassay. Results The effect of maternal separation on SHR and WKY differed in a number of behavioural measures. Similar to its reported effect in other rat strains, maternal separation increased the anxiety-like behaviour of WKY (decreased open arm entries but not SHR. Maternal separation increased the activity of SHR in the novel environment of the elevated plus-maze, while it decreased that of WKY. Overall, SHR showed a more active response in the elevated plus-maze and forced swim test than WKY, regardless of treatment, and were also found to have higher basal plasma corticosterone compared to WKY. Maternal separation increased basal levels of plasma corticosterone in SHR females only, possibly through adaptive

  10. Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning

    DEFF Research Database (Denmark)

    Phuong, H N; Martin, O; de Boer, I J M

    2015-01-01

    , body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows......, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency....

  11. Genetic effects of ionising radiation in man

    International Nuclear Information System (INIS)

    Sankaranarayanan, K.

    1991-01-01

    A review is given of genetic risk estimation in man. Topics covered include the methods used, the germ cell stages and radiation conditions relevant for genetic risk estimation, doubling dose estimates, the classification and prevalence of naturally-occurring genetic disorders, the source of data used in the direct method of risk estimation, the genetic risk estimates from the mid-1970s to the present, the estimates of genetic risk used in ICRP 26 in 1977 and ICRP's current assessment of genetic risks. (UK)

  12. Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist

    DEFF Research Database (Denmark)

    2015-01-01

    BACKGROUND: To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. METHODS: We created a genetic score combining the effects of alleles...... of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers...... of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type...

  13. Genetic parameters and genetic trends in the Chinese × European Tiameslan composite pig line. II. Genetic trends

    Directory of Open Access Journals (Sweden)

    Legault Christian

    2000-01-01

    Full Text Available Abstract The Tiameslan line was created between 1983 and 1985 by mating Meishan × Jiaxing crossbred Chinese boars with sows from the Laconie composite male line. The Tiameslan line has been selected since then on an index combining average backfat thickness (ABT and days from 20 to 100 kg (DT. Direct and correlated responses to 11 years of selection were estimated using BLUP methodology applied to a multiple trait animal model. A total of 11 traits were considered, i.e.: ABT, DT, body weight at 4 (W4w, 8 (W8w and 22 (W22w weeks of age, teat number (TEAT, number of good teats (GTEAT, total number of piglets born (TNB, born alive (NBA and weaned (NW per litter, and birth to weaning survival rate (SURV. Performance data from a total of 4 881 males and 4 799 females from 1 341 litters were analysed. The models included both direct and maternal effects for ABT, W4w and W8w. Male and female performances were considered as different traits for W22w, DT and ABT. Genetic parameters estimated in another paper (Zhang et al., Genet. Sel. Evol. 32 (2000 41-56 were used to perform the analyses. Favourable phenotypic (ΔP and direct genetic trends (ΔGd were obtained for post-weaning growth traits and ABT. Trends for maternal effects were limited. Phenotypic and genetic trends were larger in females than in males for ABT (e.g. ΔGd = -0.48 vs. -0.38 mm/year, were larger in males for W22w (ΔGd = 0.90 vs. 0.58 kg/year and were similar in both sexes for DT (ΔGd = -0.54 vs. -0.55 day/year. Phenotypic and genetic trends were slightly favourable for W4w, W8w, TEAT and GTEAT and close to zero for reproductive traits.

  14. Radiological health effects models for nuclear power plant accident consequence analysis

    International Nuclear Information System (INIS)

    Evans, J.S.; Moeller, D.W.

    1989-01-01

    Improved health effects models have been developed for assessing the early effects, late somatic effects and genetic effects that might result from low-LET radiation exposures to populations following a major accident in a nuclear power plant. All the models have been developed in such a way that the dynamics of population risks can be analyzed. Estimates of life years lost and the duration of illnesses were generated and a framework recommended for summarizing health impacts. Uncertainty is addressed by providing models for upper, central and lower estimates of most effects. The models are believed to be a significant improvement over the models used in the U.S. Nuclear Regulatory Commission's Reactor Safety Study, and they can easily be modified to reflect advances in scientific understanding of the health effects of ionizing radiation

  15. Environmental Effects Exceed Genetic Effects on Perceived Intensity and Pleasantness of Several Odors

    DEFF Research Database (Denmark)

    Knaapila, Antti; Tuorila, Hely; Silventoinen, Karri

    2008-01-01

    and pleasantness of cinnamon, chocolate, turpentine, and isovaleric acid (sweaty) odors by quantitative genetic modeling of odor rating data from 856 twin individuals (including 83 complete monozygotic and 275 dizygotic twin pairs) aged 10-60 years (44% males and 56% females) from Australia, Denmark, and Finland...

  16. Snake Model Based on Improved Genetic Algorithm in Fingerprint Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mingying Zhang

    2016-12-01

    Full Text Available Automatic fingerprint identification technology is a quite mature research field in biometric identification technology. As the preprocessing step in fingerprint identification, fingerprint segmentation can improve the accuracy of fingerprint feature extraction, and also reduce the time of fingerprint preprocessing, which has a great significance in improving the performance of the whole system. Based on the analysis of the commonly used methods of fingerprint segmentation, the existing segmentation algorithm is improved in this paper. The snake model is used to segment the fingerprint image. Additionally, it is improved by using the global optimization of the improved genetic algorithm. Experimental results show that the algorithm has obvious advantages both in the speed of image segmentation and in the segmentation effect.

  17. 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

  18. Estimates of genetic parameters of body weight in descendants of x-irradiated rat spermatogonia

    International Nuclear Information System (INIS)

    Gianola, D.; Chapman, A.B.; Rutledge, J.J.

    1977-01-01

    Effects of nine generations of 450 R per generation of ancestral spermatogonial x irradiation of inbred rats on genetic parameters of body weight at 3, 6 and 10 weeks of age and of weight gains between these periods were studied. Covariances among relatives were estimated by mixed model and regression techniques in randomly selected lines with (R) and without (C) radiation history. Analyses of the data were based on five linear genetic models combining additive direct, additive indirect (maternal), dominance and environmental effects. Parameters in these models were estimated by generalized least-squares. A model including direct and indirect genetic effects fit more closely to the data in both R and C lines. Overdominance of induced mutations did not seem to be present. Ancestral irradiation increased maternal additive genetic variances of body weights and gains but not direct genetic variances. Theoretically, due to a negative direct-maternal genetic correlation, within full-sib family selection would be ineffective in increasing body weight at six weeks in both R and C lines. However, progress from mass selection would be expected to be faster in the R lines

  19. From animal models to human disease: a genetic approach for personalized medicine in ALS.

    Science.gov (United States)

    Picher-Martel, Vincent; Valdmanis, Paul N; Gould, Peter V; Julien, Jean-Pierre; Dupré, Nicolas

    2016-07-11

    Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disease in adults. Classical ALS is characterized by the death of upper and lower motor neurons leading to progressive paralysis. Approximately 10 % of ALS patients have familial form of the disease. Numerous different gene mutations have been found in familial cases of ALS, such as mutations in superoxide dismutase 1 (SOD1), TAR DNA-binding protein 43 (TDP-43), fused in sarcoma (FUS), C9ORF72, ubiquilin-2 (UBQLN2), optineurin (OPTN) and others. Multiple animal models were generated to mimic the disease and to test future treatments. However, no animal model fully replicates the spectrum of phenotypes in the human disease and it is difficult to assess how a therapeutic effect in disease models can predict efficacy in humans. Importantly, the genetic and phenotypic heterogeneity of ALS leads to a variety of responses to similar treatment regimens. From this has emerged the concept of personalized medicine (PM), which is a medical scheme that combines study of genetic, environmental and clinical diagnostic testing, including biomarkers, to individualized patient care. In this perspective, we used subgroups of specific ALS-linked gene mutations to go through existing animal models and to provide a comprehensive profile of the differences and similarities between animal models of disease and human disease. Finally, we reviewed application of biomarkers and gene therapies relevant in personalized medicine approach. For instance, this includes viral delivering of antisense oligonucleotide and small interfering RNA in SOD1, TDP-43 and C9orf72 mice models. Promising gene therapies raised possibilities for treating differently the major mutations in familial ALS cases.

  20. 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

  1. Genetic or pharmacological activation of the Drosophila PGC-1α ortholog spargel rescues the disease phenotypes of genetic models of Parkinson's disease.

    Science.gov (United States)

    Ng, Chee-Hoe; Basil, Adeline H; Hang, Liting; Tan, Royston; Goh, Kian-Leong; O'Neill, Sharon; Zhang, Xiaodong; Yu, Fengwei; Lim, Kah-Leong

    2017-07-01

    Despite intensive research, the etiology of Parkinson's disease (PD) remains poorly understood and the disease remains incurable. However, compelling evidence gathered over decades of research strongly support a role for mitochondrial dysfunction in PD pathogenesis. Related to this, PGC-1α, a key regulator of mitochondrial biogenesis, has recently been proposed to be an attractive target for intervention in PD. Here, we showed that silencing of expression of the Drosophila PGC-1α ortholog spargel results in PD-related phenotypes in flies and also seem to negate the effects of AMPK activation, which we have previously demonstrated to be neuroprotective, that is, AMPK-mediated neuroprotection appears to require PGC-1α. Importantly, we further showed that genetic or pharmacological activation of the Drosophila PGC-1α ortholog spargel is sufficient to rescue the disease phenotypes of Parkin and LRRK2 genetic fly models of PD, thus supporting the proposed use of PGC-1α-related strategies for neuroprotection in PD. Copyright © 2017 National Neuroscience Institute. Published by Elsevier Inc. All rights reserved.

  2. The joint effects of background selection and genetic recombination on local gene genealogies.

    Science.gov (United States)

    Zeng, Kai; Charlesworth, Brian

    2011-09-01

    Background selection, the effects of the continual removal of deleterious mutations by natural selection on variability at linked sites, is potentially a major determinant of DNA sequence variability. However, the joint effects of background selection and genetic recombination on the shape of the neutral gene genealogy have proved hard to study analytically. The only existing formula concerns the mean coalescent time for a pair of alleles, making it difficult to assess the importance of background selection from genome-wide data on sequence polymorphism. Here we develop a structured coalescent model of background selection with recombination and implement it in a computer program that efficiently generates neutral gene genealogies for an arbitrary sample size. We check the validity of the structured coalescent model against forward-in-time simulations and show that it accurately captures the effects of background selection. The model produces more accurate predictions of the mean coalescent time than the existing formula and supports the conclusion that the effect of background selection is greater in the interior of a deleterious region than at its boundaries. The level of linkage disequilibrium between sites is elevated by background selection, to an extent that is well summarized by a change in effective population size. The structured coalescent model is readily extendable to more realistic situations and should prove useful for analyzing genome-wide polymorphism data.

  3. 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.

  4. The genetic architecture of fitness in a seed beetle: assessing the potential for indirect genetic benefits of female choice

    Directory of Open Access Journals (Sweden)

    Maklakov AA

    2008-10-01

    Full Text Available Abstract Background Quantifying the amount of standing genetic variation in fitness represents an empirical challenge. Unfortunately, the shortage of detailed studies of the genetic architecture of fitness has hampered progress in several domains of evolutionary biology. One such area is the study of sexual selection. In particular, the evolution of adaptive female choice by indirect genetic benefits relies on the presence of genetic variation for fitness. Female choice by genetic benefits fall broadly into good genes (additive models and compatibility (non-additive models where the strength of selection is dictated by the genetic architecture of fitness. To characterize the genetic architecture of fitness, we employed a quantitative genetic design (the diallel cross in a population of the seed beetle Callosobruchus maculatus, which is known to exhibit post-copulatory female choice. From reciprocal crosses of inbred lines, we assayed egg production, egg-to-adult survival, and lifetime offspring production of the outbred F1 daughters (F1 productivity. Results We used the bio model to estimate six components of genetic and environmental variance in fitness. We found sizeable additive and non-additive genetic variance in F1 productivity, but lower genetic variance in egg-to-adult survival, which was strongly influenced by maternal and paternal effects. Conclusion Our results show that, in order to gain a relevant understanding of the genetic architecture of fitness, measures of offspring fitness should be inclusive and should include quantifications of offspring reproductive success. We note that our estimate of additive genetic variance in F1 productivity (CVA = 14% is sufficient to generate indirect selection on female choice. However, our results also show that the major determinant of offspring fitness is the genetic interaction between parental genomes, as indicated by large amounts of non-additive genetic variance (dominance and/or epistasis

  5. Life cycle assessment of genetically modified products as a basis for a comprehensive assessment of possible environmental effects

    International Nuclear Information System (INIS)

    Kloepffer, W.; Renner, I.; Schmidt, E.; Tappeser, B.; Gensch, C.O.; Gaugitsch, H.

    2001-01-01

    In the preceding project 'Life Cycle Assessment of genetically modified products as a basis for a comprehensive assessment of possible environmental effects' for the first time the risks of deliberate release of genetically modified organisms (GMOs) into the environment have been taken into account in a Life Cycle Assessment (LCA). This was performed by a risk assessment in addition to a quantitative impact assessment. As from a methodological perspective this was not satisfactory, the Federal Environment Agency commissioned the C.A.U. GmbH and the Institute of Applied Ecology Freiburg to further develop the impact assessment methodology for the risks of GMOs. Any further development of the methodology of impact assessment in LCAs has to be performed on the basis of the standard EN/ISO 14042. There are 2 options for taking into account risks of deliberate release of GMOs: 1. allocation of the potential effects resulting from the genetic modification on human beings and the environment to existing categories of the impact assessment and attempt to quantify within those existing methods of characterization; 2. development of a new category, e.g. 'effects of genetically modified crop plants'. In order to asses the possibilities under option 1 various models of characterization within the categories human toxicity, ecotoxicity and land use (appropriation of environmental space) have been analyzed. The risks of GMOs identified and dealt with in the preceding study were allocated to these categories. It seemed to be impossible to integrate the risks in existing models of characterization for human toxicity and ecotoxicity, as these are based on exposure and impact factors. The development of a factor for exposure seems possible for GMOs, however a suitable impact factor is not possible to generate. In addition it was analyzed if in other impact categories which are difficult to quantify any solutions for operationalization exist. This does not seem to be the case. As a

  6. 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

  7. The genetic effects of radio-activity in man and other organisms

    International Nuclear Information System (INIS)

    Parry, J.M.

    1979-01-01

    The changes that occur in the chromosomal information and which give rise to observable genetic effects stem from the induction by radiation of a number of lesions within the DNA. The relative frequencies of single and double strand breaks induced in DNA is dependent upon the type of radiation exposure given. Radiation sensitivity of a variety of different species of bacteria irradiated with gamma rays in air are given. The effect of dose rate upon radiation induced genetic damage indicates that at low dose rates the cells are capable of handling or repairing a higher proportion of the radiation induced DNA lesions before they undergo the events leading to chromosome and chromatid aberration. The radiation quality, expressed in terms of LET (linear energy transfer) also influence the induction of genetic damage. (U.K.)

  8. Genetic origin of the relationship between parental negativity and behavior problems from early childhood to adolescence: A longitudinal genetically sensitive study

    Science.gov (United States)

    Alemany, Silvia; Rijsdijk, Frühling V.; Haworth, Claire Margaret Alison; Fañanás, Lourdes; Plomin, Robert

    2013-01-01

    Little is known about how genetic and environmental factors contribute to the association between parental negativity and behavior problems from early childhood to adolescence. The current study fitted a cross-lagged model in a sample consisting of 4,075 twin pairs to explore (a) the role of genetic and environmental factors in the relationship between parental negativity and behavior problems from age 4 to age 12, (b) whether parent-driven and child-driven processes independently explain the association, and (c) whether there are sex differences in this relationship. Both phenotypes showed substantial genetic influence at both ages. The concurrent overlap between them was mainly accounted for by genetic factors. Causal pathways representing stability of the phenotypes and parent-driven and child-driven effects significantly and independently account for the association. Significant but slight differences were found between males and females for parent-driven effects. These results were highly similar when general cognitive ability was added asa covariate. In summary, the longitudinal association between parental negativity and behavior problems seems to be bidirectional and mainly accounted for by genetic factors. Furthermore, child-driven effects were mainly genetically mediated, and parent-driven effects were a function of both genetic and shared-environmental factors. PMID:23627958

  9. Estimates of Genetic Parameters of Production Traits for Khuzestan Buffaloes of Iran using Repeated-Records Animal Model

    Directory of Open Access Journals (Sweden)

    Maryam Baharizadeh

    2012-10-01

    Full Text Available Buffalo milk yield records were obtained from monthly records of the Animal Breeding Organization of Iran from 1992 to 2009 in 33 herds raised in the Khuzestan province. Variance components, heritability and repeatability were estimated for milk yield, fat yield, fat percentage, protein yield and protein percentage. These estimates were carried out through single trait animal model using DFREML program. Herd-year-season was considered as fixed effect in the model. For milk production traits, age at calving was fitted as a covariate. The additive genetic and permanent environmental effects were also included in the model. The mean values (±SD for milk yield, fat yield, fat percentage, protein yield and protein percentage were 2285.08±762.47 kg, 144.35±54.86 kg, 6.25±0.90%, 97.30±26.73 kg and 4.19±0.27%, respectively. The heritability (±SE of milk yield, fat yield, fat percentage, protein yield and protein percentage were 0.093±0.08, 0.054±0.06, 0.043±0.05, 0.093±0.16 and zero, respectively. These estimates for repeatability were 0.272, 0.132, 0.043, 0.674 and 0.0002, respectively. Lower values of genetic parameter estimates require more data and reliable pedigree records.

  10. On theoretical models of gene expression evolution with random genetic drift and natural selection.

    Directory of Open Access Journals (Sweden)

    Osamu Ogasawara

    2009-11-01

    Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

  11. Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

    Science.gov (United States)

    Greenberg, David A; Zhang, Junying; Shmulewitz, Dvora; Strug, Lisa J; Zimmerman, Regina; Singh, Veena; Marathe, Sudhir

    2005-12-30

    The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also

  12. Genetic background effects of keratin 8 and 18 in a DDC-induced hepatotoxicity and Mallory-Denk body formation mouse model.

    Science.gov (United States)

    Haybaeck, Johannes; Stumptner, Cornelia; Thueringer, Andrea; Kolbe, Thomas; Magin, Thomas M; Hesse, Michael; Fickert, Peter; Tsybrovskyy, Oleksiy; Müller, Heimo; Trauner, Michael; Zatloukal, Kurt; Denk, Helmut

    2012-06-01

    Keratin 8 (K8) and keratin 18 (K18) form the major hepatocyte cytoskeleton. We investigated the impact of genetic loss of either K8 or K18 on liver homeostasis under toxic stress with the hypothesis that K8 and K18 exert different functions. krt8⁻/⁻ and krt18⁻/⁻ mice crossed into the same 129-ola genetic background were treated by acute and chronic administration of 3,5-diethoxy-carbonyl-1,4-dihydrocollidine (DDC). In acutely DDC-intoxicated mice, macrovesicular steatosis was more pronounced in krt8⁻/⁻ and krt18⁻/⁻ compared with wild-type (wt) animals. Mallory-Denk bodies (MDBs) appeared in krt18⁻/⁻ mice already at an early stage of intoxication in contrast to krt8⁻/⁻ mice that did not display MDB formation when fed with DDC. Keratin-deficient mice displayed significantly lower numbers of apoptotic hepatocytes than wt animals. krt8⁻/⁻, krt18⁻/⁻ and control mice displayed comparable cell proliferation rates. Chronically DDC-intoxicated krt18⁻/⁻ and wt mice showed a similarly increased degree of steatohepatitis with hepatocyte ballooning and MDB formation. In krt8⁻/⁻ mice, steatosis was less, ballooning, and MDBs were absent. krt18⁻/⁻ mice developed MDBs whereas krt8⁻/⁻ mice on the same genetic background did not, highlighting the significance of different structural properties of keratins. They are independent of the genetic background as an intrinsic factor. By contrast, toxicity effects may depend on the genetic background. krt8⁻/⁻ and krt18⁻/⁻ mice on the same genetic background show similar sensitivity to DDC intoxication and almost resemble wt animals regarding survival, degree of porphyria, liver-to-body weight ratio, serum bilirubin and liver enzyme levels. This stands in contrast to previous work where krt8⁻/⁻ and krt18⁻/⁻ mice on different genetic backgrounds were investigated.

  13. 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).

  14. 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

  15. Functional genetics of intraspecific ecological interactions in Arabidopsis thaliana.

    Science.gov (United States)

    Wolf, Jason B; Mutic, Joshua J; Kover, Paula X

    2011-05-12

    Studying the genetic basis of traits involved in ecological interactions is a fundamental part of elucidating the connections between evolutionary and ecological processes. Such knowledge allows one to link genetic models of trait evolution with ecological models describing interactions within and between species. Previous work has shown that connections between genetic and ecological processes in Arabidopsis thaliana may be mediated by the fact that quantitative trait loci (QTL) with 'direct' effects on traits of individuals also have pleiotropic 'indirect' effects on traits expressed in neighbouring plants. Here, we further explore these connections by examining functional relationships between traits affected directly and indirectly by the same QTL. We develop a novel approach using structural equation models (SEMs) to determine whether observed pleiotropic effects result from traits directly affected by the QTL in focal individuals causing the changes in the neighbours' phenotypes. This hypothesis was assessed using SEMs to test whether focal plant phenotypes appear to mediate the connection between the focal plants' genotypes and the phenotypes of their neighbours, or alternatively, whether the connection between the focal plants' genotypes and the neighbours' phenotypes is mediated by unmeasured traits. We implement this analysis using a QTL of major effect that maps to the well-characterized flowering locus, FRIGIDA. The SEMs support the hypothesis that the pleiotropic indirect effects of this locus arise from size and developmental timing-related traits in focal plants affecting the expression of developmental traits in their neighbours. Our findings provide empirical insights into the genetics and nature of intraspecific ecological interactions. Our technique holds promise in directing future work into the genetic basis and functional relationship of traits mediating and responding to ecological interactions.

  16. Compensatory mechanisms in genetic models of neurodegeneration: are the mice better than humans?

    Directory of Open Access Journals (Sweden)

    Grzegorz eKreiner

    2015-03-01

    Full Text Available Neurodegenerative diseases are one of the main causes of mental and physical disabilities. Neurodegeneration has been estimated to begin many years before the first clinical symptoms manifest, and even a prompt diagnosis at this stage provides very little advantage for a more effective treatment as the currently available pharmacotherapies are based on disease symptomatology. The etiology of the majority of neurodegenerative diseases remains unknown, and even for those diseases caused by identified genetic mutations, the direct pathways from gene alteration to final cell death have not yet been fully elucidated. Advancements in genetic engineering have provided many transgenic mice that are used as an alternative to pharmacological models of neurodegenerative diseases. Surprisingly, even the models reiterating the same causative mutations do not fully recapitulate the inevitable neuronal loss, and some fail to even show phenotypic alterations, which suggests the possible existence of compensatory mechanisms. A better evaluation of these mechanisms may not only help us to explain why neurodegenerative diseases are mostly late-onset disorders in humans but may also provide new markers and targets for novel strategies designed to extend neuronal function and survival. The aim of this mini-review is to draw attention to this under-explored field in which investigations may reasonably contribute to unveiling hidden reserves in the organism.

  17. Genetic inhibition of CETP, ischemic vascular disease and mortality, and possible adverse effects

    DEFF Research Database (Denmark)

    Johannsen, Trine Holm; Frikke-Schmidt, Ruth; Schou, Jesper

    2012-01-01

    This study tested whether genetic variation in the CETP gene is consistent with a protective effect of cholesteryl ester transfer protein (CETP) inhibition on risk of ischemic events and on total mortality, without the adverse effects reported for torcetrapib.......This study tested whether genetic variation in the CETP gene is consistent with a protective effect of cholesteryl ester transfer protein (CETP) inhibition on risk of ischemic events and on total mortality, without the adverse effects reported for torcetrapib....

  18. gPGA: GPU Accelerated Population Genetics Analyses.

    Directory of Open Access Journals (Sweden)

    Chunbao Zhou

    Full Text Available The isolation with migration (IM model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC simulations of gene genealogies. But computational burden of IM program has placed limits on its application.With strong computational power, Graphics Processing Unit (GPU has been widely used in many fields. In this article, we present an effective implementation of IM program on one GPU based on Compute Unified Device Architecture (CUDA, which we call gPGA.Compared with IM program, gPGA can achieve up to 52.30X speedup on one GPU. The evaluation results demonstrate that it allows datasets to be analyzed effectively and rapidly for research on divergence population genetics. The software is freely available with source code at https://github.com/chunbaozhou/gPGA.

  19. 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

  20. Environment Changes Genetic Effects on Respiratory Conditions and Allergic Phenotypes

    DEFF Research Database (Denmark)

    Song, Yong; Schwager, Michelle J; Backer, Vibeke

    2017-01-01

    The prevalence of asthma and allergic diseases is disproportionately distributed among different populations, with an increasing trend observed in Western countries. Here we investigated how the environment affected genotype-phenotype association in a genetically homogeneous, but geographically...... separated population. We evaluated 18 single nucleotide polymorphisms (SNPs) corresponding to 8 genes (ADAM33, ALOX5, LT-α, LTC4S, NOS1, ORMDL3, TBXA2R and TNF-α), the lung function and five respiratory/allergic conditions (ever asthma, bronchitis, rhinitis, dermatitis and atopy) in two populations of Inuit......-phenotype associations relating to bronchitis and allergy susceptibility are dependent on the environment and that environmental factors/lifestyles modify genetic predisposition and change the genetic effects on diseases....

  1. Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

    Directory of Open Access Journals (Sweden)

    Nunes Virginia

    2008-01-01

    Full Text Available Abstract Background Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC. Conclusion This study proposes that variation at putative 8q24 cis-regulator(s of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

  2. 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.

  3. Cause and effect analysis by fuzzy relational equations and a genetic algorithm

    International Nuclear Information System (INIS)

    Rotshtein, Alexander P.; Posner, Morton; Rakytyanska, Hanna B.

    2006-01-01

    This paper proposes using a genetic algorithm as a tool to solve the fault diagnosis problem. The fault diagnosis problem is based on a cause and effect analysis which is formally described by fuzzy relations. Fuzzy relations are formed on the basis of expert assessments. Application of expert fuzzy relations to restore and identify the causes through the observed effects requires the solution to a system of fuzzy relational equations. In this study this search for a solution amounts to solving a corresponding optimization problem. An optimization algorithm is based on the application of genetic operations of crossover, mutation and selection. The genetic algorithm suggested here represents an application in expert systems of fault diagnosis and quality control

  4. Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

    Science.gov (United States)

    Nené, Nuno R; Dunham, Alistair S; Illingworth, Christopher J R

    2018-05-01

    A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. Copyright © 2018 Nené et al.

  5. Genetic and environmental effects on performance traits of ...

    African Journals Online (AJOL)

    Genetic and environmental effects on performance traits of Simmentaler cattle on the Transvaal Highveld. Tina Rust, J van der Westhuizen. Abstract. No Abstract. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · AJOL African Journals Online. HOW TO USE ...

  6. Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

    Science.gov (United States)

    Cook, James P; Mahajan, Anubha; Morris, Andrew P

    2017-02-01

    Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

  7. Genetic basis of a cognitive complexity metric.

    Directory of Open Access Journals (Sweden)

    Narelle K Hansell

    Full Text Available Relational complexity (RC is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ, reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787. Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG, followed by meta-analysis (N>6500 at the single marker level. Twin modelling showed RC is highly heritable (67%, has considerable genetic overlap with IQ (59%, and is a major component of genetic covariation between reasoning and working memory (72%. At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB, and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.

  8. Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

    Science.gov (United States)

    Sztepanacz, Jacqueline L; Blows, Mark W

    2017-07-01

    The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

  9. Estimates of genetic