Academic literature on the topic 'Quantitative Genetics Model'
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Journal articles on the topic "Quantitative Genetics Model"
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Zeng, Z. B., and C. C. Cockerham. "Mutation models and quantitative genetic variation." Genetics 133, no. 3 (March 1, 1993): 729–36. http://dx.doi.org/10.1093/genetics/133.3.729.
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Abstract Analyses of evolution and maintenance of quantitative genetic variation depend on the mutation models assumed. Currently two polygenic mutation models have been used in theoretical analyses. One is the random walk mutation model and the other is the house-of-cards mutation model. Although in the short term the two models give similar results for the evolution of neutral genetic variation within and between populations, the predictions of the changes of the variation are qualitatively different in the long term. In this paper a more general mutation model, called the regression mutation model, is proposed to bridge the gap of the two models. The model regards the regression coefficient, gamma, of the effect of an allele after mutation on the effect of the allele before mutation as a parameter. When gamma = 1 or 0, the model becomes the random walk model or the house-of-cards model, respectively. The additive genetic variances within and between populations are formulated for this mutation model, and some insights are gained by looking at the changes of the genetic variances as gamma changes. The effects of gamma on the statistical test of selection for quantitative characters during macroevolution are also discussed. The results suggest that the random walk mutation model should not be interpreted as a null hypothesis of neutrality for testing against alternative hypotheses of selection during macroevolution because it can potentially allocate too much variation for the change of population means under neutrality.
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Tachida, H., and C. C. Cockerham. "A building block model for quantitative genetics." Genetics 121, no. 4 (April 1, 1989): 839–44. http://dx.doi.org/10.1093/genetics/121.4.839.
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Abstract We introduce a quantitative genetic model for multiple alleles which permits the parameterization of the degree, D, of dominance of favorable or unfavorable alleles. We assume gene effects to be random from some distribution and independent of the D's. We then fit the usual least-squares population genetic model of additive and dominance effects in an infinite equilibrium population to determine the five genetic components--additive variance sigma 2 a, dominance variance sigma 2 d, variance of homozygous dominance effects d2, covariance of additive and homozygous dominance effects d1, and the square of the inbreeding depression h--required to treat finite populations and large populations that have been through a bottleneck or in which there is inbreeding. The effects of dominance can be summarized as functions of the average, D, and the variance, sigma 2 D. An important distinction arises between symmetrical and nonsymmetrical distributions of gene effects. With symmetrical distributions d1 = -d2/2 which is always negative, and the contribution of dominance to sigma 2 a is equal to d2/2. With nonsymmetrical distributions there is an additional contribution H to sigma 2 a and -H/2 to d1, the sign of H being determined by D and the skew of the distribution. Some numerical evaluations are presented for the normal and exponential distributions of gene effects, illustrating the effects of the number of alleles and of the variation in allelic frequencies. Random additive by additive (a*a) epistatic effects contribute to sigma 2 a and to the a*a variance, sigma 2/aa, the relative contributions depending on the number of alleles and the variation in allelic frequencies.(ABSTRACT TRUNCATED AT 250 WORDS)
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Zhivotovsky, L. A., and M. W. Feldman. "On models of quantitative genetic variability: a stabilizing selection-balance model." Genetics 130, no. 4 (April 1, 1992): 947–55. http://dx.doi.org/10.1093/genetics/130.4.947.
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Abstract A model of stabilizing selection on a multilocus character is proposed that allows the maintenance of stable allelic polymorphism and linkage disequilibrium. The model is a generalization of Lerner's model of homeostasis in which heterozygotes are less susceptible to environmental variation and hence are superior to homozygotes under phenotypic stabilizing selection. The analysis is carried out for weak selection with a quadratic-deviation model for the stabilizing selection. The stationary state is characterized by unequal allele frequencies, unequal proportions of complementary gametes, and a reduction of the genetic (and phenotypic) variance by the linkage disequilibrium. The model is compared with Mather's polygenic balance theory, with models that include mutation-selection balance, and others that have been proposed to study the role of linkage disequilibrium in quantitative inheritance.
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Kao, Chen-Hung, and Zhao-Bang Zeng. "Modeling Epistasis of Quantitative Trait Loci Using Cockerham's Model." Genetics 160, no. 3 (March 1, 2002): 1243–61. http://dx.doi.org/10.1093/genetics/160.3.1243.
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AbstractWe use the orthogonal contrast scales proposed by Cockerham to construct a genetic model, called Cockerham's model, for studying epistasis between genes. The properties of Cockerham's model in modeling and mapping epistatic genes under linkage equilibrium and disequilibrium are investigated and discussed. Because of its orthogonal property, Cockerham's model has several advantages in partitioning genetic variance into components, interpreting and estimating gene effects, and application to quantitative trait loci (QTL) mapping when compared to other models, and thus it can facilitate the study of epistasis between genes and be readily used in QTL mapping. The issues of QTL mapping with epistasis are also addressed. Real and simulated examples are used to illustrate Cockerham's model, compare different models, and map for epistatic QTL. Finally, we extend Cockerham's model to multiple loci and discuss its applications to QTL mapping.
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Hill, William G. "Sewall Wright and quantitative genetics." Genome 31, no. 1 (January 1, 1989): 190–95. http://dx.doi.org/10.1139/g89-033.
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Some aspects of Wright's great contribution to quantitative genetics and animal breeding are reviewed in relation to current research and practice. Particular aspects discussed are as follows: the utility of his definition of inbreeding coefficient in terms of the correlation of uniting gametes; the maintenance of genetic variation in the optimum model; the inter-relations between past and present animal-breeding practice and the shifting-balance theory of evolution.Key words: quantitative genetics, inbreeding coefficient, genetic variation, evolution.
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Luo, L., Y.-M. Zhang, and S. Xu. "A quantitative genetics model for viability selection." Heredity 94, no. 3 (November 10, 2004): 347–55. http://dx.doi.org/10.1038/sj.hdy.6800615.
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Nagylaki, T. "Geographical variation in a quantitative character." Genetics 136, no. 1 (January 1, 1994): 361–81. http://dx.doi.org/10.1093/genetics/136.1.361.
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Abstract A model for the evolution of the local averages of a quantitative character under migration, selection, and random genetic drift in a subdivided population is formulated and investigated. Generations are discrete and nonoverlapping; the monoecious, diploid population mates at random in each deme. All three evolutionary forces are weak, but the migration pattern and the local population numbers are otherwise arbitrary. The character is determined by purely additive gene action and a stochastically independent environment; its distribution is Gaussian with a constant variance; and it is under Gaussian stabilizing selection with the same parameters in every deme. Linkage disequilibrium is neglected. Most of the results concern the covariances of the local averages. For a finite number of demes, explicit formulas are derived for (i) the asymptotic rate and pattern of convergence to equilibrium, (ii) the variance of a suitably weighted average of the local averages, and (iii) the equilibrium covariances when selection and random drift are much weaker than migration. Essentially complete analyses of equilibrium and convergence are presented for random outbreeding and site homing, the Levene and island models, the circular habitat and the unbounded linear stepping-stone model in the diffusion approximation, and the exact unbounded stepping-stone model in one and two dimensions.
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Andersson, Leif. "Fisher’s quantitative genetic model and the molecular genetics of multifactorial traits." Journal of Animal Breeding and Genetics 135, no. 6 (October 2018): 391–92. http://dx.doi.org/10.1111/jbg.12362.
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Caballero, A., and P. D. Keightley. "A pleiotropic nonadditive model of variation in quantitative traits." Genetics 138, no. 3 (November 1, 1994): 883–900. http://dx.doi.org/10.1093/genetics/138.3.883.
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Abstract A model of mutation-selection-drift balance incorporating pleiotropic and dominance effects of new mutations on quantitative traits and fitness is investigated and used to predict the amount and nature of genetic variation maintained in segregating populations. The model is based on recent information on the joint distribution of mutant effects on bristle traits and fitness in Drosophila melanogaster from experiments on the accumulation of spontaneous and P element-induced mutations. These experiments suggest a leptokurtic distribution of effects with an intermediate correlation between effects on the trait and fitness. Mutants of large effect tend to be partially recessive while those with smaller effect are on average additive, but apparently with very variable gene action. The model is parameterized with two different sets of information derived from P element insertion and spontaneous mutation data, though the latter are not fully known. They differ in the number of mutations per generation which is assumed to affect the trait. Predictions of the variance maintained for bristle number assuming parameters derived from effects of P element insertions, in which the proportion of mutations with an effect on the trait is small, fit reasonably well with experimental observations. The equilibrium genetic variance is nearly independent of the degree of dominance of new mutations. Heritabilities of between 0.4 and 0.6 are predicted with population sizes from 10(4) to 10(6), and most of the variance for the metric trait in segregating population is due to a small proportion of mutations (about 1% of the total number) with neutral or nearly neutral effects on fitness and intermediate effects on the trait (0.1-0.5 sigma P).(ABSTRACT TRUNCATED AT 250 WORDS)
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Eshel, Ilan, and Carlo Matessi. "Canalization, Genetic Assimilation and Preadaptation: A Quantitative Genetic Model." Genetics 149, no. 4 (August 1, 1998): 2119–33. http://dx.doi.org/10.1093/genetics/149.4.2119.
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Abstract We propose a mathematical model to analyze the evolution of canalization for a trait under stabilizing selection, where each individual in the population is randomly exposed to different environmental conditions, independently of its genotype. Without canalization, our trait (primary phenotype) is affected by both genetic variation and environmental perturbations (morphogenic environment). Selection of the trait depends on individually varying environmental conditions (selecting environment). Assuming no plasticity initially, morphogenic effects are not correlated with the direction of selection in individual environments. Under quite plausible assumptions we show that natural selection favors a system of canalization that tends to repress deviations from the phenotype that is optimal in the most common selecting environment. However, many experimental results, dating back to Waddington and others, indicate that natural canalization systems may fail under extreme environments. While this can be explained as an impossibility of the system to cope with extreme morphogenic pressure, we show that a canalization system that tends to be inactivated in extreme environments is even more advantageous than rigid canalization. Moreover, once this adaptive canalization is established, the resulting evolution of primary phenotype enables substantial preadaptation to permanent environmental changes resembling extreme niches of the previous environment.
Dissertations / Theses on the topic "Quantitative Genetics Model"
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Shen, Xia. "Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-170091.
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This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision. Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).
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Bao, Haikun. "Bayesian hierarchical regression model to detect quantitative trait loci /." Electronic version (PDF), 2006. http://dl.uncw.edu/etd/2006/baoh/haikunbao.pdf.
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BARBIERI, MIRKO. "THE GENETICS OF LEAF RUST RESISTANCE IN THE MODEL GRASS BRACHYPODIUM DISTACHYON." Doctoral thesis, Università Cattolica del Sacro Cuore, 2009. http://hdl.handle.net/10280/640.
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Brachypodium distachyon è stato recentemente proposto come pianta modello per le Triticeae che includono frumento e orzo. L’obbiettivo del presente studio è stato quello di identificare regioni genomiche associate con la resistenza quantitativa alla ruggine fogliare in Brachypodium. Le malattie causate dalle ruggini fogliari causano ingenti perdite in termini di produzione delle specie cerealicole. Una popolazione di 110 individui F2 è stata sviluppata incrociando due linee inbred di Brachypodium e una mappa di linkage di marcatori AFLP è stata create. La mappa di linkage consiste di 192 loci AFLP in dieci gruppi di linkage, e copre una lunghezza pari a 1,231 Kosambi cM. Allo scopo di identificare loci coinvolti nella resistenza quantitativa sulla mappa, i 110 individui F2 sono stati valutati per la loro reazione alla ruggine fogliare allo stadio di plantula e a quello adulto. Per confermare i risultati delle piante F2, le rispettive famiglie F3 sono state studiate per la loro resistenza alla ruggine fogliare in due esperimenti indipendenti. Due loci genomici sembrano essere maggiormente coinvolti nella resistenza.Brachypodium distachyon has been proposed as a model species for the tribe of the Triticeae, which includes wheat and barley. The objective of our study was to identify the genomic regions associated with quantitative resistance to leaf rust in Brachypodium. Leaf rust diseases cause significant reductions annually in yield of cereal crops worldwide. An F2 mapping population of 110 individuals was generated between two Brachypodium inbred lines and a AFLP-based linkage map was developed. The linkage map consists of 192 AFLP loci in ten linkage groups, and spans a total genetic length of 1,231 Kosambi cM. To locate quantitative resistance loci on the map, the 110 F2 plants were evaluated for their reaction to the leaf rust at both seedling and adult plant stages. To improve QTL identification, F2-derived F3 families were studied for resistance to leaf rust in two independent experiments. Two major genomic regions involved in resistance to leaf rust were detected.
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Baker, Peter John. "Applied Bayesian modelling in genetics." Thesis, Queensland University of Technology, 2001.
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Leaf, Robert Thomas. "The Evolutionary Effects of Fishing: Implications for Stock Management and Rebuilding." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28636.
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Recent empirical studies have demonstrated inter-generational morphological and life-history
changes in fish stocks that have been impacted by size-selective harvest. Evolutionary processes
in biological populations occur through differential survival and reproductive success based, in
part, upon individual phenotypic variability. Fishing is a source of directional selection resulting
in the directed removal of some phenotypes; however, many aspects of the evolutionary effects
of fishing remain have yet to be described. In order to better understand the life-history and
morphological changes that occur as a result of size-selective fishing, and their effect on fishery
dynamics, I first determined the suitability of Japanese medaka (Oryzias latipes) for selection
experiments. I performed selection experiments using Japanese medaka and report how
morphology and life-history characteristics changed over multiple generations of selection. I
then used these patterns of change in life-history and morphology to validate individual-based
simulation candidate models to test general mechanisms of life-history relationships. Finally, I
applied the individual-based simulation modeling approach in order to describe how biological
and fishery characteristics change in a large, age-structured population exposed to size-selective
fishing over multiple generations. I found that the Japanese medaka has attractive characteristics
for biological investigation. The selection experiments indicated large changes in the age-atmaturity,
including a nearly 50% decrease over four generations in the most intense sizeselective
removal regimes. However, I did not observe significant changes in length-at-age or
weight-at-age over the course of the experiment. Candidate simulation models were poor at
predicting some aspects of the life-history characteristics of Japanese medaka. The simulation
model to determine fishery characteristics predicted large decreases in yield and egg production
as a result of decreases in length-at-age. Understanding the relationships of life-history
characteristics and their role in determining population resilience is a step toward understanding
the importance of evolutionary processes in fishery management.Ph. D.
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Baldoni, Pedro Luiz 1989. "Modelos lineares generalizados mistos multivariados para caracterização genética de doenças." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307180.
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Orientador: Hildete Prisco PinheiroDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação
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Resumo: Os Modelos Lineares Generalizados Mistos (MLGM) são uma generalização natural dos Modelos Lineares Mistos (MLM) e dos Modelos Lineares Generalizados (MLG). A classe dos MLGM estende a suposição de normalidade dos dados permitindo o uso de várias outras distribuições bem como acomoda a superdispersão frequentemente observada e também a correlação existente entre observações em estudos longitudiais ou com medidas repetidas. Entretanto, a teoria de verossimilhança para MLGM não é imediata uma vez que a função de verossimilhança marginal não possui forma fechada e envolve integrais de alta dimensão. Para solucionar este problema, diversas metodologias foram propostas na literatura, desde técnicas clássicas como quadraturas numéricas, por exemplo, até métodos sofisticados envolvendo algoritmo EM, métodos MCMC e quase-verossimilhança penalizada. Tais metodologias possuem vantagens e desvantagens que devem ser avaliadas em cada tipo de problema. Neste trabalho, o método de quase-verossimilhança penalizada (\cite{breslow1993approximate}) foi utilizado para modelar dados de ocorrência de doença em uma população de vacas leiteiras pois demonstrou ser robusto aos problemas encontrados na teoria de verossimilhança deste conjunto de dados. Além disto, os demais métodos não se mostram calculáveis frente à complexidade dos problemas existentes em genética quantitativa. Adicionalmente, estudos de simulação são apresentados para verificar a robustez de tal metodologia. A estabilidade dos estimadores e a teoria de robustez para este problema não estão completamente desenvolvidos na literatura
Abstract: Generalized Linear Mixed Models (GLMM) are a generalization of Linear Mixed Models (LMM) and of Generalized Linear Models (GLM). The class of models GLMM extends the normality assumption of the data and allows the use of several other probability distributions, for example, accommodating the over dispersion often observed and also the correlation among observations in longitudinal or repeated measures studies. However, the likelihood theory of the GLMM class is not straightforward since its likelihood function has not closed form and involves a high order dimensional integral. In order to solve this problem, several methodologies were proposed in the literature, from classical techniques as numerical quadrature¿s, for example, up to sophisticated methods involving EM algorithm, MCMC methods and penalized quasi-likelihood. These methods have advantages and disadvantages that must be evaluated in each problem. In this work, the penalized quasi-likelihood method (\cite{breslow1993approximate}) was used to model infection data in a population of dairy cattle because demonstrated to be robust in the problems faced in the likelihood theory of this data. Moreover, the other methods do not show to be treatable faced to the complexity existing in quantitative genetics. Additionally, simulation studies are presented in order to verify the robustness of this methodology. The stability of these estimators and the robust theory of this problem are not completely studied in the literature
Mestrado
Estatistica
Mestre em Estatística
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Coffman, Valerie Chest. "Determining Molecular Mechanisms of Cell Division in Fission Yeast by Testing Major Assumptions of the Search, Capture, Pull, and Release Model of Contractile-Ring Assembly." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366202358.
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Santure, Anna Wensley, and n/a. "Quantitative genetic models for genomic imprinting." University of Otago. Department of Zoology, 2006. http://adt.otago.ac.nz./public/adt-NZDU20060811.134008.
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A gene is imprinted when its expression is dependent on the sex of the parent from which it was inherited. An increasing number of studies are suggesting that imprinted genes have a major influence on medically, agriculturally and evolutionarily important traits, such as disease severity and livestock production traits. While some genes have a large effect on the traits of an individual, quantitative characters such as height are influenced by many genes and by the environment, including maternal effects. The interaction between these genes and the environment produces variation in the characteristics of individuals. Many quantitative characters are likely to be influenced by a small number of imprinted genes, but at present there is no general theoretical model of the quantitative genetics of imprinting incorporating multiple loci, environmental effects and maternal effects. This research develops models for the quantitative genetics of imprinting incorporating these effects, including deriving expressions for genetic variation and resemblances between relatives. Imprinting introduces both parent-of-origin and generation dependent differences in the derivation of standard quantitative genetic models that are generally equivalent under Mendelian expression. Further, factors such as epistasis, maternal effects and interactions between genotype and environment may mask the effect of imprinting in a quantitative trait. Maternal effects may also mimic a number of signatures in variance and covariance components that are expected in a population with genomic imprinting. This research allows a more comprehensive understanding of the processes influencing an individual�s characteristics.
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Cerqueira, Pedro Henrique Ramos. "Structural equation models applied to quantitative genetics." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-145419/.
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Causal models have been used in different areas of knowledge in order to comprehend the causal associations between variables. Over the past decades, the amount of studies using these models have been growing a lot, especially those related to biological systems where studying and learning causal relationships among traits are essential for predicting the consequences of interventions in such system. Graph analysis (GA) and structural equation modeling (SEM) are tools used to explore such associations. While GA allows searching causal structures that express qualitatively how variables are causally connected, fitting SEM with a known causal structure allows to infer the magnitude of causal effects. Also SEM can be viewed as multiple regression models in which response variables can be explanatory variables for others. In quantitative genetics studies, SEM aimed to study the direct and indirect genetic effects associated to individuals through information related to them, beyond the observed characteristics, such as the kinship relations. In those studies typically the assumptions of linear relationships among traits are made. However, in some scenarios, nonlinear relationships can be observed, which make unsuitable the mentioned assumptions. To overcome this limitation, this paper proposes to use a mixed effects polynomial structural equation model, second or superior degree, to model those nonlinear relationships. Two studies were developed, a simulation and an application to real data. The first study involved simulation of 50 data sets, with a fully recursive causal structure involving three characteristics in which linear and nonlinear causal relations between them were allowed. The second study involved the analysis of traits related to dairy cows of the Holstein breed. Phenotypic relationships between traits were calving difficulty, gestation length and also the proportion of perionatal death. We compare the model of multiple traits and polynomials structural equations models, under different polynomials degrees in order to assess the benefits of the SEM polynomial of second or higher degree. For some situations the inappropriate assumption of linearity results in poor predictions of the direct, indirect and total of the genetic variances and covariance, either overestimating, underestimating, or even assign opposite signs to covariances. Therefore, we conclude that the inclusion of a polynomial degree increases the SEM expressive power.Modelos causais têm sido muitos utilizados em estudos em diferentes áreas de conhecimento, a fim de compreender as associações ou relações causais entre variáveis. Durante as últimas décadas, o uso desses modelos têm crescido muito, especialmente estudos relacionados à sistemas biológicos, uma vez que compreender as relações entre características são essenciais para prever quais são as consequências de intervenções em tais sistemas. Análise do grafo (AG) e os modelos de equações estruturais (MEE) são utilizados como ferramentas para explorar essas relações. Enquanto AG nos permite buscar por estruturas causais, que representam qualitativamente como as variáveis são causalmente conectadas, ajustando o MEE com uma estrutura causal conhecida nos permite inferir a magnitude dos efeitos causais. Os MEE também podem ser vistos como modelos de regressão múltipla em que uma variável resposta pode ser vista como explanatória para uma outra característica. Estudos utilizando MEE em genética quantitativa visam estudar os efeitos genéticos diretos e indiretos associados aos indivíduos por meio de informações realcionadas aos indivíduas, além das característcas observadas, como por exemplo o parentesco entre eles. Neste contexto, é tipicamente adotada a suposição que as características observadas são relacionadas linearmente. No entanto, para alguns cenários, relações não lineares são observadas, o que torna as suposições mencionadas inadequadas. Para superar essa limitação, este trabalho propõe o uso de modelos de equações estruturais de efeitos polinomiais mistos, de segundo grau ou seperior, para modelar relações não lineares. Neste trabalho foram desenvolvidos dois estudos, um de simulação e uma aplicação a dados reais. O primeiro estudo envolveu a simulação de 50 conjuntos de dados, com uma estrutura causal completamente recursiva, envolvendo 3 características, em que foram permitidas relações causais lineares e não lineares entre as mesmas. O segundo estudo envolveu a análise de características relacionadas ao gado leiteiro da raça Holandesa, foram utilizadas relações entre os seguintes fenótipos: dificuldade de parto, duração da gestação e a proporção de morte perionatal. Nós comparamos o modelo misto de múltiplas características com os modelos de equações estruturais polinomiais, com diferentes graus polinomiais, a fim de verificar os benefícios do MEE polinomial de segundo grau ou superior. Para algumas situações a suposição inapropriada de linearidade resulta em previsões pobres das variâncias e covariâncias genéticas diretas, indiretas e totais, seja por superestimar, subestimar, ou mesmo atribuir sinais opostos as covariâncias. Portanto, verificamos que a inclusão de um grau de polinômio aumenta o poder de expressão do MEE.
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Barros, Matheus Souza de. "Progresso genético para produção de grãos obtido em doze anos de melhoramento da população elite de arroz de terras altas." Universidade Federal de Goiás, 2015. http://repositorio.bc.ufg.br/tede/handle/tede/7167.
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The genetic improvement resulted from plant breeding acts decisively in maintaining the supply of agricultural foods like rice. The contribution of this genetic improvement to increase productivity is expressed in many crops by genetic progress which represents the genetic changes in the course of the selection cycles, and promotes the advance of genotypic average towards selection. Among the strategies adopted to increase the gain by selection, the early generation selection proves to be promising. This work has aimed to evaluate the genetic potential for selecting upland rice progenies and estimate the genetic progress for grain yield. The data used in this study were obtained from the progeny yield trials conducted in the period of eleven agricultural years 2002/03 to 2012/13 conducted by Embrapa Rice and Beans. The traits analyzed were grain yield (kg ha-1), plant height (cm) and days to flowering (day). In each year of the experiment, a group of progeny was tested in four to six sites. It was used Federer's augmented block design without replication per site in seven years and with at least three checks, in four years of the series were used two replications. The experimental data within each year were submitted to joint analysis. A mixedeffects linear model was applied for estimating the components of variance by the method of restricted maximum likelihood (REML). From this estimate of the components, it was calculated the genetic and phenotypic parameters, in addition the selective accuracy, the experimental precision coefficient, the experimental variation coefficient and relative variation coefficient. The genetic progress was estimated by the method of generalized linear regression of the adjusted means of progeny groups evaluated in each year by the mixed model approach. The estimates of the relative annual mean gain and the total relative gain for the three studied traits were also obtained. The estimates of genetic variance among progenies for grain yield were highly significant (p < 0.001), except for the progeny group evaluated in 2007. The heritability estimation ranging from 0.22 to 0.69 that, associated with the selective accuracy, indicates the expected level of efficiency with early generation selection in each group of progenies. For Plant height and daysto- flowering, the genetic variance estimates were significant (p ≤ 0.01) in all groups. The variance components for these traits led to a rather high heritability estimation that suggests favorable conditions for selection in early generations. The genetic progress for grain yield (80.5 kg ha-1 yr-1) was highly significant. This value represents a relative annual mean gain of 2.88%. Throughout the period, the cumulative gain was estimated in 32.86% which indicates an increase of 918 kg ha-1 for grain yield. The response for plant height was not significant, suggesting that the height of progenies remained stable over the period. For days-to-flowering, it was detected significant increase in cycle length, indicated by the cumulative increase of the vegetative period in about five days (6.73%). From these results we conclude that early generation selection, adopted by the breeding program, were effective in promoting the genetic gain for grain yield in the elite populations.
O melhoramento genético de plantas atua de modo decisivo na manutenção da oferta de alimentos de origem agrícola como o arroz. A contribuição do melhoramento para o aumento da produtividade em várias culturas é expressa pelo progresso genético, que representa as alterações genéticas, no decorrer dos ciclos seletivos, promovendo o deslocamento da média genotípica do caráter no sentido da seleção. Entre várias estratégias adotadas para aumentar os ganhos com a seleção merece destaque a seleção precoce, que envolve a avaliação de progênies endogâmicas nas gerações F3 ou F4. Este trabalho teve como objetivo avaliar o potencial genético para a seleção em progênies de arroz de terras altas e estimar o progresso genético para produção de grãos. Foram utilizados dados dos ensaios de rendimento de progênies conduzidos no período de onze anos agrícolas, 2002/03 a 2012/13 pela Embrapa Arroz e Feijão. Foram analisados os caracteres produção de grãos (kg.ha-1), altura de plantas (cm) e dias para a floração (dia). Em cada ano da série um grupo de progênies foi testado em experimentos instalados entre quatro a seis locais. Foi empregado o delineamento blocos aumentados de Federer em sete anos da série sem repetição por local e com no mínimo três testemunhas, e em quatro anos os ensaios foram duplicados. Os dados foram submetidos à análise conjunta dos experimentos dentro de cada ano. Por meio de um modelo linear de efeitos mistos foram estimados os componentes de variância pelo método da máxima verossimilhança restrita ou residual (REML). A partir da estimativa dos componentes foram calculados os parâmetros genéticos e fenotípicos. O progresso genético foi estimado pelo método da regressão linear generalizada das médias ajustadas dos grupos de progênies avaliadas em cada ano, pela abordagem de modelos mistos. Foram obtidas as estimativas do ganho médio relativo anual e do ganho relativo total. As estimativas de variância genética, para produção de grãos, entre progênies foram altamente significativas (p<0,001), exceto pelo grupo de progênie avaliado em 2007. As estimativas de herdabilidade variaram de 0,22 a 0,69, que associadas às estimativas de acurácia seletiva indicam o nível de eficiência esperado com a seleção precoce em cada grupo de progênies. Para os caracteres altura de plantas e dias para floração as estimativas de variância genética foram significativas (p≤0,01) em todos os grupos. Os componentes de variância para esses caracteres conduziram a estimativas de herdabilidade bastante elevadas, sugerindo, por tanto, condições favoráveis para seleção em gerações iniciais. O progresso genético estimado para produção de grãos (80,5 kg.ha-1ano-1) foi altamente significativo, representando um ganho relativo médio anual de 2,88%. Em todo o período o ganho acumulado estimado foi de 32,86%, que equivale ao incremento em produtividade de 918 kg ha-1. A resposta para altura de plantas não foi significativa, sugerindo que a estatura das progênies avaliadas permaneceu estável ao longo do período. Para dias para floração houve aumento significativo na duração do ciclo, expresso pelo acréscimo acumulado de aproximadamente cinco dias (6,73%) na duração do ciclo vegetativo. Conclui-se que a estratégia de seleção precoce, adotada pelo programa de melhoramento, foi eficiente em promover o progresso genético para o caráter produção de grãos nas populações elites.
Books on the topic "Quantitative Genetics Model"
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Silson, Roy G. A predictive additive model for quantitative genetics: Principles and results. Tring: Greenfield, 1993.
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Silson, Roy G. Additive gene systems: An explanation for problems in evolution and selection. Herts: Greenfield, 1988.
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1955-, Banzhaf Wolfgang, and Eeckman Frank H, eds. Evolution and biocomputation: Computational models of evolution. Berlin: Springer, 1995.
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E, Tollefson Ann, ed. Adenovirus Methods and Protocols: Volume 1: Adenoviruses, Ad Vectors, Quantitation, and Animal Models. Totowa, NJ: Humana Press, 2007.
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Jarnecke, Amber M., and Susan C. South. Behavior and Molecular Genetics of the Five Factor Model. Edited by Thomas A. Widiger. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199352487.013.25.
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Behavior and molecular genetics informs knowledge of the etiology, structure, and development of the Five Factor Model (FFM) of personality. Behavior genetics uses quantitative modeling to parse the relative influence of nature and nurture on phenotypes that vary within the population. Behavior genetics research on the FFM has demonstrated that each domain has a heritability (proportion of variation due to genetic influences) of 40–50%. Molecular genetic methods attempt to identify specific genetic mechanisms associated with personality variation. To date, findings from molecular genetics are tentative, with significant results failing to replicate and accounting for only a small percentage of the variance. However, newer techniques hold promise for finding the “missing heritability” of FFM and related personality domains. This chapter presents an overview of commonly used behavior and molecular genetic techniques, reviews the work that has been done on the FFM domains and facets, and offers a perspective for future directions.
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Walsh, Bruce, and Michael Lynch. The Infinitesimal Model and Its Extensions. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0024.
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One standard approximation in quantitative genetics is the infinitesimal model, which assumes a large number of loci, each of small effect. In such a setting, the distribution of breeding values in unselected descendants is roughly multivariate normal and most of the (short-term) change in the additive variance under selection is through Bulmer effects (the generation of linkage disequilibrium) rather than by allele-frequency change. A variety of different infinitesimal models are found in the literature, and this chapter examines these different versions and the connections between them. It also examines the theory for moving beyond the infinitesimal approximation. Finally, this chapter shows that the much-debated worry over “missing heritability” simply follows under the infinitesimal setting.
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Quantitative Genetics in the Wild. Oxford University Press, 2014.
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Charmantier, Anne, Dany Garant, and Loeske E. B. Kruuk. Quantitative Genetics in the Wild. Oxford University Press, 2014.
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Walsh, Bruce, and Michael Lynch. Maintenance of Quantitative Genetic Variation. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0028.
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One of the major unresolved issues in quantitative genetics is what accounts for the amount of standing genetic variation in traits. A wide range of models, all reviewed in this chapter, have been proposed, but none fit the data, either giving too much variation or too little apparent stabilizing selection.
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Walsh, Bruce, and Michael Lynch. Evolution and Selection of Quantitative Traits. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.001.0001.
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Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.
Book chapters on the topic "Quantitative Genetics Model"
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Xu, Shizhong. "Mixed Model Analysis of Genetic Variances." In Quantitative Genetics, 195–213. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6_12.
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Lyons, P. A., and L. S. Wicker. "Localising Quantitative Trait Loci in the NOD Mouse Model of Type 1 Diabetes." In Genes and Genetics of Autoimmunity, 208–25. Basel: KARGER, 1999. http://dx.doi.org/10.1159/000060488.
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Hall, Brian K. "A Quantitative Genetics Model for Morphological Change in Development and Evolution." In Evolutionary Developmental Biology, 321–32. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-3961-8_20.
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Morota, Gota, Diego Jarquin, Malachy T. Campbell, and Hiroyoshi Iwata. "Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data." In Methods in Molecular Biology, 269–96. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2537-8_21.
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AbstractThe advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new technologies also bring new challenges in quantitative genetics, namely, a need for the development of robust frameworks that can accommodate these high-dimensional data. In this chapter, we describe methods for the statistical analysis of high-throughput phenotyping (HTP) data with the goal of enhancing the prediction accuracy of genomic selection (GS). Following the Introduction in Sec. 1, Sec. 2 discusses field-based HTP, including the use of unoccupied aerial vehicles and light detection and ranging, as well as how we can achieve increased genetic gain by utilizing image data derived from HTP. Section 3 considers extending commonly used GS models to integrate HTP data as covariates associated with the principal trait response, such as yield. Particular focus is placed on single-trait, multi-trait, and genotype by environment interaction models. One unique aspect of HTP data is that phenomics platforms often produce large-scale data with high spatial and temporal resolution for capturing dynamic growth, development, and stress responses. Section 4 discusses the utility of a random regression model for performing longitudinal modeling. The chapter concludes with a discussion of some standing issues.
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Bürger, Reinhard. "Dynamical Models in Quantitative Genetics." In Lecture Notes in Economics and Mathematical Systems, 75–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-662-00545-3_7.
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Dawid, Herbert, Karl Doerner, Richard F. Hartl, Marc Reimann, Georg Dorffner, Thomas Fent, Markus Feurstein, Andreas Mild, Martin Natter, and Alfred Taudes. "Genetic-based machine learning." In Quantitative Models of Learning Organizations, 23–46. Vienna: Springer Vienna, 2002. http://dx.doi.org/10.1007/978-3-7091-6158-6_3.
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Gabriel, W. "Quantitative Genetic Models for Parthenogenetic Species." In Population Genetics and Evolution, 73–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73069-6_8.
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Gianola, D. "Inferences from Mixed Models in Quantitative Genetics." In Handbook of Statistical Genetics, 678–717. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch20.
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Zonta, L. A., and S. D. Jayakar. "Models of Fluctuating Selection for a Quantitative Trait." In Population Genetics and Evolution, 102–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73069-6_11.
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Hill, J., H. C. Becker, and P. M. A. Tigerstedt. "Genetic models and their predictive value." In Quantitative and Ecological Aspects of Plant Breeding, 17–66. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5830-5_2.
Full textConference papers on the topic "Quantitative Genetics Model"
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Neophytou, Katerina, Christos A. Nicolaou, Constantinos S. Pattichis, and Christos N. Schizas. "Deriving Quantitative Structure-Activity Relationship Models Using Genetic Programming for Drug Discovery." In 6th International Special Topic Conference on Information Technology Applications in Biomedicine, 2007. IEEE, 2007. http://dx.doi.org/10.1109/itab.2007.4407401.
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Soltani, Mohsen Reza, Hiwa Khaledi, Mohammad Bagher Ghofrani, and Amir Abbas Rezaei. "Optimum Design and Sensitivity Analysis of Axial Flow Compressor With Combination of Analytical Method, Qualitative and Quantitative Rules and Genetic Algorithm." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51033.
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Simulation and prediction of gas turbine performance is a very important issue in design process or in actual behavior analysis. In these models physical behavior of components such as compressors, combustion chambers and turbines are simulated related to each other. The compressor is the most important part of simulation. This paper presents a model for simulating a compressor using stage stacking procedure with the aid of a genetic algorithm. The most important feature of the proposed method is that qualitative and quantitative rules based on turbo-machinery knowledge of compressors are used as constraints to the genetic algorithm to find the corrected situations of design. This knowledge is evaluated with both industrial and aero gas turbine engines (501F & CF6 (LM2500)). The model is based on an analytical solution and provides an insight into the effects of choices made during the compressor design process on performance and off-design stage matching. The results of the model highlight the capability of the method which accurately reproduces the available data. In addition to obtaining design conditions, this model can find and calculate stages that are highly loaded and this information is vital to control the compressor.
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Peng, Jiang-Tao, Hai-Yan Wang, An Jiang, Qi-Wei Xie, and Huai-Song Wang. "Quantitative calibration model for Infrared spectroscopy using continuous wavelet transform combined with genetic algorithm." In 2012 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2012. http://dx.doi.org/10.1109/icwapr.2012.6294791.
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Ma, Yong-guang, Jian-qiang Gao, Liang-yu Ma, Qin Yan, and Peng Tong. "Study on Fault Diagnosis Based on the Qualitative / Quantitative Model of SDG and Genetic Algorithm." In 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258342.
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Occhipinti, Annalisa, and Claudio Angione. "A Computational Model of Cancer Metabolism for Personalised Medicine." In Building Bridges in Medical Science 2021. Cambridge Medicine Journal, 2021. http://dx.doi.org/10.7244/cmj.2021.03.001.3.
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Cancer cells must rewrite their ‘‘internal code’’ to satisfy the demand for growth and proliferation. Such changes are driven by a combination of genetic (e.g., genes’ mutations) and non-genetic factors (e.g., tumour microenvironment) that result in an alteration of cellular metabolism. For this reason, understanding the metabolic and genomic changes of a cancer cell can provide useful insight on cancer progression and survival outcomes. In our work, we present a computational framework that uses patient-specific data to investigate cancer metabolism and provide personalised survival predictions and cancer development outcomes. The proposed model integrates patient-specific multi-omics data (i.e., genomic, metabolomic and clinical data) into a metabolic model of cancer to produce a list of metabolic reactions affecting cancer progression. Quantitative and predictive analysis, through survival analysis and machine learning techniques, is then performed on the list of selected reactions. Since our model performs an analysis of patient-specific data, the outcome of our pipeline provides a personalised prediction of survival outcome and cancer development based on a subset of identified multi-omics features (genomic, metabolomic and clinical data). In particular, our work aims to develop a computational pipeline for clinicians that relates the omic profile of each patient to their survival probability, based on a combination of machine learning and metabolic modelling techniques. The model provides patient-specific predictions on cancer development and survival outcomes towards the development of personalised medicine.
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Ismail, Mohamed A., Attia H. Gomaa, and Ashraf O. Nassef. "Solving the Multi-Objective Facility Layout Problem Using Evolutionary Multi-Objective Optimization Algorithms." In ASME 2006 International Manufacturing Science and Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/msec2006-21067.
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The multi-objective facility layout problem is defined in the literature as an extension of the famous quadratic assignment problem (QAP). Most previous mathematical models tried to combine both the quantitative and the qualitative objectives into a single objective by using weighting factors. This paper introduces a multi-objective mathematical model and solves it using the revised Strength Pareto Evolutionary Algorithm (SPEAII). The purpose of this paper is to find an efficient set of solutions “Pareto optimal set” which could be introduced to the decision maker to select the best alternative, while considering conflicting and noncommensurate objectives. A computer program is developed to define the mathematical model, code candidate solutions into genetic form, and use Evolutionary Multi-Objective Optimization algorithms (EMO) to find the efficient set of solutions. The problem model is built according to its customized data input. The suggested model and solution algorithms are applied to a wide set of different benchmark problems. Results showed the superiority of the suggested models and algorithms in terms of the quality of solution and objective space exploration.
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Orta, Adil Han, Shain Azadi, Saeid Hedayatrasa, Nicolaas Bernardus Roozen, Wim Van Paepegem, Mathias Kersemans, and Koen Van Den Abeele. "Identification of the Orthotropic Elastic Tensor of Composites Using Full Field Lamb Wave Energy Velocities and Dispersion Curves." In 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/qnde2021-75067.
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Abstract A multi-objective inversion procedure is proposed based on 3D Lamb wave dispersion curves and energy velocity matching to identify the elastic stiffness tensor of orthotropic composite plates. To validate the procedure, finite element model simulations and experimental measurements have been conducted on an aluminum and a composite plate by using piezoelectric actuator broadband signals. Experimentally, the in-plane and out-of-plane velocity components on the surface of these plates were measured using a 3D Infrared Scanning Laser Doppler Vibrometer. By exploiting Fourier Transform, the measured space-time domain data is converted into the frequency-wavenumber domain, from which dispersion curves are extracted. To identify the energy velocity, Short Time Fourier Transform and linear Radon transformation have been applied. Then, image processing is used both for dispersion and energy velocity curves to match the amplitude of the in-plane and out-of-plane velocities on the surface of the plate. The Semi Analytical Finite Element method (SAFE) was selected as the forward model to be embedded in an inversion algorithm due to its accuracy and robustness. Using a multi-objective genetic algorithm, the elastic tensor is calculated by simultaneously minimizing the error between (i) the measured and calculated dispersion curves on one hand, and (ii) the measured and calculated energy velocity slowness curves on the other hand for every in and out of plane velocity measurement. The mean values of the pareto front are selected as optimum parameters. The reconstructed elastic stiffness properties show good agreement with less than 6% average deviation.
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Zhou, Yu, Chen Xuedong, Zhichao Fan, and Han Yichun. "An Improved Mechanism-Based Creep Constitutive Model Using Stress-Dependent Creep Ductility." In ASME 2016 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/pvp2016-63447.
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Creep ductility which is assumed to be constant at a given temperature in many creep constitutive models, actually varies with temperature, stress level and creep strain rate, etc. In this paper, the relationship between creep ductility and stress levels of ferritic steels has been briefly discussed from the perspective of failure mechanisms. It can be generally divided into three regimes, including the upper shelf, lower shelf and the transition regime. The four-parameter logistic model has been adopted to quantitatively describe the stress-dependent creep ductility. Furthermore, a modified mechanism-based continuum damage mechanics (CDM) model for ferrtic steels has been proposed using the stress-dependent creep ductility model. Uniaxial creep tests of 2.25Cr1Mo0.25V steel at three stress levels have been carried out and the experimental data points realistically reflecting the creep behavior have been carefully selected to fit the improved CDM model using genetic algorithm (GA). It is shown that the improved model has the capability to characterize the whole creep process of ferritic steels and the stress-dependent creep ductility over a wide range of applied stress.
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Jin, Mohui, Xianmin Zhang, and Benliang Zhu. "Design of Compliant Mechanisms Using a Pseudo-Rigid-Body Model Based Topology Optimization Method." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34325.
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This paper presents a novel method for the topological synthesis of flexure-based compliant mechanisms. Such kind of mechanisms are usually obtained by replacing the kinematic pairs of existing rigid-body mechanisms with flexure hinges, which is often regarded as the rigid-body replacement approach. This approach uses the topologies from rigid-body mechanism and pays little attention to the selection of the optimal topology among them. The proposed method tries to find out the optimal topology directly from design problem, without referencing to the existing rigid-body mechanisms. The topology of the flexure-based compliant mechanisms is represented by the pseudo-rigid-body model (PRBM). The PRBM is expressed in a ground structure using an adjacency matrix. An analysis method based on the principle of minimum potential energy is introduced to evaluate the static performance of the PRBM candidates quantitatively. Using genetic algorithm (GA), the optimal PRBM can be found out according to the objective function that is based on the analysis results. The validity of the proposed method is tested on a single-input-output compliant mechanism design problem.
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Lawson, Michael J., Ye Li, and Danny C. Sale. "Development and Verification of a Computational Fluid Dynamics Model of a Horizontal-Axis Tidal Current Turbine." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-49863.
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This paper describes the development of a computational fluid dynamics (CFD) methodology to simulate the hydrodynamics of horizontal-axis tidal current turbines (HATTs). First, an HATT blade was designed using the blade element momentum method in conjunction with a genetic optimization algorithm. Several unstructured computational grids were generated using this blade geometry and steady CFD simulations were used to perform a grid resolution study. Transient simulations were then performed to determine the effect of time-dependent flow phenomena and the size of the computational timestep on the numerical solution. Qualitative measures of the CFD solutions were independent of the grid resolution. Conversely, quantitative comparisons of the results indicated that the use of coarse computational grids results in an under prediction of the hydrodynamic forces on the turbine blade in comparison to the forces predicted using more resolved grids. For the turbine operating conditions considered in this study, the effect of the computational timestep on the CFD solution was found to be minimal, and the results from steady and transient simulations were in good agreement. Additionally, the CFD results were compared to corresponding blade element momentum method calculations and reasonable agreement was shown. Nevertheless, we expect that for other turbine operating conditions, where the flow over the blade is separated, transient simulations will be required.
Reports on the topic "Quantitative Genetics Model"
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Zhang, Hongbin B., David J. Bonfil, and Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, March 2003. http://dx.doi.org/10.32747/2003.7586464.bard.
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The goals of this project were to develop essential genomic tools for modern chickpea genetics and genomics research, map the genes and quantitative traits of importance to chickpea production and generate DNA markers that are well-suited for enhanced chickpea germplasm analysis and breeding. To achieve these research goals, we proposed the following research objectives in this period of the project: 1) Develop an ordered BAC library with an average insert size of 150 - 200 kb (USA); 2) Develop 300 simple sequence repeat (SSR) markers with an aid of the BAC library (USA); 3) Develop SSR marker tags for Ascochyta response, flowering date and grain weight (USA); 4) Develop a molecular genetic map consisting of at least 200 SSR markers (Israel and USA); 5) Map genes and QTLs most important to chickpea production in the U.S. and Israel: Ascochyta response, flowering and seed set date, grain weight, and grain yield under extreme dryland conditions (Israel); and 6) Determine the genetic correlation between the above four traits (Israel). Chickpea is the third most important pulse crop in the world and ranks the first in the Middle East. Chickpea seeds are a good source of plant protein (12.4-31.5%) and carbohydrates (52.4-70.9%). Although it has been demonstrated in other major crops that the modern genetics and genomics research is essential to enhance our capacity for crop genetic improvement and breeding, little work was pursued in these research areas for chickpea. It was absent in resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. For instance, there were no large-insert BAC and BIBAC libraries, no sufficient and user- friendly DNA markers, and no intraspecific genetic map. Grain sizes, flowering time and Ascochyta response are three main constraints to chickpea production in drylands. Combination of large seeds, early flowering time and Ascochyta blight resistance is desirable and of significance for further genetic improvement of chickpea. However, it was unknown how many genes and/or loci contribute to each of the traits and what correlations occur among them, making breeders difficult to combine these desirable traits. In this period of the project, we developed the resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. In particular, we constructed the proposed large-insert BAC library and an additional plant-transformation-competent BIBAC library from an Israeli advanced chickpea cultivar, Hadas. The BAC library contains 30,720 clones and has an average insert size of 151 kb, equivalent to 6.3 x chickpea haploid genomes. The BIBAC library contains 18,432 clones and has an average insert size of 135 kb, equivalent to 3.4 x chickpea haploid genomes. The combined libraries contain 49,152 clones, equivalent to 10.7 x chickpea haploid genomes. We identified all SSR loci-containing clones from the chickpea BAC library, generated sequences for 536 SSR loci from a part of the SSR-containing BACs and developed 310 new SSR markers. From the new SSR markers and selected existing SSR markers, we developed a SSR marker-based molecular genetic map of the chickpea genome. The BAC and BIBAC libraries, SSR markers and the molecular genetic map have provided essential resources and tools for modern genetic and genomic analyses of the chickpea genome. Using the SSR markers and genetic map, we mapped the genes and loci for flowering time and Ascochyta responses; one major QTL and a few minor QTLs have been identified for Ascochyta response and one major QTL has been identified for flowering time. The genetic correlations between flowering time, grain weight and Ascochyta response have been established. These results have provided essential tools and knowledge for effective manipulation and enhanced breeding of the traits in chickpea.
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Semerikov, Serhiy O., Illia O. Teplytskyi, Yuliia V. Yechkalo, and Arnold E. Kiv. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. [б. в.], November 2018. http://dx.doi.org/10.31812/123456789/2648.
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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890-1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). The role of Walter Pitts in combining the descriptive and quantitative theories of training is discussed. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. It is indicated that there are three groups of models, which are promising in terms of developing corresponding methods – the continuous two-factor model of Rashevsky, the discrete model of McCulloch and Pitts, and the discrete-continuous models of Householder and Landahl.
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Tanksley, Steven D., and Dani Zamir. Development and Testing of a Method for the Systematic Discovery and Utilization of Novel QTLs in the Production of Improved Crop Varieties: Tomato as a Model System. United States Department of Agriculture, June 1995. http://dx.doi.org/10.32747/1995.7570570.bard.
Full textAbstract:
Modern cultivated varieties carry only a small fraction of the variation present in the gene pool. The narrow genetic basis of modern crop plants is a result of genetic bottlenecks imposed during early domestication and modern plant breeding. The wild ancestors of most crop plants can still be found in their natural habitats and Germplasm Centers have been established to collect and maintain this material. These wild and unadapted resources can potentially fuel crop plant improvement efforts for many years into the future (Tanksley and McCouch 1997). Unfortunately, scientists have been unable to exploit the majority of the genetic potential warehoused in germplasm repositories. This is especially true as regards to the improvement of quantitative traits like yield and quality. One of the major problems is that much of the wild germplasm is inferior to modern cultivars for many of the quantitative traits that breeders would like to improve. Our research, focusing on the tomato as a model system, has shown that despite their inferior phenotypes, wild species are likely to contain QTLs that can substantially increase the yield and quality of elite cultivars (de Vicente and Tanksley 1992, Eshed and Zamir 1994, Eshed et al. 1996). Using novel population structures of introgression lines (ILs; Eshed and Zamir 1995) and advanced backcross lines (AB; Tanksley et al. 1996) we identified and introduced valuable QTLs from unadapted germplasm into elite processing tomato varieties. Populations involving crosses with five Lycopersicon species (L. pennellii (Eshed and Zamir 1994; Eshed et al. 1996; Eshed and Zamir 1996), L. hirsutum (Bernacchi et al. 1998), L. pimpinellifolium (Tanksley et al. 1996), L. parviflorum (unpub.), L. peruvianum (Fulton et al. 1997) have been field and laboratory tested in a number of locations around the world. QTLs from the wild parent were identified that improve one or more of the key quantitative traits for processing tomatoes (yield, brix, sugar and acid composition and earliness) by as much as 10-30%. Nearly isogenic lines (QTL-NILs) have been generated for a subset of these QTLs. Each QTL-NIL contains the entire genome of the elite cultivated parent except for a segment (5-40 cM) of the wild species genome corresponding to a specific QTL. The genetic material and information that was developed in this program is presently used by American and Israeli seed companies for the breeding of superior varieties. We expect that in the next few years these varieties will make a difference in the marketplace.
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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.
Full textAbstract:
The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.
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Fallik, Elazar, Robert Joly, Ilan Paran, and Matthew A. Jenks. Study of the Physiological, Molecular and Genetic Factors Associated with Postharvest Water Loss in Pepper Fruit. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7593392.bard.
Full textAbstract:
The fruit of pepper (Capsicum annuum) commonly wilts (or shrivels) during postharvest storage due to rapid water loss, a condition that greatly reduces its shelf life and market value. The fact that pepper fruit are hollow, and thus have limited water content, only exacerbates this problem in pepper. The collaborators on this project completed research whose findings provided new insight into the genetic, physiological, and biochemical basis for water loss from the fruits of pepper (Capsicum annuum and related Capsicum species). Well-defined genetic populations of pepper were used in this study, the first being a series of backcross F₁ and segregating F₂, F₃, and F₄ populations derived from two original parents selected for having dramatic differences in fruit water loss rate (very high and very low water loss). The secondly population utilized in these studies was a collection of 50 accessions representing world diversity in both species and cultivar types. We found that an unexpectedly large amount of variation was present in both fruit wax and cutin composition in these collections. In addition, our studies revealed significant correlations between the chemical composition of both the fruit cuticular waxes and cutin monomers with fruit water loss rate. Among the most significant were that high alkane content in fruit waxes conferred low fruit water loss rates and low permeability in fruit cuticles. In contrast, high amounts of terpenoids (plus steroidal compounds) were associated with very high fruit water loss and cuticle permeability. These results are consistent with our models that the simple straight chain alkanes pack closely together in the cuticle membrane and obstruct water diffusion, whereas lipids with more complex 3-dimensional structure (such as terpenoids) do not pack so closely, and thus increase the diffusion pathways. The backcross segregating populations were used to map quantitative trait loci (QTLs) associated with water loss (using DART markers, Diversity Arrays Technology LTD). These studies resulted in identification of two linked QTLs on pepper’s chromosome 10. Although the exact genetic or physiological basis for these QTLs function in water loss is unknown, the genotypic contribution in studies of near-isogenic lines selected from these backcross populations reveals a strong association between certain wax compounds, the free fatty acids and iso-alkanes. There was also a lesser association between the water loss QTLs with both fruit firmness and total soluble sugars. Results of these analyses have revealed especially strong genetic linkages between fruit water loss, cuticle composition, and two QTLs on chromosome 10. These findings lead us to further speculate that genes located at or near these QTLs have a strong influence on cuticle lipids that impact water loss rate (and possibly, whether directly or indirectly, other traits like fruit firmness and sugar content). The QTL markers identified in these studies will be valuable in the breeding programs of scientists seeking to select for low water loss, long lasting fruits, of pepper, and likely the fruits of related commodities. Further work with these newly developed genetic resources should ultimately lead to the discovery of the genes controlling these fruit characteristics, allowing for the use of transgenic breeding approaches toward the improvement of fruit postharvest shelf life.
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Fridman, Eyal, Jianming Yu, and Rivka Elbaum. Combining diversity within Sorghum bicolor for genomic and fine mapping of intra-allelic interactions underlying heterosis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597925.bard.
Full textAbstract:
Heterosis, the enigmatic phenomenon in which whole genome heterozygous hybrids demonstrate superior fitness compared to their homozygous parents, is the main cornerstone of modern crop plant breeding. One explanation for this non-additive inheritance of hybrids is interaction of alleles within the same locus. This proposal aims at screening, identifying and investigating heterosis trait loci (HTL) for different yield traits by implementing a novel integrated mapping approach in Sorghum bicolor as a model for other crop plants. Originally, the general goal of this research was to perform a genetic dissection of heterosis in a diallel built from a set of Sorghum bicolor inbred lines. This was conducted by implementing a novel computational algorithm which aims at associating between specific heterozygosity found among hybrids with heterotic variation for different agronomic traits. The initial goals of the research are: (i) Perform genotype by sequencing (GBS) of the founder lines (ii) To evaluate the heterotic variation found in the diallel by performing field trails and measurements in the field (iii) To perform QTL analysis for identifying heterotic trait loci (HTL) (iv) to validate candidate HTL by testing the quantitative mode of inheritance in F2 populations, and (v) To identify candidate HTL in NAM founder lines and fine map these loci by test-cross selected RIL derived from these founders. The genetic mapping was initially achieved with app. 100 SSR markers, and later the founder lines were genotyped by sequencing. In addition to the original proposed research we have added two additional populations that were utilized to further develop the HTL mapping approach; (1) A diallel of budding yeast (Saccharomyces cerevisiae) that was tested for heterosis of doubling time, and (2) a recombinant inbred line population of Sorghum bicolor that allowed testing in the field and in more depth the contribution of heterosis to plant height, as well as to achieve novel simulation for predicting dominant and additive effects in tightly linked loci on pseudooverdominance. There are several conclusions relevant to crop plants in general and to sorghum breeding and biology in particular: (i) heterosis for reproductive (1), vegetative (2) and metabolic phenotypes is predominantly achieved via dominance complementation. (ii) most loci that seems to be inherited as overdominant are in fact achieving superior phenotype of the heterozygous due to linkage in repulsion, namely by pseudooverdominant mechanism. Our computer simulations show that such repulsion linkage could influence QTL detection and estimation of effect in segregating populations. (iii) A new height QTL (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 in sorghum, and its genetic dissection in RIL population demonstrated that it affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. (iv) HTL mapping for grain nitrogen content in sorghum grains has identified several candidate genes that regulate this trait, including several putative nitrate transporters and a transcription factor belonging to the no-apical meristem (NAC)-like large gene family. This activity was combined with another BARD-funded project in which several de-novo mutants in this gene were identified for functional analysis.
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Smith, Margaret, Nurit Katzir, Susan McCouch, and Yaakov Tadmor. Discovery and Transfer of Genes from Wild Zea Germplasm to Improve Grain Oil and Protein Composition of Temperate Maize. United States Department of Agriculture, 1998. http://dx.doi.org/10.32747/1998.7580683.bard.
Full textAbstract:
Project Objectives 1. Develop and amplify two interspecific populations (annual and perennial teosintes x elite maize inbred) as the basis for genetic analysis of grain quality. 2. Identify quantitative trait loci (QTLs) from teosinte that improve oil, protein, and essential amino acid composition of maize grain. 3. Develop near isogenic lines (NILs) to quantify QTL contributions to grain quality and as a resource for future breeding and gene cloning efforts. 4. Analyze the contribution of these QTLs to hybrid performance in both the US and Israel. 5. Measure the yield potential of improved grain quality hybrids. (NOTE: Yield potential could not be evaluated due to environmentally-caused failure of the breeding nursery where seed was produced for this evaluation.) Background: Maize is a significant agricultural commodity worldwide. As an open pollinated crop, variation within the species is large and, in most cases, sufficient to supply the demand for modem varieties and for new environments. In recent years there is a growing demand for maize varieties with special quality attributes. While domesticated sources of genetic variation for high oil and protein content are limited, useful alleles for these traits may remain in maize's wild relative, teosinte. We utilized advanced backcross (AB) analysis to search for QTLs contributing to oil and protein content from two teosinte accessions: Zea mays ssp. mexicana Race Chalco, an annual teosinte (referred to as Chalco), and Z diploperennis Race San Miguel, a perennial teosinte (referred to as Diplo). Major Conclusions and Achievements Two NILs targeting a Diplo introgression in bin 1.04 showed a significant increase in oil content in homozygous sib-pollinated seed when compared to sibbed seed of their counterpart non-introgressed controls. These BC4S2 NILs, referred to as D-RD29 and D-RD30, carry the Diplo allele in bin 1.04 and the introgression extends partially into bins 1.03 and 1.05. These NILs remain heterozygous in bins 4.01 and 8.02, but otherwise are homozygous for the recurrent parent (RD6502) alleles. NILs were developed also for the Chalco introgression in bin 1.04 but these do not show any improvement in oil content, suggesting that the Chalco alleles differ from the Diplo alleles in this region. Testcross Fl seed and sibbed grain from these Fl plants did not show any effect on oil content from this introgression, suggesting that it would need to be present in both parents of a maize hybrid to have an effect on oil content. Implications, both Scientific and Agricultural The Diplo region identified increases oil content by 12.5% (from 4.8% to 5.4% oil in the seed). Although this absolute difference is not large in agronomic terms, this locus could provide additive increases to oil content in combination with other maize-derived loci for high oil. To our knowledge, this is the first confirmed report of a QTL from teosinte for improved grain oil content in maize. It suggests that further research on grain quality alleles from maize wild relatives would be of both scientific and agricultural interest.
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Smith, Margaret, Nurit Katzir, Susan McCouch, and Yaakov Tadmor. Discovery and Transfer of Genes from Wild Zea Germplasm to Improve Grain Oil and Protein Composition of Temperate Maize. United States Department of Agriculture, October 2002. http://dx.doi.org/10.32747/2002.7695846.bard.
Full textAbstract:
Project Objectives 1. Develop and amplify two interspecific populations (annual and perennial teosintes x elite maize inbred) as the basis for genetic analysis of grain quality. 2. Identify quantitative trait loci (QTLs) from teosinte that improve oil, protein, and essential amino acid composition of maize grain. 3. Develop near isogenic lines (NILs) to quantify QTL contributions to grain quality and as a resource for future breeding and gene cloning efforts. 4. Analyze the contribution of these QTLs to hybrid performance in both the US and Israel. 5. Measure the yield potential of improved grain quality hybrids. (NOTE: Yield potential could not be evaluated due to environmentally-caused failure of the breeding nursery where seed was produced for this evaluation.) Background: Maize is a significant agricultural commodity worldwide. As an open pollinated crop, variation within the species is large and, in most cases, sufficient to supply the demand for modem varieties and for new environments. In recent years there is a growing demand for maize varieties with special quality attributes. While domesticated sources of genetic variation for high oil and protein content are limited, useful alleles for these traits may remain in maize's wild relative, teosinte. We utilized advanced backcross (AB) analysis to search for QTLs contributing to oil and protein content from two teosinte accessions: Zea mays ssp. mexicana Race Chalco, an annual teosinte (referred to as Chalco), and Z diploperennis Race San Miguel, a perennial teosinte (referred to as Diplo). Major Conclusions and Achievements Two NILs targeting a Diplo introgression in bin 1.04 showed a significant increase in oil content in homozygous sib-pollinated seed when compared to sibbed seed of their counterpart non-introgressed controls. These BC4S2 NILs, referred to as D-RD29 and D-RD30, carry the Diplo allele in bin 1.04 and the introgression extends partially into bins 1.03 and 1.05. These NILs remain heterozygous in bins 4.01 and 8.02, but otherwise are homozygous for the recurrent parent (RD6502) alleles. NILs were developed also for the Chalco introgression in bin 1.04 but these do not show any improvement in oil content, suggesting that the Chalco alleles differ from the Diplo alleles in this region. Testcross Fl seed and sibbed grain from these Fl plants did not show any effect on oil content from this introgression, suggesting that it would need to be present in both parents of a maize hybrid to have an effect on oil content. Implications, both Scientific and Agricultural The Diplo region identified increases oil content by 12.5% (from 4.8% to 5.4% oil in the seed). Although this absolute difference is not large in agronomic terms, this locus could provide additive increases to oil content in combination with other maize-derived loci for high oil. To our knowledge, this is the first confirmed report of a QTL from teosinte for improved grain oil content in maize. It suggests that further research on grain quality alleles from maize wild relatives would be of both scientific and agricultural interest.