Dissertations / Theses: '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 Pinheiro
Dissertação (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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
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.

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Zhu, Guohua. "Ascertainment in two-phase sampling designs for segregation and linkage analysis /." Connect to text online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1112844349.

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Thesis (Ph. D.)--Case Western Reserve University, 2005.
[School of Medicine] Department of Epidemiology and Biostatistics. Includes bibliographical references. Available online via OhioLINK's ETD Center.

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Chen, Lin. "Causal modeling in quantitative genomics /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/9577.

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Wilder, Steven P. "Computational analysis of susceptibility genes for diabetes and cardiovascular diseases in animal models." Thesis, University of Oxford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670109.

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Maniatis, Nikolaos. "Quantitative genetic analyses of growth traits in sheep under different models of inheritance." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341920.

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Morrill, Benson H. "Quantitative Genetic Analysis of Reproduction Traits in Ball Pythons." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1005.

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Although the captive reproduction of non-avian reptiles has increased steadily since the 1970’s, a dearth of information exists on successful management practices for large captive populations of these species. The data reported here come from a captive population of ball pythons (Python regius) maintained by a commercial breeding company, The Snake Keeper, Inc. (Spanish Fork, UT). Reproductive data are available for 6,480 eggs from 937 ball python clutches. The data presented suggest that proper management practices should include the use of palpation and/or ultrasound to ensure breeding occurs during the proper time of the female reproductive cycle, and that maintenance of proper humidity during the incubation of eggs is vitally important. Ball python reproduction traits (clutch size, clutch mass, relative clutch mass, egg mass, hatch rate, egg length, egg width, hatchling mass, healthy offspring per clutch, week laid, and days of incubation) were recorded for the clutches laid during this study. For the 937 clutches, the identity of the dam and sire were known for 862 (92%) and 777 (83%) of the clutches, respectively. A multivariate model that included nine of the 11 traits listed above was compiled. Heritability and genetic and phenotypic correlations were calculated from the multivariate analysis. The trait that showed the most promise for use in artificial selection to increase reproduction rates was clutch size due to considerable genetic variation, high heritability, and favorable genetic correlations with other reproduction traits. Although large datasets have been published for twinning in avian species, relatively few are available for non-avian reptiles. Reported here are 14 sets of twins produced from 6,480 eggs from 937 ball python clutches. The survival rate for twins during the first 3 months of life in our study was 97%. Interestingly, 11 of the sets of twins were identical in sex and phenotype, and additional genetic data suggested the rate of monozygotic twinning within this captive population of ball pythons was higher than that of dizygotic twinning. Further, using microsatellite analysis we were able to generate data that shows three sets of python twins were genetically identical.

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Miyake, Takeshi. "STATISTICAL GENETIC EVALUATION OF ANIMALS FOR QUANTITATIVE TRAITS UNDER POLYGENIC MODEL AND MIXED INHERITANCE MODEL." Kyoto University, 1999. http://hdl.handle.net/2433/181392.

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Sampson, Joshua Neil. "Clustering genes in genetical genomics /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/9549.

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Hanif, Shahid. "Quantitative expression of genes involved in the leptin receptor-mediated STAT signalling pathway in rodent models of obesity." Thesis, University of Glasgow, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272872.

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Carlborg, Örjan. "New methods for mapping quantitative trait loci /." Uppsala : Dept. of Animal Breeding and Genetics, Swedish Univ. of Agricultural Sciences ([Institutionen för husdjurens genetik], Sveriges lantbruksuniv.), 2002. http://projkat.slu.se/SafariDokument/210.htm.

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Faria, Vinícius Ribeiro. "Melhor Predição Linear Imparcial (BLUP) no melhoramento vegetal: seleção entre famílias de meios-irmãos." Universidade Federal de Viçosa, 2008. http://locus.ufv.br/handle/123456789/4776.

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The objectives of the present work were to install the REML/BLUP methodology in the recurrent populational improvement, using half-brothers families, to compare this methodology with the traditional analysis of the ordinary least squares and to present the SAS routines for the analyses of mixed models. The model used corresponds to the beeder model used in the animal improvement. The computer analyses were carried out using the computer software SAS® through proc mixed, proc inbreed, proc iml and proc gml procedures. As the theory support, data from three cycles of recurrent selection in the population of Voçosa por-corn, of the Programa de Melhoramento do Setor de Genética (Improvement Program of the Genetic Sector), do Departamento de biologia Gerald a Universidade Federal de Viçosa (Department of General Biology of the Viçosa Federal University) were used. The experiments were designed in single 14 x 14 lattice. In each block of the experiment, the production and the expansion ability (CE) in ml/g were evaluated. For each improvement cycle, the variance components were estimated the genotypic means were predicted, according to the REML/BLUP methodology. For each cycle the analysis by the ordinary Least Squares (OLS) was also made with the estimation of the variance components and of the genotypic means. Besides, the gains due to the selection in each cycle mere calculated. Moreover the ordination of the selected individuals was verified and the confidence intervals for the genetic values predicted and estimated were built. By the variance analysis, it could be verified that as the improvement cycles progressed, there was a sifnificant reduction in the variability for CE, and in the third selection cycle the variability was no more detected. This variability reduction can be explained by the high selection intensity, because the 20 families selected in the third cycle were from only mine plants of the first cycle of selection. Referring the genetic parameters estimated by the two methodologies, it was observed that both with the REML and the OLS methodology the estimate values for the variance components were similar. For the genotypic means, when there was no relationship among the individuals there was an accordance among the best individuals estimated and predicted, but the predicted values presented narrower confidence intervals, indicating that these values are more accurate than the estimated ones. When the relationship information was included, there was a reduction on the coincidence values between the selected ones and those of the Speerman co-relation indicating that the use of the prodictd genotypic means in the selection of superior individuals will provide greater gains due to the selection.
O presente trabalho teve como objetivos implementar a metodologia REML/BLUP no melhoramento populacional recorrente, empregando famílias de meios-irmãos, comparar essa metodologia com a análise tradicional por mínimos quadrados ordinário e apresentar as rotinas do SAS para as análises de modelos mistos. O modelo empregado corresponde ao modelo de reprodutor utilizado no melhoramento animal. As análises computacionais foram realizadas utilizando o aplicativo computacional SAS® por meio dos seus procedimentos proc mixed, proc inbreed, proc iml e proc glm. Como suporte à teoria, foram utilizados dados de três ciclos de seleção recorrente na população de milho-pipoca Viçosa, do Programa de Melhoramento do Setor de Genética, do Departamento de Biologia Geral da Universidade Federal de Viçosa. Os experimentos foram delineados em látice 14 x 14 simples. Em cada parcela dos experimentos, foram avaliadas a produção e a capacidade de expansão (CE) em ml/g. Para cada ciclo de melhoramento, foram estimados os componentes de variância e preditas as médias genotípicas, de acordo com a metodologia REML/BLUP. Para cada ciclo também foi feita análise por Mínimos Quadrados Ordinário (OLS), com estimação dos componentes de variância e das médias genotípicas. Foram calculados, ainda, os ganhos devidos à seleção em cada ciclo. Também foi verificada a ordenação dos indivíduos selecionados e construídos os intervalos de confiança para os valores genéticos preditos e estimados. Pelas análises de variância, pôde-se verificar que à medida que os ciclos de melhoramento avançaram, houve uma redução significativa na variabilidade para CE, sendo que no terceiro ciclo de seleção não foi detectada variabilidade. Essa redução da variabilidade pode ser explicada pela alta intensidade de seleção, tanto que as 20 famílias selecionadas no terceiro ciclo eram originárias de apenas nove plantas do primeiro ciclo de seleção. Quanto aos parâmetros genéticos estimados pelas duas metodologias, observou-se que, tanto pela metodologia REML quanto pela OLS, os valores estimados para os componentes de variância foram semelhantes. Para as médias genotípicas, quando não existia parentesco entre os indivíduos, houve concordância entre os melhores indivíduos estimados e preditos, porém, os valores preditos apresentaram intervalos de confiança mais estreitos, indicando que esses valores são mais precisos que os estimados. Ao incluir as informações de parentesco, houve uma redução nos valores de coincidência entre os selecionados e os da correlação de Speerman, indicando que o uso das médias genotípicas preditas na seleção dos indivíduos superiores proporcionará maiores ganhos devidos à seleção.

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21

Galal, Ushma. "The statistical theory underlying human genetic linkage analysis based on quantitative data from extended families." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_2684_1361989724.

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Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the
development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.
There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.

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22

Mistro, Julio César. "Estimativas de parâmetros genéticos visando o melhoramento do café robusta (Coffea canephora Pierre ex. A. Froehner)." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/11/11137/tde-11092013-153709/.

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O presente estudo objetivou estimar parâmetros genéticos visando quantificar a variabilidade genética de uma população de café robusta (Coffea canephora Pierre ex A. Froehner) introduzida da Costa Rica e analisar o seu potencial genético para o desenvolvimento de futuras cultivares clonais para o estado de São Paulo. Outro intuito foi verificar a possibilidade de submeter essa população à seleção recorrente, tornando-a, assim, fonte de alimentação e sustentação de programas de melhoramento genético do café robusta. O experimento foi composto por 25 tratamentos, sendo 21 progênies de C. canephora e quatro cultivares de C. arabica, plantados em Mococa (SP). O delineamento experimental utilizado foi em látice balanceado 5x5 quadruplicado, com seis repetições e uma planta por parcela. Foram realizadas doze colheitas e após a sexta colheita as plantas foram podadas. Em 2004, foi realizada uma seleção fenotípica dessa população a fim de clonar os melhores indivíduos. Essa seleção resultou em novo experimento, instalado em Campinas, seguindo o delineamento de blocos ao acaso, com três repetições, 28 clones e quatro plantas por parcela, sendo realizadas cinco colheitas consecutivas. As análises estatísticas e biométricas foram realizadas considerando os modelos lineares mistos (procedimento REML/BLUP), por meio do software Selegen, cujos componentes de variância são estimados pelo método da máxima verossimilhança restrita (REML) e os valores genotípicos preditos pela melhor predição linear não viesado (BLUP). As análises mostraram que, na população em estudo, observou-se elevada variabilidade genética, passível de ser explorada tanto para a extração de clones quanto para a seleção recorrente. As adversidades climáticas severas fizeram com que a seleção fosse prejudicada. Nessa situação é preferível não considerar o período afetado e analisar os dados após a recuperação das plantas. A seleção baseada em seis colheitas forneceu estimativas de parâmetros e ganhos genéticos similares aos obtidos na seleção baseada em duas colheitas de alta produção. Os ganhos genéticos esperados nas duas formas de propagações foram elevados e a seleção clonal proporcionou maiores ganhos do que a sexual. No experimento clonal foi possível identificar materiais com potencial produtivo e que poderão vir a ser recomendados para o cultivo no estado de São Paulo. Apesar de a interação genótipos x colheitas ter sido do tipo complexa, devido ao veranico ocorrido, esta não afetou significativamente o ordenamento dos melhores clones e nem comprometeu as estimativas dos parâmetros genéticos. Os coeficientes de variação experimental e genético bem como seu valor relativo deverão ser analisados conjuntamente com o número de repetições e a acurácia seletiva. A seleção recorrente deverá ser conduzida concomitantemente com o programa de seleção clonal, a fim de evitar o esgotamento da variabilidade genética e o comprometimento do programa de melhoramento genético visando o desenvolvimento de cultivares clonais. Tendo em vista que a população inicial foi constituída por um pequeno número de progênies, é aconselhável o monitoramento do tamanho efetivo populacional e do grau de endogamia ao longo dos ciclos de seleção recorrente.
The objective of this research was to estimate genetic parameters to quantify the variability of a population of robusta coffee (Coffea canephora Pierre ex A. Froehner) introduced into Brazil from Costa Rica in 1974 aiming at determining its genetic potential for the development of clonal or seedling cultivars for the state of São Paulo, Brazil. The feasibility has also been studied to submit this population to recurrent selection, making it a continuous source of improved base material in support of varietal improvement of robusta. An experiment consisting of 21 open pollinated seedling progenies of robusta and four cultivars of arabica was established in Mococa (SP) in 1975. Yield was observed for twelve harvests and after the sixth harvest the plants were pruned. The experimental lay out was a balanced 5x5 quadruple lattice design, with six replicates and one plant per plot. In 2004 a phenotypic selection of this population for yield was carried out aiming at cloning the best individuals. These 28 clones were planted in an experiment in Campinas in 2005, following a completely randomized block design, with 28 treatments (clones), three replications and four plants per plot. In total, yields were collected over five harvests. Statistical and biometrical analyzes were performed considering the linear mixed models (REML/BLUP), through software Selegen, where the variance components are estimated by restricted maximum likelihood (REML) and genotypic values predicted by best linear unbiased prediction (BLUP). The analyzes showed that the population had high genetic variability, which can be exploited for the extraction of both clones and seedling progenies, used for recurrent selection. Selection was impaired by severe adverse weather conditions. In such situations it is preferable not to consider the affected period and analyze the data after recovery of the plants. Due to the moisture stress that occurred in the clonal trial, genotype x environment interaction was complex. However this did not affect the ranking of superior clones nor compromised the genetic parameter estimates. Selection for yield based on six yield resulted in genetic parameters and genetic gains similar to those obtained by selection based on two high yielding harvesting periods. The expected genetic gains both for clones as for open pollinated progenies were high. However, clonal selection resulted in higher genetic gains for yield than the seedling selection. In the clonal experiment it was possible to identify materials with high yield potential that may become to be recommended for cultivation in São Paulo State. The experimental, genetics and relative coefficients of variation, should be analyzed together with the number of replications and selective accuracy. Recurrent selection should be conducted concurrently with the clonal selection program in order to avoid depletion of genetic variability and to impairthe breeding program aiming at the development of clonal cultivars. Considering that the initial population was composed of a small number of progeny, it will be important monitoring adequately the effective size and the inbreeding coefficient during recurrent selection cycles.

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23

Banerjee, Samprit. "Bayesian genome-wide QTL mapping for multiple traits." Thesis, Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2009r/banerjee.pdf.

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24

Dhindaw, Seema. "Characterization of a 793 Kilobase Segment of the Rat Genome in Blood Pressure Regulation." University of Toledo Health Science Campus / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=mco1188911291.

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25

Phenix, Hilary. "Derivation and Use of Gene Network Models to Make Quantitative Predictions of Genetic Interaction Data." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/37031.

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This thesis investigates how pairwise combinatorial gene and stimulus perturbation experiments are conducted and interpreted. In particular, I investigate gene perturbation in the form of knockout, which can be achieved in a pairwise manner by SGA or CRISPR/Cas9 methods. In the present literature, I distinguish two approaches to interpretation: the calculation of stimulus and gene interactions, and the identification of equality among phenotypes measured for distinct perturbation conditions. I describe how each approach has been applied to derive hypotheses about gene regulatory networks. I identify conflicts and uncertainties in the assumptions allowing these derivations, and explore theoretically and experimentally approaches to improve the interpretation of genetic interaction data. I apply the approaches to a well-studied gene regulatory branch of the DNA damage checkpoint (DDC) pathway of Saccharomyces cerevisiae, and confirm the known order of genes within this pathway. I also describe observations that seem inconsistent with this pathway structure. I explore this inconsistency experimentally and discover that high concentrations of the DNA alkylating drug methyl methanesulfonate cause a cell division arrest program distinct from a G1 or G2/M checkpoint or from DNA damage adaptation, that resembles an endocycle.

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26

Goldberg, Ximena. "Complex Models of Genetic and Environmental Influences on Human Cognition. Implications for Functional Psychoses / Modelos complejos de las influencias genéticas y ambientales en la cognición humana. Implicaciones para las psicosis funcionales." Doctoral thesis, Universitat de Barcelona, 2012. http://hdl.handle.net/10803/83588.

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The general construct of human cognition implies a series of mental processes by means of which human interpret and consequently act on the world that surrounds them (Sternberg y Mio, 2009). During the last decades, the recognition of human diversity and psychological variability among individuals has encouraged challenging questions addressing inter-individual differences that make each subject unique in terms of their cognitive performance (Baddeley, 2003; Botvinick, 2008). In particular, quantitative genetic studies show that both genetic variability and environmental factors are involved in the phenotypic expression of cognitive functions (Plomin, 2011). However, the mechanisms by which genes and exposure to environmental influences may contribute to the observed variability are not yet clear. The study of the origins of inter-individual differences in cognition is strongly associated with the ontogenic development of the human brain (Tau, 2010). As a consequence, cognitive alterations are considered a central trait in those mental disorders where neurodevelopmental alterations are assumed to exist, such as schizophrenia. This disease, which affects around 1% of the world’s population, is one of the main causes of years lost due to disability (WHO, 2004), while cognitive alterations in these patients explain about 20%-60% of the variance in measures of outcome (Green, 2004). The aetiological model of neurodevelopment in schizophrenia proposes that this disease might be the expression of neurobiological compromise that could begin early in the lifespan, even before the onset of the clinical symptoms (van Os, 2009). However, and despite the scientific efforts invested in the elucidation of its aetiological underpinnings, the heterogeneous presentation of the disease has prevented a deeper comprehension of these mechanisms. Are all cognitive domains heritable? Are there long-term consequences on cognition for the early exposure to environmental impact? What is the association between genetic variability and cognitive vulnerability? Can we identify specific neurobiological pathways in the expression of the cognitive alterations of patients with schizophrenia? These questions are explored in the present thesis through the analyses of twins- and family-based samples, which constitute powerful designs to study the effects of genetic and environmental variability on human cognition. In the six chapters of results that are the body of this thesis, complex models are proposed that aim at representing the mechanisms involved in the origin of cognitive variability at the population level. The findings included indicate that this variability could be the result of the relative contribution of genetic determination and environmental modelling, which could vary in different cognitive functions following ontogenic mechanisms of neurodevelopment. Specifically, results are reported on the influences of childhood maltreatment and socioeconomic status as environmental stressors, as well as Val158Met functional polymorphism of COMT gene as a genetic factor. The aetiological implications of the study of these processes are extended to the field of mental disorders, as the results may indicate that the cognitive variability present among patients with schizophrenia could support a model of developmental compromise in this disease. Accordingly, the effects of genetic and environmental influences on behaviour may underlie the heterogeneous expression of this highly disabling mental disorder. To sum up, the phenotypic diversity of schizophrenia and human cognition, far from representing an obstacle, lays the foundations for complex models of these traits that may feed an increasing understanding of their aetiology (Belsky, 2011). These findings highlight the putative role of neurobiological liability traits in crucial aspects of clinical practice. Risk factors might be identified that could be included as potential guidelines in the assessment and management of need-adapted treatments (Leiftker, 2009). Moreover, liability traits might operate as markers in preventive interventions for targeting individuals at risk of developing particular forms of the disease (Keshavan, 2011).
El constructo general de cognición humana involucra una serie de procesos mentales por medio de los cuales los individuos perciben, interpretan y, en consecuencia, actúan sobre la realidad que los rodea y sobre sus pares (Sternberg y Mio, 2009). En los últimos años, el reconocimiento de la diversidad humana y la variabilidad de los rasgos psicológicos entre los individuos ha promovido preguntas acerca de las diferencias inter-individuales que hacen a cada sujeto único en términos de cognición (Baddeley, 2003; Botvinick, 2008). En particular, los estudios de genética cuantitativa demuestran que tanto la variabilidad genética como los factores ambientales podrían estar involucrados en la expresión fenotípica de las funciones cognitivas (Plomin, 2011). Sin embargo, aún no son claros los mecanismos específicos por medio de los cuales los genes y el ambiente contribuyen a esta variabilidad. Las alteraciones cognitivas son un rasgo central en enfermedades mentales donde se presume que existen alteraciones del neurodesarrollo, como lo es la esquizofrenia. El modelo etiológico del neurodesarrollo de la esquizofrenia propone que esta enfermedad se expresaría como consecuencia de alteraciones neurobiológicas que iniciarían en una época temprana de la vida, incluso antes del desencadenamiento de los síntomas clínicos (van Os, 2009). No obstante, la presentación heterogénea de la enfermedad ha dificultado una comprensión más clara de los mecanismos involucrados en su manifestación. ¿Son todas las funciones cognitivas igualmente heredables? ¿Tienen los factores ambientales tempranos consecuencias a largo plazo sobre la cognición? ¿Cuál es la relación entre variabilidad genética y vulnerabilidad cognitiva? ¿Existen vías neurobiológicas específicas para la manifestación de las alteraciones cognitivas en pacientes con esquizofrenia? Estas preguntas se exploran en la presente tesis a partir de análisis basados en muestras de gemelos y en grupos familiares, que constituyen una manera metodológicamente potente de estudiar los efectos de la variabilidad genética y ambiental sobre la cognición humana. En este sentido, la diversidad fenotípica de la esquizofrenia y la cognición humana, lejos de representar un obstáculo para la investigación de su etiología, sienta las bases de modelos complejos que podrían fomentar una comprensión cada vez más completa de los mecanismos de vulnerabilidad y resiliencia posiblemente involucrados en su origen (Belsky, 2011).

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27

Vanhoenacker, Eloïse. "The evolution of sex : theoretical study based on quantitative genetics models ad experimental approach using the facultatively sexual rotifer Brachionus plicatilis." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS347.

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L’objectif de cette thèse était d’étudier les bénéfices évolutifs possibles de la reproduction sexuée par une approche à la fois théorique et expérimentale. La première approche visait au développement de modèles de génétique quantitative pour l’évolution du sexe. Un premier modèle (s’appuyant sur le modèle géométrique de Fisher) considère un nombre arbitraire de traits phénotypiques sous sélection stabilisante autour d’un optimum fixe, et explore l’effet du biais mutationnel agissant sur les traits. Un deuxième modèle représente un trait phénotypique à la fois sous sélection stabilisante et directionnelle (représentée par un déplacement de l’optimum phénotypique de façon linéaire, cyclique ou stochastique). Des simulations individu-centrées ont montré qu’en l’absence de biais ou de changement environnemental, la population évolue vers l’asexualité. Cependant, avec un biais mutationnel, des taux de sexe intermédiaires peuvent évoluer même lorsque le coût du sexe est élevé. Des taux de sexe plus importants peuvent évoluer lorsque l’optimum phénotypique change dans le temps. La deuxième partie de la thèse consistait à développer un modèle expérimental pour tester les prédictions théoriques sur les éventuels avantages du sexe, en utilisant le rotifère à reproduction sexuée facultative Brachionus plicatilis. Les résultats démontrent l’existence de variabilité génétique dans l’investissement pour le sexe, entre des souches d’une même population naturelle, et celle d’effets maternels transgénérationels qui affectent le taux de sexe. Pour finir, les résultats d’une expérience d’évolution suggèrent que le sexe facilite l’adaptation à un environnement stressant
This thesis aimed at investigating some of the possible evolutionary benefits of sexual reproduction using both a theoretical and an experimental approach. The first approach consisted in developing evolutionary quantitative genetic models for the evolution of sex. A first model (based on Fisher’s geometrical model) considers an arbitrary number of phenotypic traits under stabilizing selection around a fixed optimum, and explores the effect of mutational bias acting on the traits. A second model represents a phenotypic trait under both stabilizing and directional selection (modeled by a linear, cyclical or stochastic change in the phenotypic optimum). Individual-based simulations showed that in the absence of mutational bias or environmental change, the population evolves towards asexuality. However, with mutational bias, intermediate rates of sex are maintained in the population even when the cost of sex is strong. Higher rates of sex evolve when the phenotypic optimum changes over time. The second part of the thesis consisted in developing an experimental model to test theoretical predictions on the possible benefits of sex, using the facultatively sexual rotifer Brachionus plicatilis. The results demonstrate genetic variation for investment in sex between strains from the same natural population, and the existence of transgenerational maternal effects affecting the rate of sex. Finally, the results from an evolution experiment suggest that sex facilitates adaptation to a stressful environment

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28

Nettelblad, Carl. "Two Optimization Problems in Genetics : Multi-dimensional QTL Analysis and Haplotype Inference." Doctoral thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-180920.

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The existence of new technologies, implemented in efficient platforms and workflows has made massive genotyping available to all fields of biology and medicine. Genetic analyses are no longer dominated by experimental work in laboratories, but rather the interpretation of the resulting data. When billions of data points representing thousands of individuals are available, efficient computational tools are required. The focus of this thesis is on developing models, methods and implementations for such tools. The first theme of the thesis is multi-dimensional scans for quantitative trait loci (QTL) in experimental crosses. By mating individuals from different lines, it is possible to gather data that can be used to pinpoint the genetic variation that influences specific traits to specific genome loci. However, it is natural to expect multiple genes influencing a single trait to interact. The thesis discusses model structure and model selection, giving new insight regarding under what conditions orthogonal models can be devised. The thesis also presents a new optimization method for efficiently and accurately locating QTL, and performing the permuted data searches needed for significance testing. This method has been implemented in a software package that can seamlessly perform the searches on grid computing infrastructures. The other theme in the thesis is the development of adapted optimization schemes for using hidden Markov models in tracing allele inheritance pathways, and specifically inferring haplotypes. The advances presented form the basis for more accurate and non-biased line origin probabilities in experimental crosses, especially multi-generational ones. We show that the new tools are able to reconstruct haplotypes and even genotypes in founder individuals and offspring alike, based on only unordered offspring genotypes. The tools can also handle larger populations than competing methods, resolving inheritance pathways and phase in much larger and more complex populations. Finally, the methods presented are also applicable to datasets where individual relationships are not known, which is frequently the case in human genetics studies. One immediate application for this would be improved accuracy for imputation of SNP markers within genome-wide association studies (GWAS).
eSSENCE

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29

Reyes-Centeno, Hugo [Verfasser], and Katerina [Akademischer Betreuer] Harvati. "Quantitative and population genetic approaches for testing modern human out-of-Africa models / Hugo Reyes-Centeno ; Betreuer: Katerina Harvati." Tübingen : Universitätsbibliothek Tübingen, 2016. http://d-nb.info/1164018361/34.

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30

Karaman, Mesut. "A Genetic Algorithm For The Multi-level Maximal Covering Ambulance Location Problem." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12610099/index.pdf.

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The emergency medical services (EMS) provide the preliminary assistance and transportation for patients in need of urgent medical care in order to decrease the mortality rate and reduce the non-reversible effects of injuries. Since the objective is directly related to the human life, the value of the proposed solutions in order to improve the performance of EMS is highly welcomed. Mainly, there are three problems that EMS managers face with: location, allocation and redeployment of the EMS facilities/vehicles. Most of the studies in EMS literature focus on accurately modeling the probabilistic nature of the availability of an ambulance when it is called for. However, trivial changes in model parameters or estimates could dramatically change the optimal allocations generated by the probabilistic models and hence make the model invalid. In this study, we formulate the ambulance location problem as a deterministic multi-level maximal coverage model by which the total demand is tried to be covered as many as possible at multiple levels. Both a mathematical programming model and genetic algorithm-based heuristic approaches are proposed for the problem. The results indicate that the genetic algorithm-based solutions give reliable (near-optimal) and robust results in reasonable computational times for the problem. Moreover, the tradeoffs between the two performance measures, &lsquo
responsiveness&rsquo
and &lsquo
preparedness&rsquo
, are searched for
and our approaches with multi-level coverage are compared against the multiple coverage approaches in terms of these performance measures.

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Valente, Mágno Sávio Ferreira. "Emprego do BLUP/REML na avaliação genética de linhagens elites de milho-pipoca." Universidade Federal de Viçosa, 2010. http://locus.ufv.br/handle/123456789/4719.

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In breeding programs, it is important to use viable alternatives to reduce cost and time spent on population evaluations, combined with adequate statistical methodologies applying the maximum information available. Within this context, this work aimed to: i) study the genetic control of popping capacity and grain yield in popcorn; ii) predict the effects of general combining ability (GCA) and specific combining ability (SCA), applying mixed model analysis; iii) evaluate the performance per se of the lines used in hybrid crosses; and iv) evaluate the efficiency of Best Linear Unbiased-Prediction (BLUP) in predicting the performance of non crossed hybrids in diallelic analysis. Data from experiment evaluations of intra-population diallels of the Beija-Flor and Viçosa popcorn populations were used in the analyses. Eighteen S6 Beija-Flor elite lines were analyzed in ten environments and 29 S6 Viçosa elite lines in eight environments. Combined analyses were carried out, considering all the environments, with the additive model being adopted. The software ASREML was used in all analyses. GCA variability was verified both for grain yield and popping capacity. A significant SCA variability was verified in Beija-Flor for the two variables. In Viçosa, SCA was significant at 8% for grain yield while for popping capacity, the presence of additive effects was practically verified in its expression. Through the incorporation of sibling relationships in diallelic analysis, SCA values of combination of a line with itself (sjj) were predicted, without such cross being carried out. The use of BLUP/REML allowed the prediction of over 43 to 210% hybrid combinations, if compared only to the hybrid observed. Based on hybrid predictions, promising crosses were identified both for grain yield and popping capacity, being observed that the inclusion of a pedigree seems to make the analyses more accurate, as compared to the model not using this information. The performance per se and under S6 family crosses showed moderate correlations (r = 0.53) for popping capacity, showing that families with high popping capacity GCA can be selected, based on their performance per se. Aiming to obtain information on the efficiency in predicting S6 families based on performance per se and on S3 family crosses, a positive correlation (r = 0.76) was found for production between the GCA of top cross hybrids of the S3 families and the S6.family hybrids. When verifying BLUP efficiency in the prediction of non crossed hybrids, moderate to high Pearson and Spearman correlations were found among the predicted and observed values. Prediction of hybrids in the absence of dominance (popping capacity, r = 0.88) was more efficient than in the presence of dominance (grain yield, r = 0.53). The overall results showed that the use of mixed models is an efficient alternative in diallelic analysis, providing good precision in estimating genetic parameters, besides allowing the prediction of non crossed hybrids.
Em programas de melhoramento é importante o uso de alternativas viáveis para redução de custos e tempo nas avaliações de populações, aliadas ao uso de metodologias estatísticas adequadas, que aproveitem ao máximo as informações disponíveis. Neste contexto, o presente trabalho teve como objetivos: i) estudar o controle genético da capacidade de expansão e produção de grãos em milho-pipoca; ii) predizer os efeitos da capacidade geral de combinação (CGC) e da capacidade específica de combinação (CEC) por meio da análise de modelos mistos; iii) avaliar o desempenho per se das linhagens utilizadas nos cruzamentos híbridos; iv) avaliar a eficiência do BLUP na predição do desempenho de híbridos não realizados na análise dialélica. Nas análises, foram utilizados dados de experimentos de avaliação de dialelos intrapopulacionais das populações de milho-pipoca Beija-Flor e Viçosa. Foram analisadas 18 linhagens elites S6 de Beija-Flor, em 10 ambientes, e 29 linhagens elites S6 de Viçosa, em 8 ambientes. Foram realizadas análises conjuntas, considerando todos os ambientes, sendo adotado o modelo aditivo-dominante. Em todas as análises foi utilizado o software ASREML. Foi verificada variabilidade para CGC tanto para produção como para capacidade de expansão. Para CEC houve variabilidade significativa em Beija-Flor para as duas variáveis. Em Viçosa, a CEC foi significativa a 8% para produção de grãos, enquanto para capacidade de expansão foi verificada praticamente a presença de efeitos aditivos na sua expressão. Por meio da incorporação de informações de parentesco na análise dialélica, valores de capacidade específica de combinação de uma linhagem com ela mesma (sjj) foram preditos, sem que este cruzamento tenha sido realizado. Com o uso do BLUP/REML foi possível predizer de 43% a 210% a mais de combinações híbridas, se comparada somente aos híbridos observados. A partir das predições dos híbridos, cruzamentos promissores foram identificados tanto para produção de grãos como para capacidade de expansão, sendo que a inclusão do pedigree parece deixar as análises mais acuradas, em comparação ao modelo sem uso destas informações. O desempenho per se e em cruzamento de famílias S6 evidenciaram correlações moderadas (r=0,53) para capacidade de expansão, mostrando ser possível selecionar famílias com alta CGC em capacidade de expansão a partir do desempenho per se de suas famílias. Visando obter informações sobre a eficiência da predição de famílias S6 a partir do desempenho per se e em cruzamento de famílias S3, foi encontrada correlação positiva (r=0,76) para produção, entre a CGC dos híbridos topcross de famílias S3 e híbridos de famílias S6. Ao verificar a eficiência do BLUP na predição de híbridos não realizados, foram encontradas correlações de Pearson e Spearman de moderada a elevadas, entre os valores preditos e observados. A predição de híbridos não realizados na ausência de dominância (capacidade de expansão, r=0,88) foi mais eficiente, em comparação à presença de dominância (produção de grãos, r=0,53). Os resultados gerais demonstraram que o uso de modelos mistos é uma alternativa eficiente na análise dialélica, proporcionando boa precisão nas estimações dos parâmetros genéticos, além de permitir a previsão de cruzamentos não realizados.

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Duarte, Nubia Esteban. "Análise multivariada no mapeamento genético de traços quantitativos." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-01032013-184306/.

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Em pesquisa Genômica é de grande interesse o mapeamento de genes que controlam traços ou fenótipos quantitativos. Metodologias estatsticas para identicar genes que tenham efeitos sobre um unico traço são bem conhecidas na literatura e têm sido exaustivamente aplicadas no mapeamento genético de muitas doenças. Porem, na pratica, diferentes traços são correlacionados, como é o caso de hipertensão e obesidade, possivelmente, devido a aço de genes comuns envolvidos na sua regulação. Nestes casos, por meio de tecnicas estatísticas multivariadas, que exploram a estrutura de covariância entre os traços, é possvel identificar genes não detectados por analises univariadas, ganhar precisão nas estimativas dos efeitos e conhecer a posicão desses genes, alem de testar efeitos de pleiotropia (um mesmo gene controlando varios traços) e interacções gene-ambiente (os genes que controlam a pressão antes e depois de dieta com sal). Neste trabalho diferentes alternativas de analise estatstica são consideradas para explorar a informacão de vários tracos conjuntamente: modelo de regressão intervalar multivariado (Jiang & Zeng, 1995), mapeamento multivariado via a teoria espectral (Mangin et al.,1998), via medidas resumo relevantes (como a diferenca entre respostas antes e depois de uma exposição) e via ajustes por covariaveis. Também são introduzidas algumas abordagens graficas para o estudo do efeito de pleiotropia e interação geneambiente. As metodologias supracitadas são aplicadas a dados reais fornecidos pelo Laboratorio de Cardiologia e Genética Molecular do InCor/USP, que consideram várias medidas de pressão arterial em ratos provenientes de uma população F2.
In Genomic research, the mapping of genes which control quantitative traits has been of great interest. Statistical methods for detection of genes, in uencing a single trait, are well known in the literature and they have been exhaustive used in the genetic mapping of many diseases. However, in real situations, dierent kind of traits are correlated, such as hypertention and obesity, that would be due to the action of a set of commom genes involved in the regulation of these traits. In these cases, through of multivariate statistical techniques, which explore the covariance structure between the traits, it is possible to identify genes that are not detected by univariated analysis. In addition multivariate analysis are useful to obtain accurate estimates and to know the position of these genes, besides testing eects of pleiotropic (a gene controlling several traits) and geneenvironmental interations (genes that control the pressure before and after salt diet). In this work dierent alternatives from statistical analysis are considered to explore information of several traits jointly: Interval multivariate regression models (Jiang and Zeng, 1995); multivariate mapping through the espectral theory (Mangin et al. 1998), summary measures (for example, models formulated in terms of the dierence between two traits) and adjustments including covariates. Also, graphics procedures are introduced in order to study eects of pleiotropy and geneenvironmental interactions . The methodologies mentioned above are applied to real data set, supplied by the Cardiology and Molecular Genetic Laboratory of Heart institute (InCor-USP), that consider several measurements of blood pressure in rats that come from a F2 population.

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33

Laureano, Monyka Marianna Massolini. "Estudo genético quantitativo do fluxo lácteo em bovinos da raça Holandesa /." Jaboticabal : [s.n.], 2008. http://hdl.handle.net/11449/102782.

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Resumo: Parâmetros genéticos para o fluxo lácteo medido no dia do controle (FLDC) de primeiras lactações de vacas da raça Holandesa foram estimados utilizando modelos de dimensão finita (TDM) e modelos de regressão aleatória. Para os TDM foram analisadas 10 características por meio de modelos uni e bi e multi-características e de repetibilidade, que continham como aleatórios, o efeito genético aditivo e o efeito residual e, como efeitos fixos, o grupo de contemporâneos e as covariáveis idade da vaca ao parto. A variável número de dias em lactação foi incluída somente no modelo de repetibilidade. Para os MRA, foram considerados os efeitos aleatórios genético aditivo direto, de ambiente permanente e o residual. Foram considerados como efeitos fixos, o grupo de contemporâneos, os efeitos linear e quadrático da covariável idade da vaca ao parto e a curva média de lactação da população, modelada por meio de polinômios ortogonais de Legendre de quarta ordem. Os efeitos aleatórios genético aditivo e de ambiente permanente foram modelados por meio de regressão aleatória sobre polinômios ortogonais de Legendre e por meio de funções b-splines. Diferentes estruturas de variâncias residuais foram testadas, por meio de classes contendo 1, 7, 10, 20 e 43 variâncias residuais, para os MRA modelados por meio de polinômios de Legendre. Já, para os MRA modelados por funções b-splines, a estrutura residual foi considerada heterogênea, contendo 7 classes de variâncias. Os MRA foram comparados usando o teste de razão de verossimilhança, o critério de informação de Akaike e o critério de informação de Bayesiano de Schwarz. As estimativas de herdabilidade (h2) para os FLDC variaram de 0,23 a 0,32 nas análises unicaracterísticas, de 0,24 a 0,32 nas bi-características e de 0,28 a 0,37 nas multicaracterísticas. Os valores de h2 estimados variaram no decorrer da... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: Flow milk genetic parameters to the first lactation test-day milk yields of Holstein cattle were estimated using Test-day models (TDM) and Random regression models (RRM). Ten TDM differents traits were analyzed using uni, bi and multi-trait and repeatability animal models, that included the additive genetic as random effect and the fixed effects of contemporary group, age of cow (linear and quadratic) as covariables. The days in milk (linear) variable was included only at repeatability model. To RRM were included the additive genetic, permanent environmental and residual as random effects, the fixed effects of contemporary group, age of cow as covariable (linear and quadratic effects) and a 4th-order Legendre orthogonal polynomials of days in milk, to model the mean trend. The additive genetic and permanent environmental effects were fitted by Legendre orthogonal polynomials and b-splines functions. Different structures of residual variances were used, through the variances classes containing 1, 7, 10, 20, and e 43 residual variances, to the models fitted by Legendre orthogonal polynomials. Moreover, for the RRM fitted by b-splines-functions, the residual estructure was considered heterogeneous, having 7 variance classes. The RRM were compared by Likelihood ratio test, Bayesian and Akaike's information criteria. The heritability estimated ranged from 0.23 to 0.32 by uni-trait analyses, from 0.24 to 0.32 by bi-traits analyses and from 0.28 to 0.37 by multi-trait analyses. The h2 estimates varied during the lactation being the highest estimate at the fourth month. The estimate obtained by the repeatability model was 0.27, and a repeatability estimate of 0.66. For the MRA fitted by Legendre orthogonal polynomials, related to the residual variance, the best model the one that deemed 7 residual classes. For the additive and permanent environmental effects, the having 3th-order... (Complete abstract click electronic access below)
Orientadora: Lúcia Galvão de Albuquerque
Coorientadora: Lenira El Faro Zadra
Banca: Laila Talarico Dias Teixeira
Banca: Anibal Eugênio Vercesi Filho
Banca: Humberto Tonhati
Banca: Henrique Nunes de Oliveira
Doutor

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Felleki, Majbritt. "Genetic Heteroscedasticity for Domestic Animal Traits." Doctoral thesis, Högskolan Dalarna, Statistik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:du-14310.

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Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean. The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows. The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased. For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

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Villemereuil, Pierre de. "Méthodes pour l’étude de l’adaptation locale et application au contexte de l’adaptation aux conditions d’altitude chez la plante alpine Arabis alpina." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAS003/document.

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L'adaptation locale est un phénomène micro-évolutif qui peut survenir lorsque des populations d'une même espèce sont exposées à des conditions environnementales différentes.Si cet environnement exerce une pression sous forme de sélection naturelle, qu'il existe un potentiel adaptatif au sein des populations et que le flux de gènes est suffisamment modéré, les populations vont alors tendre vers un optimum adaptatif local.Dans cette thèse, je m'intéresse aux moyens méthodologiques de l'étude de l'adaptation locale d'une part, et à l'étude de ce phénomène le long d'un gradient d'altitude chez la plante alpine Arabis alpina d'autre part.Dans la première partie méthodologique, je montre que les méthodes de scan génomique pour détecter les marqueurs génétiques sous sélection peuvent souffrir de forts taux de faux positifs lorsqu'exposées à des jeux de données complexes, mais réalistes.Je présente ensuite une méthode statistique de détection de marqueurs génétiques sous sélection qui, contrairement aux méthodes existantes, utilisent à la fois la notion de différentiation génétique (ou Fst) et une information environnementale.Cette méthode a été développée de manière à limiter son taux de faux positifs de manière générale.J'offre enfin une perspective concernant les liens entre une expérience ancienne en biologie évolutive (l'expérience de jardin commun) et les nouveaux développements moléculaires et statistiques modernes.Dans la seconde partie empirique, je présente une analyse de la démographie d'A. alpina dans six populations naturelles. Outre qu'elle révèle des caractéristiques biologiques intéressantes sur cette espèce (faible espérance de vie, reproduction et survie très différentielle...), cette analyse montre que la croissance diminue et la survie augmente chez cette espèce avec la baisse de la température moyenne (donc avec l'altitude).Puisque ces analyses ne permettent pas d'exclure des hypothèses de dérive et de plasticité phénotype, je présente une analyse en jardin commun sur A. alpina qui permet de lisser les problèmes de plasticité phénotypique et qui, combinée à des analyses moléculaires, permettent d'exclure l'hypothèse de dérive.Les résultats montrent qu'il existe un syndrome phénotypique adaptatif lié à la température moyenne qui tend à des plantes plus petites, plus compactes, qui croissent et se reproduisent moins, dans les milieux froids.À l'aide des données moléculaires et de méthodes de scan génomique, je présente une liste de 40 locus qui peuvent être impliqués dans ce processus.Pour finir, je discute l'ensemble de ces résultats empiriques dans un contexte plus général d'écologie alpine. Je résume ensuite les principaux obstacles méthodologiques à l'étude de l'adaptation locale et je fourni quelques perspectives méthodologiques
Local adaptation is a micro-evolutionary phenomenon, which arises when populations of the same species are exposed to contrasted environmental conditions.If this environment exert some natural selection pressure, if an adaptive potential exists among the populations and if the gene flow is sufficiently mild, populations are expected to tend toward a local adaptive optimum.In this thesis, I study the methodological means of the study of local adaptation on the one hand, and I investigate this phenomenon along an elevation gradient in the alpine plant Arabis alpina on the other hand.In the first, methodological part, I show that the genome scan methods to detect selection using genetic markers might suffer strong false positive rates when confronted to complex but realistic datasets.I then introduce a statistical method to detect markers under selection, which, contrary to existing methods, make use of both the concept of genetic differentiation (or Fst) and environmental information.This method has been developed in order to reduce its global false positive rate.Finally, I present some perspectives regarding the relationships between the relatively old ``common garden'' experiment and the new developments in molecular biology and statistics.In the second, empirical part, I introduce an analysis of the demographic characteristics of A. alpina in six natural populations. Besides providing interesting biological information on this species (low life expectancy, strongly contrasted reproduction and survival...), these analyses show that growth increase and survival decrease with the decrease of average temperature (hence with altitude).Since these analyses do not allow us to rule out hypotheses such as drift and phenotypic plasticity, I show the results of a common garden experiment which enable us to smooth phenotypic plasticity and, when combined with molecular data, enable us to rule out the hypothesis of drift.The results show the existence of an adaptive phenotypic syndrome, in which plants are smaller, are more compact, grow slower and reproduce less in cold temperature environments.Using the molecular data, I draw a list of 40 locus which might be involved in this adaptive process.In the end, I discuss these empirical findings as a whole to place them in a more general context of alpine ecology. I sum up the main methodological challenges when studying local adaptation and offer some methodological perspectives

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Laureano, Monyka Marianna Massolini [UNESP]. "Estudo genético quantitativo do fluxo lácteo em bovinos da raça Holandesa." Universidade Estadual Paulista (UNESP), 2008. http://hdl.handle.net/11449/102782.

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Parâmetros genéticos para o fluxo lácteo medido no dia do controle (FLDC) de primeiras lactações de vacas da raça Holandesa foram estimados utilizando modelos de dimensão finita (TDM) e modelos de regressão aleatória. Para os TDM foram analisadas 10 características por meio de modelos uni e bi e multi-características e de repetibilidade, que continham como aleatórios, o efeito genético aditivo e o efeito residual e, como efeitos fixos, o grupo de contemporâneos e as covariáveis idade da vaca ao parto. A variável número de dias em lactação foi incluída somente no modelo de repetibilidade. Para os MRA, foram considerados os efeitos aleatórios genético aditivo direto, de ambiente permanente e o residual. Foram considerados como efeitos fixos, o grupo de contemporâneos, os efeitos linear e quadrático da covariável idade da vaca ao parto e a curva média de lactação da população, modelada por meio de polinômios ortogonais de Legendre de quarta ordem. Os efeitos aleatórios genético aditivo e de ambiente permanente foram modelados por meio de regressão aleatória sobre polinômios ortogonais de Legendre e por meio de funções b-splines. Diferentes estruturas de variâncias residuais foram testadas, por meio de classes contendo 1, 7, 10, 20 e 43 variâncias residuais, para os MRA modelados por meio de polinômios de Legendre. Já, para os MRA modelados por funções b-splines, a estrutura residual foi considerada heterogênea, contendo 7 classes de variâncias. Os MRA foram comparados usando o teste de razão de verossimilhança, o critério de informação de Akaike e o critério de informação de Bayesiano de Schwarz. As estimativas de herdabilidade (h2) para os FLDC variaram de 0,23 a 0,32 nas análises unicaracterísticas, de 0,24 a 0,32 nas bi-características e de 0,28 a 0,37 nas multicaracterísticas. Os valores de h2 estimados variaram no decorrer da...
Flow milk genetic parameters to the first lactation test-day milk yields of Holstein cattle were estimated using Test-day models (TDM) and Random regression models (RRM). Ten TDM differents traits were analyzed using uni, bi and multi-trait and repeatability animal models, that included the additive genetic as random effect and the fixed effects of contemporary group, age of cow (linear and quadratic) as covariables. The days in milk (linear) variable was included only at repeatability model. To RRM were included the additive genetic, permanent environmental and residual as random effects, the fixed effects of contemporary group, age of cow as covariable (linear and quadratic effects) and a 4th-order Legendre orthogonal polynomials of days in milk, to model the mean trend. The additive genetic and permanent environmental effects were fitted by Legendre orthogonal polynomials and b-splines functions. Different structures of residual variances were used, through the variances classes containing 1, 7, 10, 20, and e 43 residual variances, to the models fitted by Legendre orthogonal polynomials. Moreover, for the RRM fitted by b-splines-functions, the residual estructure was considered heterogeneous, having 7 variance classes. The RRM were compared by Likelihood ratio test, Bayesian and Akaike´s information criteria. The heritability estimated ranged from 0.23 to 0.32 by uni-trait analyses, from 0.24 to 0.32 by bi-traits analyses and from 0.28 to 0.37 by multi-trait analyses. The h2 estimates varied during the lactation being the highest estimate at the fourth month. The estimate obtained by the repeatability model was 0.27, and a repeatability estimate of 0.66. For the MRA fitted by Legendre orthogonal polynomials, related to the residual variance, the best model the one that deemed 7 residual classes. For the additive and permanent environmental effects, the having 3th-order... (Complete abstract click electronic access below)

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Kaizik, Stephan Martin. "Analysis of mouse models of insulin secretion disorders." Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:4d44b68a-a0a0-4c92-8809-00ddbfe3e636.

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Sobreira, Fábio Moreira. "Melhor predição linear não viesada (BLUP) multicaracterística na seleção recorrente de plantas anuais." Universidade Federal de Viçosa, 2009. http://locus.ufv.br/handle/123456789/4696.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico
The BLUP methodology, which is widely used in animal and forestry genetic evaluation, can also be applied to annual crop breeding. The objective of this study was to compare the accuracy and efficiency of among- and within-half-sib family selection through the use of multi-trait BLUP, single-trait BLUP and phenotypic selection. Expansion volume and yield data from two recurrent selection cycles of a popcorn population were analyzed. Progeny tests were designed as a lattice. In order to maximize accuracy of the prediction of breeding values, the BLUP analyses included phenotypic values of the two cycles. All statistical analyses were performed using the ASREML software. The multi-trait BLUP method demonstrated greater accuracy and efficiency in family selection. In the case of within-family selection, both accuracy and efficiency of multi-trait or single-trait BLUP methods were equivalent. The selection efficiency of the multi-trait BLUP was dependent on the estimated genetic parameters, particularly the difference between the genetic and environmental correlations of the traits.
A metodologia BLUP, que é amplamente utilizada na avaliação genética animal e florestal também pode ser aplicada no melhoramento de culturas anuais. O objetivo deste estudo foi comparar a acurácia e a eficiência da seleção entre e dentro de famílias de meios-irmãos através da utilização do BLUP multicaracterística, BLUP unicaracterística e seleção fenotípica. Dados de capacidade de expansão e produção de dois ciclos de seleção recorrente em uma população de milho-pipoca foram analisados. Os testes de progênies foram delineados como um látice. Visando maximizar a acurácia da predição dos valores genéticos as análises BLUP incluíram valores fenotípicos dos dois ciclos. Todas as análises estatísticas foram realizadas utilizando o software ASREML. O método BLUP multicaracterística apresentou maior acurácia e eficiência de seleção de famílias. No caso da seleção dentro de famílias a acurácia e a eficiência dos métodos BLUP multicaracterística e BLUP unicaracterística foram equivalentes. A eficiência de seleção do BLUP multicaracterística foi dependente dos parâmetros genéticos estimados, particularmente da diferença entre as correlações genéticas e ambientais das características.

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Schmidt, Peter. "Islet Xenotransplantation : An Experimental Study of Barriers to Clinical Transplantation." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3942.

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40

Méndez-Vera, José. "Understanding how evolution affects the spatial dynamics of interacting species." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS262.

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Les pressions sélectives sur les organismes étant en perpétuel changement, en conséquence de multiples facteurs tels que le changement climatique et l'introduction d'espèces exotiques, il est indispensable d’avoir une meilleure compréhension des dynamiques déterminant les distributions spatiales des espèces. L'évidence empirique montre que les interactions inter-spécifiques et l'évolution peuvent avoir des effets importants sur la distribution des espèces, individuellement ou simultanément. Il est donc nécessaire de disposer de modèles capables de décrire l'effet de ces facteurs afin de mieux comprendre les déterminants des distributions géographiques des espèces dans un monde qui change. Au cours de cette thèse, nous avons étudié les effets de l'adaptation à des gradients environnementaux dans deux scénarios d'interaction: dans un scénario mono-spécifique et dans le cas d'une communauté à deux espèces dont une proie et un prédateur. Dans une troisième partie, nous avons étudié les effets de l'adaptation à des pathogènes dans un scénario d'invasion où trois espèces interagissent : une population native et un compétiteur exotique co-introduit avec un pathogène. Les modèles étudiés révèlent les effets de l'adaptation et de l'interaction à travers des vitesses de propagation éco-évolutives qui dépendent fortement des capacités d'adaptation des espèces considérées. Nous discutons des implications de ces résultats pour la description et l’interprétation des modèles de distribution d'espèces (SDMs) utilisés actuellement
Selective pressures on organisms are constantly changing due to multiple factors, such as climate change and the introduction of exotic species. Empirical evidence shows that interspecific interactions and evolution can have important effects on species distributions, independently or simultaneously. We are thus in need of models capable of describing the effects of both these factors, in order to better understand the drivers of species geographical distributions in a changing world. In this thesis we explored the effects of adaptation to environmental gradients under two different interaction scenarios: in a monospecific context and for a two-species predator-prey community. In a third time, we studied the effects of adaptation to pathogens in an invasion scenario, where three species interact: a native population and an exotic competitor co-introduced with a pathogen. The studied models reveal the effects of adaptation and interaction through eco-evolutionary propagation speeds that are closely linked to the species' adaptation potentials. We discuss implications of these results for description and interpretation of currently utilized Species Distribution Models

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41

Nyh, Johan. "From Snow White to Frozen : An evaluation of popular gender representation indicators applied to Disney’s princess films." Thesis, Karlstads universitet, Institutionen för geografi, medier och kommunikation, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-36877.

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Simple content analysis methods, such as the Bechdel test and measuring percentage of female talk time or characters, have seen a surge of attention from mainstream media and in social media the last couple of years. Underlying assumptions are generally shared with the gender role socialization model and consequently, an importance is stated, due to a high degree to which impressions from media shape in particular young children’s identification processes. For young girls, the Disney Princesses franchise (with Frozen included) stands out as the number one player commercially as well as in customer awareness. The vertical lineup of Disney princesses spans from the passive and domestic working Snow White in 1937 to independent and super-power wielding princess Elsa in 2013, which makes the line of films an optimal test subject in evaluating above-mentioned simple content analysis methods. As a control, a meta-study has been conducted on previous academic studies on the same range of films. The sampled research, within fields spanning from qualitative content analysis and semiotics to coded content analysis, all come to the same conclusions regarding the general changes over time in representations of female characters. The objective of this thesis is to answer whether or not there is a correlation between these changes and those indicated by the simple content analysis methods, i.e. whether or not the simple popular methods are in general coherence with the more intricate academic methods.

Betyg VG (skala IG-VG)

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42

Foster, Scott David. "The LASSO linear mixed model for mapping quantitative trait loci." 2006. http://hdl.handle.net/2440/37868.

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This thesis concerns the identification of quantitative trait loci (QTL) for important traits in cattle line crosses. One of these traits is birth weight of calves, which affects both animal production and welfare through correlated effects on parturition and subsequent growth. Birth weight was one of the traits measured in the Davies' Gene Mapping Project. These data form the motivation for the methods presented in this thesis. Multiple QTL models have been previously proposed and are likely to be superior to single QTL models. The multiple QTL models can be loosely divided into two categories : 1 ) model building methods that aim to generate good models that contain only a subset of all the potential QTL ; and 2 ) methods that consider all the observed marker explanatory variables. The first set of methods can be misleading if an incorrect model is chosen. The second set of methods does not have this limitation. However, a full fixed effect analysis is generally not possible as the number of marker explanatory variables is typically large with respect to the number of observations. This can be overcome by using constrained estimation methods or by making the marker effects random. One method of constrained estimation is the least absolute selection and shrinkage operator (LASSO). This method has the appealing ability to produce predictions of effects that are identically zero. The LASSO can also be specified as a random model where the effects follow a double exponential distribution. In this thesis, the LASSO is investigated from a random effects model perspective. Two methods to approximate the marginal likelihood are presented. The first uses the standard form for the double exponential distribution and requires adjustment of the score equations for unbiased estimation. The second is based on an alternative probability model for the double exponential distribution. It was developed late in the candidature and gives similar dispersion parameter estimates to the first approximation, but does so in a more direct manner. The alternative LASSO model suggests some novel types of predictors. Methods for a number of different types of predictors are specified and are compared for statistical efficiency. Initially, inference for the LASSO effects is performed using simulation. Essentially, this treats the random effects as fixed effects and tests the null hypothesis that the effect is zero. In simulation studies, it is shown to be a useful method to identify important effects. However, the effects are random, so such a test is not strictly appropriate. After the specification of the alternative LASSO model, a method for making probability statements about the random effects being above or below zero is developed. This method is based on the predictive distribution of the random effects (posterior in Bayesian terminology). The random LASSO model is not sufficiently flexible to model most QTL mapping data. Typically, these data arise from large experiments and require models containing terms for experimental design. For example, the Davies' Gene Mapping experiment requires fixed effects for different sires, a covariate for birthdate within season and random normal effects for management group. To accommodate these sources of variation a mixed model is employed. The marker effects are included into this model as random LASSO effects. Estimation of the dispersion parameters is based on an approximate restricted likelihood (an extension of the first method of estimation for the simple random effects model). Prediction of the random effects is performed using a generalisation of Henderson's mixed model equations. The performance of the LASSO linear mixed model for QTL identification is assessed via simulation. It performs well against other commonly used methods but it may lack power for lowly heritable traits in small experiments. However, the rate of false positives in such situations is much lower. Also, the LASSO method is more precise in locating the correct marker rather than a marker in its vicinity. Analysis of the Davies' Gene Mapping Data using the methods described in this thesis identified five non-zero marker-within-sire effects ( there were 570 such effects). This analysis clearly shows that most of the genome does not affect the trait of interest. The simulation results and the analysis of the Davies' Gene Mapping Project Data show that the LASSO linear mixed model is a competitive method for QTL identification. It provides a flexible method to model the genetic and experimental effects simultaneously.
Thesis (Ph.D.)--School of Agriculture, Food and Wine, 2006.

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43

Foster, Scott David. "The LASSO linear mixed model for mapping quantitative trait loci." Thesis, 2006. http://hdl.handle.net/2440/37868.

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Abstract:

This thesis concerns the identification of quantitative trait loci (QTL) for important traits in cattle line crosses. One of these traits is birth weight of calves, which affects both animal production and welfare through correlated effects on parturition and subsequent growth. Birth weight was one of the traits measured in the Davies' Gene Mapping Project. These data form the motivation for the methods presented in this thesis. Multiple QTL models have been previously proposed and are likely to be superior to single QTL models. The multiple QTL models can be loosely divided into two categories : 1 ) model building methods that aim to generate good models that contain only a subset of all the potential QTL ; and 2 ) methods that consider all the observed marker explanatory variables. The first set of methods can be misleading if an incorrect model is chosen. The second set of methods does not have this limitation. However, a full fixed effect analysis is generally not possible as the number of marker explanatory variables is typically large with respect to the number of observations. This can be overcome by using constrained estimation methods or by making the marker effects random. One method of constrained estimation is the least absolute selection and shrinkage operator (LASSO). This method has the appealing ability to produce predictions of effects that are identically zero. The LASSO can also be specified as a random model where the effects follow a double exponential distribution. In this thesis, the LASSO is investigated from a random effects model perspective. Two methods to approximate the marginal likelihood are presented. The first uses the standard form for the double exponential distribution and requires adjustment of the score equations for unbiased estimation. The second is based on an alternative probability model for the double exponential distribution. It was developed late in the candidature and gives similar dispersion parameter estimates to the first approximation, but does so in a more direct manner. The alternative LASSO model suggests some novel types of predictors. Methods for a number of different types of predictors are specified and are compared for statistical efficiency. Initially, inference for the LASSO effects is performed using simulation. Essentially, this treats the random effects as fixed effects and tests the null hypothesis that the effect is zero. In simulation studies, it is shown to be a useful method to identify important effects. However, the effects are random, so such a test is not strictly appropriate. After the specification of the alternative LASSO model, a method for making probability statements about the random effects being above or below zero is developed. This method is based on the predictive distribution of the random effects (posterior in Bayesian terminology). The random LASSO model is not sufficiently flexible to model most QTL mapping data. Typically, these data arise from large experiments and require models containing terms for experimental design. For example, the Davies' Gene Mapping experiment requires fixed effects for different sires, a covariate for birthdate within season and random normal effects for management group. To accommodate these sources of variation a mixed model is employed. The marker effects are included into this model as random LASSO effects. Estimation of the dispersion parameters is based on an approximate restricted likelihood (an extension of the first method of estimation for the simple random effects model). Prediction of the random effects is performed using a generalisation of Henderson's mixed model equations. The performance of the LASSO linear mixed model for QTL identification is assessed via simulation. It performs well against other commonly used methods but it may lack power for lowly heritable traits in small experiments. However, the rate of false positives in such situations is much lower. Also, the LASSO method is more precise in locating the correct marker rather than a marker in its vicinity. Analysis of the Davies' Gene Mapping Data using the methods described in this thesis identified five non-zero marker-within-sire effects ( there were 570 such effects). This analysis clearly shows that most of the genome does not affect the trait of interest. The simulation results and the analysis of the Davies' Gene Mapping Project Data show that the LASSO linear mixed model is a competitive method for QTL identification. It provides a flexible method to model the genetic and experimental effects simultaneously.
Thesis (Ph.D.)--School of Agriculture, Food and Wine, 2006.

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44

Symonds, Victor Vaughan. "Genetic analyses of natural variation in the model plant Arabidopsis thaliana: neutral marker, quantitative genetic, and population genetic approaches." Thesis, 2004. http://hdl.handle.net/2152/1418.

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45

Symonds, Victor Vaughan Lloyd Alan M. "Genetic analyses of natural variation in the model plant Arabidopsis thaliana neutral marker, quantitative genetic, and population genetic approaches /." 2004. http://repositories.lib.utexas.edu/bitstream/handle/2152/1418/symondsv32362.pdf.

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46

Martini, Johannes Wolfgang Robert. "Incorporating Interactions and Gene Annotation Data in Genomic Prediction." Doctoral thesis, 2017. http://hdl.handle.net/11858/00-1735-0000-002E-E4BB-0.

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47

Chen, Yi-Shin, and 陳怡欣. "Genetic Model Construction for Quantitative Traits of Seeds." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/10288278442816608894.

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博士
國立臺灣大學
農藝學研究所
90
An available genetic model for seed with quantitative traits has been established in this study. In this genetic model the total genetic effect of seed quantitative trait had been partitioned into embryo’s nucleus additive effect [d], embryo’s nucleus dominance effect [h], endosperm’s nucleus additive effect [dS], endosperm’s nucleus additive effect [h2S] and cytoplasm’s additive effect [dC]. All these genetic effects are fixed, can be estimated by weighted least square method. Utilizing the practical data of cotton’s seed (Dani & Kohel, 1989), the analytic results indicating the genetic model was suitable to predict the genetic effects those controlled by the genetic materials within the nucleus of embryo and endosperm, simultaneous the inheritable materials contained within cytoplasm. In the processing, we present the genetic model for estimating the components of generation means and genotype environment interaction effects. A method of weighted least square is used to evaluate the parameters and showing this genetic model being able to estimate these effects efficiently. For more advance, consider one genetic model that all the genetic effects being random effects. And according to the numbers of genetic variance components included in the model partition the model into embryo model, endosperm model and full model. From the results analyzed by MINQUE method with different generations data generated by computer simulation, indicating using embryo mode, the estimates of different genetic variance components could fit the presupposition well when the parents’ number is 6. Adopting endosperm model and the parents’ number is 4, most estimates of variance components could fit the assumption well. Only the variance component of maternal dominant effect would be biased with the degree of dominance increasing. Finally, using the full model for the prediction of variance components under the situation of 4 parents, indicated the variance components estimates of embryo additive effect, embryo dominant effect, endosperm additive effect and endosperm dominant effect would be increasing with the degree of dominance raising, but the variance component of maternal additive effect would be underestimated.

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48

Henshaw, Jonathan. "Models of Mating System Evolution: Gamete Competition, Hermaphroditism and Sexual Selection." Phd thesis, 2017. http://hdl.handle.net/1885/135769.

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To understand how mating systems evolve, we depend on both (i) theoretical explanations and predictions, supported by mathematical modelling, and (ii) quantitative tools to test predictions rigorously. This thesis is divided equally between these two aims. The first three papers explore the evolution of mating systems using analytic and simulation models. I begin by considering a long-standing puzzle in marine invertebrate systems: the widespread association between a species' body size, whether it is hermaphroditic or has separate sexes, and its mode of fertilisation (i.e. whether eggs and sperm are released into the water or retained by the adult until fertilisation). I argue that local competition among eggs for fertilisation can explain these patterns, which arise in taxa as diverse as sea stars, corals and polychaete worms (Paper 1). I then turn to egg trading – the alternating exchange of egg parcels during mating by simultaneous hermaphrodites – which is one of the best-supported cases of reciprocity between non-relatives. I show that egg trading is under positive frequency-dependent selection and should evolve most easily when potential mates are encountered frequently (Paper 2). Once evolved, egg trading selects for female-biased sex allocation. I explain how this bias allows simultaneous hermaphroditism to persist stably, even in motile species living at high population densities, where simultaneous hermaphroditism is otherwise predicted to be unstable (Paper 3). These three papers contribute to the resolution of Williams' paradox – the mismatch between the empirical distribution of hermaphroditism and our theoretical expectations – by providing finer-grained predictions for when hermaphroditism should occur. The last three papers provide quantitative tools for the measurement of natural (and particularly sexual) selection. I argue that pre-mating sexual selection should be understood as a two-step causal process: traits affect mating success, which in turn affects reproductive success. Most previous work has focussed too narrowly on one or the other of these steps, leading to confusion about what sexual selection is and how we should measure it. I provide a new statistical framework that integrates both steps in the sexual selection pathway, and includes a third path whereby traits directly affect reproductive success. This leads to better estimates of the strength of sexual selection on traits (Paper 4). I then compare various indices of sexual selection, often used in comparative work, that do not rely on trait measurements. I show that the recently defined Jones index outperforms all others in predicting the actual strength of sexual selection, because it accounts for both steps in the sexual selection pathway (Paper 5). Lastly, I provide a new way to quantify the total selection acting on a trait, including both directional and non-directional selection (Paper 6).

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49

Sanyal, Anushree. "Genetic analyses of adaptive evolution in seed oil composition in the model plant Arabidopsis thaliana : a quantitative genetic approach." Thesis, 2010. http://hdl.handle.net/2152/ETD-UT-2010-08-1650.

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Natural variation in the relative proportions of saturated and unsaturated fatty acids in seed oils of plants is enormous when considered across a broad taxonomic range of oil seeds. It has been shown that this variation follows a latitudinal cline where the proportions of unsaturated fatty acids increases with increasing latitude as the unsaturated fatty acids in seeds provide energy at a faster rate to germinating seeds at higher latitudes. This variation which follows a latitudinal cline suggests that there may be an adaptive role for this variation. We tested this hypothesis in Arabidopsis thaliana which followed the same trend seen in Helianthus and other angiosperms. In order to understand the underlying genetics of the regulation of the relative proportions of fatty acids and their role in plant evolution, we mapped quantitative trait loci (QTLs) and candidate genes. Here we identified 67 major QTLs responsible for fatty acid synthesis in A. thaliana in Ler-0 x Sha, Ler-0 x Col-4, Ler-2 x Cvi and Ler-0 x No-0 RIL populations. Eight candidate genes were identified based on what is known about seed oil biosynthesis in A. thaliana. Six of the candidate genes collocated to most of the major QTLs. In order to demonstrate that a particular allelic variant is indeed causally related to the phenotype, we investigated DNA polymorphisms in the parental and the RIL line alleles of the collocating candidate genes. Single nucleotide polymorphisms (SNPs) were identified in the collocating candidate genes to study the correlation between the sequence variants and the particular phenotype. We identified 232 SNPs with 77 in the putative regulatory regions upstream of the 5’UTR, 61 in the introns, 18 in the 5’UTR regions, 2 in the 3’UTR regions, and 45 occurring in the exons with 10 non-synonymous substitutions affecting the amino acid residues. We also detected 44 insertions/deletions in the coding, non-coding, 5’UTR, 3’UTR and the regulatory regions. Sequence variation in the fatty acid genes due to SNPs and insertions/deletions should be valuable in tests of association to investigate how the relative proportions of saturated and unsaturated fatty acids are regulated in wild plants and what role they have played in plant evolution and also in breeding oil seed crops that are healthier or have two types of fatty acids in proportions appropriate for different uses.
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50

Chen, Yen-Chih. "A New Quantitative Structure-Activity Relationship Model for Practical Applications using Hierarchical Clustering Genetic Algorithms." 2004. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-2707200402254400.

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Dissertations / Theses on the topic 'Quantitative Genetics Model'

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