Navegando por Autor "Silva, Fabyano Fonseca e"
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Item Avaliação de curvas de crescimento morfométrico de linhagens de tilápia do nilo (Oreochromis niloticus)(2007) Santos, Vander Bruno dos; Freitas, Rilke Tadeu Fonseca de; Silva, Fabyano Fonseca e; Freato, Thiago ArchangeloThe objective of this research was to evaluate the morphometric growth curves of tilapia strains in function of the body weight, an experiment was carried out at the Fish Culture of the Animal Sciences Department, Federal University of Lavras, M.G-Brazil. Three hundred sixty-two (362) fish of the Chitralada strain and three hundred forty-five (345) of the Supreme strain, weighting between 1,7 and 800 g were used. With the animals' growth, random samples were taken; the fish were slaughtered, weighted and submitted morphometric evaluation. Different models of growth of body measurements in function of the body weight were fitted. In general, the measurements were adequately adjusted. Shorts differences were found between the fit of the models for limiting values (A) and high differences for growth rate relative the maturity (K) for all the measurements. The Brody and Logistic models had higher differences than Gompertz and von Bertalanffy that stayed in intermediary position. The Supreme strain had "A" for standard length (SL) slightly higher and for body height slightly smaller than Chitralada strain. The Chitralada strain had higher "K" for head length/standard lenght relation than Supreme strain. The Gompertz, Brody, von Bertallanffy e Logistic models described adequately the morphometric growth of tilapia in function of body weight, being more indicate the models Gompertz and von Bertalanffy. The differences between Chitralada and Supreme tilapia strains were small. Com o objetivo de avaliar curvas de crescimento morfométrico de linhagens de tilápias em função dos pesos de abate, um experimento foi conduzido no setor de piscicultura da Universidade Federal de Lavras, M.G.- Brasil. Foram avaliados 362 peixes da linhagem Chitralada e 345 da Supreme, pesando entre 1,7 e 800 g. Com o crescimento dos animais, amostras aleatórias foram tomadas, sendo os peixes abatidos, pesados e submetidos à avaliação morfométrica. Foram ajustados diferentes modelos de crescimento de medidas corporais em função do peso de abate. Pequenas diferenças entre os ajustes dos modelos foram encontradas para o valor assintótico (A) e grandes diferenças para a taxa de crescimento relativo à maturidade (K) para todas as medidas. Os modelos de Brody e Logístico apresentaram maiores diferenças, ficando os modelos de Gompertz e von Bertalanffy em posição intermediária. A linhagem Supreme obteve valores de "A" ligeiramente maiores, para o comprimento padrão (CP), e ligeiramente menores, para a altura do corpo, em relação aos valores obtidos pela linhagem Chitralada, e essa apresentou maior "K" para a relação comprimento da cabeça/comprimento padrão. Conclui-se que os modelos não lineares de Gompertz, Brody, von Bertalanffy e Logístico descrevem adequadamente o crescimento morfométrico de tilápias do Nilo em função do peso corporal, sendo mais indicados os modelos de Gompertz e von Bertalanffy, tanto para a linhagem Chitralada quanto para a Supreme, considerando que foram pequenas as diferenças existentes entre as duas linhagens.Item Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves(2017) Silva, Fabyano Fonseca e; Zambrano, Maria Fernanda Betancur; Varona, Luis; Glória, Leonardo Siqueira; Lopes, Paulo Sávio; Silva, Marcos Vinícius Gualberto Barbosa; Arbex, Wagner; Lázaro, Sirlene Fernandes; Resende, Marcos Deon Vilela de; Guimarães, Simone Eliza FacioniABSTRACT: Genome association analyses have been successful in identifying quantitative trait loci (QTLs) for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs (simultaneously affecting A and K) allows us to make inferences with regards to their contribution to the pig growth process in the population studied.Item Genome association study through nonlinear mixed models revealed new candidate genes for pig growth curves(2017) Silva, Fabyano Fonseca e; Zambrano, Maria Fernanda Betancur; Varona, Luis; Glória, Leonardo Siqueira; Lopes, Paulo Sávio; Silva, Marcos Vinícius Gualberto Barbosa; Arbex, Wagner; Lázaro, Sirlene Fernandes; Resende, Marcos Deon Vilela de; Guimarães, Simone Eliza FacioniABSTRACT: Genome association analyses have been successful in identifying quantitative trait loci (QTLs) for pig body weights measured at a single age. However, when considering the whole weight trajectories over time in the context of genome association analyses, it is important to look at the markers that affect growth curve parameters. The easiest way to consider them is via the two-step method, in which the growth curve parameters and marker effects are estimated separately, thereby resulting in a reduction of the statistical power and the precision of estimates. One efficient solution is to adopt nonlinear mixed models (NMM), which enables a joint modeling of the individual growth curves and marker effects. Our aim was to propose a genome association analysis for growth curves in pigs based on NMM as well as to compare it with the traditional two-step method. In addition, we also aimed to identify the nearest candidate genes related to significant SNP (single nucleotide polymorphism) markers. The NMM presented a higher number of significant SNPs for adult weight (A) and maturity rate (K), and provided a direct way to test SNP significance simultaneously for both the A and K parameters. Furthermore, all significant SNPs from the two-step method were also reported in the NMM analysis. The ontology of the three candidate genes (SH3BGRL2, MAPK14, and MYL9) derived from significant SNPs (simultaneously affecting A and K) allows us to make inferences with regards to their contribution to the pig growth process in the population studied.