Submitted by DIEGO GABRIEL TORRES DINI null (diego.torres.dini@gmail.com) on 2017-02-25T21:08:29Z No. of bitstreams: 1 Diego Torres Dini Tese Doutoral.pdf: 1232376 bytes, checksum: dc45dfe7c23a8fd647db24acb963c71c (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-03-07T13:42:52Z (GMT) No. of bitstreams: 1 torresdini_dg_dr_ilha.pdf: 1232376 bytes, checksum: dc45dfe7c23a8fd647db24acb963c71c (MD5) / Made available in DSpace on 2017-03-07T13:42:52Z (GMT). No. of bitstreams: 1 torresdini_dg_dr_ilha.pdf: 1232376 bytes, checksum: dc45dfe7c23a8fd647db24acb963c71c (MD5) Previous issue date: 2017-02-03 / Outra / In Uruguay, reforestation with Eucalyptus sp. is of fundamental importance to produce paper, pulp and wood. The productivity of these continually grows due to application of breeding techniques, such as hybridization. This study aimed to investigate genetic parameters, productivity, stability, adaptability and to identify SNP markers associated with the diameter breast height (DBH) for to select Eucalypts grandis x Eucalyptus globulus full-sibs hybrid clones. The study was conducted in a clonal test, repeated at two different soils, in the state of Rio Negro, Uruguay. The population was phenotypically characterized to the DBH at 48 months of age and cambium tissues of each individual were sampled for genotyping with EuCHIP60K chip. The mean growth in DBH was similar between both places. The genotype-environment interaction was the simple type, with high genotype correlation in clones’ performance between environments (0.708), indicating the possibility of the same clones being selected for both places. Mean heritability between clones (0.724), coefficient of individual genetic variation (10.9%) and relative variation (0.916), showed the possibility of obtaining gains by selecting clones with higher growth, which was estimated in 3.1% for both sites together. A total of 15,196 markers SNPs were used in the genomic selection for the DBH, but after cleaning of SNPs data, the number was reduced for 15,196 (23.5%). The predictive capacity was expected to be low or negative (-0.15) for this population given the population size (78 individuals). We used the model rrBLUP with a validation of Jackknife. The model do not showed precision to predict the DBH. These results were consistent with theoretical expectations, which indicate that it is necessary to have an improvement population of at least 1,000 phenotyped and genotyped individuals. The DBH is the most important trait in the breeding of the genus Eucalyptus. However its quantitative nature added to the time necessary for this phenotype to develop makes the early detection of this trait are difficult. The identification of molecular markers associated with quantitative phenotypes is a good choice for the identification of QTLs that will help the early detection of individuals with high DBH. Significant markers associated to DBH , were indentificated into the chromosome 6, suggesting the presence of a QTL in this chromosome. Since they are clones originated from vegetative propagation and a full-sibs single-progeny, they should preferably be used for reforestation based on their cloning, since mating between clones can generate endogamy by biparental inbreeding. The utilization of SNPs helped to confirm the degree of parentage between the clones as well as clonal identity control.

Amaranth (Amaranthus caudatus L.) is an important pseudocereal in the Andes. The seed has excellent nutritional value (high in protein, essential amino acids, and minerals) and ample capacity for growth in diverse, harsh Andean subsistence-production conditions such as water deficiency, salt stress, and soil mineral nutrient deficiency. The objective of this study was to characterize and quantify the genetic diversity among a series of 178 mostly Peruvian amaranth genotypes using 96 biallelic single-nucleotide polymorphism (SNP) markers. A total of 96 co-dominant, biallelic markers were developed using KASPar™ assays on a 96.96 Fluidigm EP1 array system. The 178 amaranth genotypes included white-opaque and white-translucent (vitreous) putative A. caudatus seed types, along with black-seeded A. hybridus and brown-seeded types, all isolated from among 48 accessions of the CICA-UNSAAC collection. Variation among and within samples and accessions was compared for empirically determined clusters (northern, north-central, south-central, and southern Peruvian Andes). Variation was highest within samples for all groups, but only in white-seeded amaranth was the p-value significant (17.43). The greatest variation among samples was found in the vitreous-seeded group (99.35). The highest average observed heterozygosity within-groups (Ho) was 0.19 in the brown-seeded group, and expected within-group heterozygosity (He) was highest in the vitreous-seeded group (0.359). Cluster analysis (UPGMA), PCA and PCO results partitioned the amaranth accessions into six discrete clusters. Clusters did not manifest obvious structure among accessions, which indicates that genetic diversity has been conserved across a broad region of the Peruvian Andes. The diversity characterization pointed to a center of origin and domestication of A. caudatus in the Ayacucho-Cusco region of southern Peru.

Made available in DSpace on 2015-03-26T13:32:12Z (GMT). No. of bitstreams: 1 texto completo.pdf: 4537549 bytes, checksum: 620653542527fa7feaefde5219b6a878 (MD5) Previous issue date: 2011-06-20 / The main contribution of molecular genetics to the benefit of applied genetic breeding is the direct use of the DNA data in genomic selection, allowing high selective efficiency and speed in the acquisition of genetic gains in selection and low costs. A practical and consistent way of analyzing the productive efficiency of beef animals subjected to selection is through the study of growth curves, as these represent a longitudinal trajectory of the weights of the animals in function of time. Thus, firstly, growth models (non-linear models) are adjusted to the weight-age data of each animal submitted to selection and the parameters estimated as phenotypes are considered. This procedure permits to determine genetic parameter estimates for any growth trajectory point, and to understand the genetic architecture of the entire trajectory, since all the weighing information is condensed by these few biologically interpretable parameters. The parameters estimated from the growth models are used to predict the Genomic Breeding Value (GBV) by means of specific statistical methods for the Genome Wide Selection (GWS). The general objective of this work was to apply statistical methods used in the Genome Wide Selection, mainly RRBLUP/ GWS and the Bayesian LASSO on the study of animal growth curves, considering as phenotypic variables the estimates of the parameters of non-linear regression models. The specific objectives were: to estimate the genomic breeding values for each individual evaluated; to estimate the effect of SNP markers and to identify those with the greatest effects; to select, via grouping techniques, groups of individuals genetically superior, in relation to the growth curve; and to validate all the methodology used via simulation study and apply it to real data of an F2 population of swine originated from the cross of two males from the naturalized Brazilian race Piau with 18 females of a commercial line (Landrace × Large White × Pietrain).The results indicated that the Genome Wide Selection statistical methods were efficient in studying the growth curves, considering simulated and real swine weight-age data. GWS presented high accuracy in the selection of the growth curve trajectory, allowing the detection of the QTLs (Quantitative Trait Loci) for the curve parameters of the individuals studied. In the absence of genes of significant effect, the methods RR-BLUP/GWS and Bayesian LASSO showed similar results but the latter showed more efficiency when the halothane gene, characterized as of significant effect, was included as a marker in the analyses. / O principal atrativo da genética molecular em benefício do melhoramento genético aplicado é a utilização direta das informações do DNA na seleção genômica, de modo a permitir alta eficiência seletiva, rapidez na obtenção de ganhos genéticos com a seleção e baixo custo. Uma forma prática e consistente de analisar a eficiência produtiva de animais de corte sujeitos à seleção é por meio dos estudos de curvas de crescimento, pois estas representam uma trajetória longitudinal dos pesos dos animais em função do tempo. Para isso, primeiramente ajustam-se modelos de crescimento (modelos não lineares) aos dados de peso-idade de cada animal submetido à seleção e consideram-se os parâmetros estimados como fenótipos. Este procedimento permite a obtenção de estimativas de parâmetros genéticos para qualquer ponto da trajetória de crescimento e possibilita a compreensão da arquitetura genética de toda a trajetória, uma vez que as informações de todas as pesagens são condensadas por esses poucos parâmetros interpretáveis biologicamente. Em seguida, os parâmetros estimados dos modelos de crescimento são utilizados para predizer os Valores Genéticos Genômicos (Genomic Breeding Value – GBV) por meio de métodos estatísticos específicos para a Seleção Genômica ix Ampla (Genome Wide Selection – GWS). O objetivo geral do presente trabalho foi empregar métodos estatísticos usados na Seleção Genômica Ampla, especificamente o RR-BLUP/GWS e o LASSO Bayesiano, no estudo de curvas de crescimento animal, considerando como variáveis fenotípicas as estimativas dos parâmetros de modelos de regressão não linear. Os objetivos específicos foram: estimar valores genéticos genômicos para cada indivíduo avaliado; estimar efeitos de marcadores SNPs e identificar os de maiores efeitos; selecionar, via técnicas de agrupamento, grupos de indivíduos geneticamente superiores em relação à curva de crescimento; e validar toda metodologia utilizada via estudo de simulação e aplicá-la a dados reais de uma população F2 de suínos proveniente do cruzamento de dois varrões da raça naturalizada brasileira Piau com 18 fêmeas de linhagem comercial (Landrace × Large White × Pietrain). Os resultados indicaram que os métodos estatísticos na Seleção Genômica Ampla foram eficientes no estudo de curvas de crescimento, considerando dados simulados e dados reais de peso-idade de suínos. A GWS apresentou alta acurácia na seleção para a trajetória das curvas de crescimento e possibilitou a detecção de QTLs (Quantitative Trait Loci) para os parâmetros da curva dos indivíduos considerados. Na ausência de genes de grande efeito, os métodos RRBLUP/ GWS e LASSO Bayesiano produziram resultados semelhantes, no entanto o método LASSO Bayesiano apresentou maior eficiência quando o gene halotano, caracterizado como de grande efeito, foi incluído como marcador nas análises.

Orientador: Alexandre Magno Sebbenn / Resumo: In Uruguay, reforestation with Eucalyptus sp. is of fundamental importance to produce paper, pulp and wood. The productivity of these continually grows due to application of breeding techniques, such as hybridization. This study aimed to investigate genetic parameters, productivity, stability, adaptability and to identify SNP markers associated with the diameter breast height (DBH) for to select Eucalypts grandis x Eucalyptus globulus full-sibs hybrid clones. The study was conducted in a clonal test, repeated at two different soils, in the state of Rio Negro, Uruguay. The population was phenotypically characterized to the DBH at 48 months of age and cambium tissues of each individual were sampled for genotyping with EuCHIP60K chip. The mean growth in DBH was similar between both places. The genotype-environment interaction was the simple type, with high genotype correlation in clones’ performance between environments (0.708), indicating the possibility of the same clones being selected for both places. Mean heritability between clones (0.724), coefficient of individual genetic variation (10.9%) and relative variation (0.916), showed the possibility of obtaining gains by selecting clones with higher growth, which was estimated in 3.1% for both sites together. A total of 15,196 markers SNPs were used in the genomic selection for the DBH, but after cleaning of SNPs data, the number was reduced for 15,196 (23.5%). The predictive capacity was expected to be low or negative (-0.15)... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor