Prediction of breeding values in sugarcane using pedigree and genomic information

• Ano de defesa: 2015
• Autor(a) principal: Costa, Paulo Mafra de Almeida
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa
• Palavras-chave em Português: Cana-de-açúcar - Melhoramento genético - Métodos estatísticos; Cana-de-açúcar - Seleção; Genética vegetal; Variabilidade (Genética); Marcadores moleculares; Melhoramento Vegetal
• Link de acesso: http://www.locus.ufv.br/handle/123456789/7539

The development of genomic tools for speed up sugarcane breeding has been delayed compared to other major crops, therefore, empirical studies must be conducted to evaluate the usefulness of this approach on this important crop. The objectives of our study were: i) to assess the accuracy of prediction of four quantitative traits using genomic information of SNP markers in a commercial sugarcane breeding population; ii) to compare the accuracy between predictions using pedigree and genomic information. Genetic values were predicted in a second phase trial population of 514 individuals genotyped with 37,024 SNP markers. Five statistical predictive models were evaluated: Genomic BLUP (GBLUP), Bayesian LASSO (BL), Bayes A (BA), Bayes B (BB) and Bayesian Ridge Regression (BRR). Accuracies of the methods were assessed through the correlation between observed and predicted genetic values in a lO-fold cross validation. The methods exhibited very similar accuracy values regarding the trait. Nevertheless, there were marked differences among traits. The highest accuracy was obtained for FB by the BRR method (0.57) and the lowest was obtained for TPH by Bayes B method (0.07). Two models (pedigree - P and pedigree + genomic - P+G) were fitted and used to predict the traits in order to compare the prediction accuracy using pedigree and genomic information. Overall, P+G exhibited higher correlation values, as well as lower standard deviation, except for the traits TSH and TPH. Genomic information explained higher proportion of the genetic variance in comparison to the pedigree. Satisfactory accuracies were obtained by using genomic information, especially for pol percentage in sugarcane and fiber percentage in bagasse. Thus, the use of genomic information could be more efficient per unit of time for improvement of desirable agronomic traits in a complex polyploid crop.