Genetic diversity and coefficient of parentage between clones and sugarcane varieties in Brazil

The success of the development of new sugarcane varieties is associated with the ability to correctly select the genitor. The aim of this study was to evaluate the genetic diversity between 113 clones and sugarcane varieties using the Ward-modified location model procedure with added information about the coefficient of parentage and endogamy. In this study, data was used from 100 experiments that evaluated clones; the experimental phase was conducted in 70 places between the years 2002 and 2009 on the outlining in random blocks. According to the diversity analysis, 3 groups formed: G1, G2, and G3, which were composed of 58, 8, and 47 genotypes, respectively. The clones of groups G1 and G3 were the most outstanding. Thus, biparental crossbreeding involving clones and varieties of these 2 groups can efficiently obtain transgressive genotypes. Knowledge of the heterotypic groups indicated by the Ward-modified location model method, along with the parentage information, will make it a lot easier to define the desirable and undesirable crossbreeds for public and private breeding programs that develop sugarcane varieties

Seleção genômica ampla para curvas de crescimento

Foi proposta uma metodologia para avaliação genética de curvas de crescimento considerando-se informações de marcadores SNPs (Single Nucleotide Polymorphisms). Em um primeiro passo foram ajustados modelos de crescimento não lineares (logístico) aos dados de peso-idade de cada animal, e em um segundo passo as estimativas dos parâmetros de tais modelos foram consideradas como fenótipos em um modelo de regressão (LASSO Bayesiano – BL) cujas covariáveis foram os genótipos dos marcadores SNPs. Este enfoque possibilitou estimar os valores genéticos genômicos (GBV) para peso em qualquer tempo da trajetória de crescimento, refletindo na confecção de curvas de crescimento genômicas, as quais permitiram a identificação de grupos de indivíduos geneticamente superiores em relação à eficiência de crescimento. Os dados simulados utilizados neste estudo foram constituídos de 2000 indivíduos (1000 na população de treinamento e 1000 na população de validação) contendo 453 marcadores SNPs distribuídos sobre cinco cromossomos. Os resultados indicaram a alta eficiência do método BL em predizer GBVs da população de validação com base na população de treinamento (coeficientes de correlação variaram entre 0,79 e 0,93), bem como a alta eficiência na detecção de QTLs, uma vez que os marcadores com maiores efeitos estimados encontravam-se em posições dos cromossomos próximas àquelas nas quais se encontravam os verdadeiros QTLs postulados na simulação.A methodology was proposed for the genetic evaluation of growth curves considering SNP (Single Nucleotide Polymorphisms) markers. At the first step, nonlinear regression growth models (Logistic) were fitted to the weight-age of each animal, and on second step the parameter estimates of the Logistic model were used as phenotype in a regression model (Bayesian LASSO - BL) which covariates were given by SNP genotypes. This approach allows the estimation of GBV (Genomic Breeding Values) for weight at either time of growth trajectory, allowing also the production of genomic growth curves, which selected groups of individuals with larger growth efficiency. The simulated data set was constituted of 2,000 individuals (being 1,000 in the training and 1,000 in the validation population) each one with 453 SNP markers distributed along 5 chromosomes. The results indicated high efficiency of the BL method to predict GBV in the validation population using information from the training population (correlation coefficients varying between 0.79 and 0.93). The BL also presented high efficiency to detect QTL, once the most expressive estimated SNP effects were located at positions closed to true QTL position fixed in the simulation