Long-term selection of biparental crosses: a comparison among genomic methods and phenotypic selection

• Ano de defesa: 2019
• Autor(a) principal: Nalin, Rafael Storto
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Triticum spp. L.; Computer simulation; Long-term selection; Predição de cruzamentos; Prediction of crosses; Seleção à longo prazo; Simulação computacional
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/11/11137/tde-04092019-103351/

The selection of crosses is a fundamental part of a breeding program, and the use of an adequate strategy is crucial. A good strategy should balance the selection of the best individuals and maintenance of genetic diversity throughout cycles of breeding, aiming for long-term genetic gains. Among the methods proposed in the literature, we can highlight the genomic prediction with simulated offsprings, which can be used to estimate the mean and genetic variance of each combination of candidate parents, providing useful information to the breeder. However, as far as we know, there are no reports on how this method performs concerning long-term genetic gain. Thus, the goal of this study was to evaluate how genomic prediction with simulated offsprings performs compared with the traditional phenotypic selection across five cycles of breeding. In silico and data-based simulation was used to investigate these approaches in terms of genetic gain and several other parameters related to the genetic diversity. We simulated an In silico standard wheat breeding program, with a capacity to evaluate 1000 lines per cycle. We considered different scenarios for the heritability, number of populations and the number of offspring per population. A real dataset of 1465 wheat inbred lines was also used to perform simulations. In this case, markers were randomly assigned to be genes. The results indicated that the best method is dependent of the heritability of the trait under consideration, the breeder\'s strategy about how many crosses will be done and also if the breeding goal is to have short or long-term genetic gains. In general, the genomic methods, especially the genomic prediction with simulated progenies, presented the best results under scenarios of low heritability and high number of population, either on short or long-term. However, even though the conversion of genetic variability into genetic gains is faster than any other strategy, the losses of variability are also higher, being interesting to bring new sources of variability with the advance of the cycles of breeding. The adoption of the restriction on the number of times a genotype is a parent in crosses is also of fundamental importance for obtaining long-term genetic gains.