Sugarcane is among the most important crops in the world, specially in developing countries. However, the complex polyploid structure of its genome is not well understood. In the recent years, many research groups have been making tremendous efforts to identify loci that control genotypic variation in quantitative traits (QTLs). Despite all advances in the development of models for QTL mapping in tetraploids, the vast majority of the models used for QTL mapping in species with high ploidy level, such as sugarcane, are approximations of those used in diploid organisms. In this context, this project has three scientifically relevant objectives: i) develop new models for QTL mapping in species with high ploidy levels; ii) implement these models in an open-source software in R statistical environment; iii) use the new models to map QTLs for agronomically important traits in sugarcane, using SNP markers. Thus, it is expected to be able to study the effects of allelic dosage precisely, as well as dominance and epistatic effects. Furthermore, it is expected that the inclusion of such effects in the mapping model, will provide more accurate and realistic estimates of QTLs than previously reported in literature. In order to perform the analyzes, the SNPs will be classified using a Bayesian approach with the software SuperMASSA, of which the applicant is co-author. A genetic map will be constructed using the model based on hidden Markov chains, as proposed by the applicant in his doctoral thesis. The models that are proposed in this project will be based models for QTL mapping in polyploids available in literature, however many theoretical developments are needed before such models contemplate co-dominant markers (such as SNPs) and high ploidy levels. The results of this project should provide important information for understanding the genetic architecture of species with higher ploidy levels, such as sugarcane.
News published in Agência FAPESP Newsletter about the scholarship: