Estudo de associação genômica ampla para produtividade em arroz (Oryza sativa L.)

• Autor(a) principal: Pantalião, Gabriel Feresin
• Data de Publicação: 2016
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/6135
• topic: Oryza sativa L.; Produtividade; SNP; GWAS; Seleção assistida por marcadores; Yield; Marker assisted selection; SILVICULTURA::GENETICA E MELHORAMENTO FLORESTAL

Cultivated rice (Oryza sativa L.) is one of the most important cereal for feeding. It is estimated that the demand for rice grains increases considerably in a reduction scenario of cultivable area and scarcity of water resources, which will require an increase in production compared to current levels. To solve this problem, a viable alternative would be the exploitation of genetic diversity available in rice germplasm banks. Rice breeding programs should prioritize the search for new strategies to increase yield in a variety of environmental conditions. The exploitation of genetic diversity allowed the identification of favorable alleles not present in the germplasm of rice varieties used in breeding programs, as well as obtaining new allelic combinations of genes related to important agronomic traits and that could significantly contribute to the achievement of more productive cultivars. In this context, genome-wide association studies (GWAS) are designed to analyze variations in the DNA sequence of the entire genome in an effort to identify associations with phenotypic traits of interest. It is expected, therefore, that the results of the GWAS analysis, together with the improvements obtained with the next generation sequencing technologies (NGS) in search of a large number of SNPs, such as genotyping by sequencing (GBS), be used to investigate the genetic control of traits related to yield. This study aimed to identify genomic regions of rice related to yield from the GWAS methodology using genotypes of Embrapa Rice Core Collection (ERiCC). The GWAS analysis was conducted from a panel of 550 accessions of the ERiCC, and after the imputation of raw data, were accounted 445,589 SNPs distributed along the 12 rice chromosomes. The molecular information was integrated with phenotypic data derived from yield evaluation experiments conducted in nine essays, divided into two cultivation systems (irrigated and rainfed) and three agricultural years (2004/2005, 2005/2006 and 2006/2007). From the joint analysis in all experiments, 31 SNPs were significantly associated with yield, but only three had the lowest frequency allele with positive effect. The joint analysis of irrigated experiments identified three SNPs associated with yield, of which one with lower frequency allele with a positive effect, whereas in the rainfed experiments was identified only one SNP with lower frequency allele associated to positive effect. Subsequently, a stepwise regression analysis was performed to keep in the model only SNPs without overlapping effects, so being selected 15 SNPs markers. After in silico analysis, it was found that the most productive accessions showed 80 to 100% of favorable alleles while the less productive showed 27 to 33% of favorable alleles. For this set of markers to be used in an assisted selection routine, they should also be validated in the laboratory. In the total joint analysis, from 44 genes identified, 14 had no particular function, while from the joint analysis of experiments irrigated and rainfed, from the six genes, only one had no particular function. The search for Arabidopsis homologues genes in the 15 unknown function rice genes resulted in four genes with known function. The expressed products of the set of genes were related to metabolic processes, response to biotic, abiotic, endogenous and external stimulus, post- embryonic multicellular development, growth and morphogenesis, which influence the number of grains, grains weight and photosynthetic capacity, all related to rice yield and be useful in indicating candidate genes to cloning and transformation, enabling the development of genetically superior rice cultivars. Among the genes identified as associated to productivity, nine were previously described in the literature, and of these, six were related proteins that influence the number and seed weight, and photosynthetic capacity: LOC_Os02g44290.1, LOC_Os04g35370.1, LOC_Os02g44260.1, LOC_Os02g44280 .1 LOC_Os09g36230.1 and LOC_Os01g66160.1. These genes are considered as candidates for cloning and transformation of rice, in order, through its overexpression, enable the development of higher yielding rice cultivars.