RESUMO
The identification of causal regions associated with resistance to Fusarium verticillioides can be useful to understand resistance mechanisms and further be used in breeding programs. In this study, a genome-wide association study (GWAS) was conducted to identify candidate markers associated with resistance to the ear rot caused by the fungus F. verticillioides. A total of 242 maize inbred lines were genotyped with 23,153 DArT-seq markers. A total of 12 DArTs were associated with ear rot resistance. Some DArTs were localized close to genes with functions directly related to ear rot resistance, such as a gene responsible for the innate immune response that belongs to the class of NBS-LRR receptors. Some markers were also found to be closely associated with genes that synthesize transcription factors (nactf11 and nactf61), genes responsible for the oxidation-reduction process and peroxidase activity. These results are encouraging since some candidate markers can present functional relationship with ear rot resistance in maize.
Assuntos
Resistência à Doença/genética , Genoma de Planta , Zea mays/genética , Fusarium/patogenicidade , Loci Gênicos , Marcadores Genéticos , Zea mays/imunologia , Zea mays/microbiologiaRESUMO
BACKGROUND: The identification of lines resistant to ear diseases is of great importance in maize breeding because such diseases directly interfere with kernel quality and yield. Among these diseases, ear rot disease is widely relevant due to significant decrease in grain yield. Ear rot may be caused by the fungus Stenocarpella maydi; however, little information about genetic resistance to this pathogen is available in maize, mainly related to candidate genes in genome. In order to exploit this genome information we used 23.154 Dart-seq markers in 238 lines and apply genome-wide selection to select resistance genotypes. We divide the lines into clusters to identify groups related to resistance to Stenocarpella maydi and use Bayesian stochastic search variable approach and rr-BLUP methods to comparate their selection results. RESULTS: Through a principal component analysis (PCA) and hierarchical clustering, it was observed that the three main genetic groups (Stiff Stalk Synthetic, Non-Stiff Stalk Synthetic and Tropical) were clustered in a consistent manner, and information on the resistance sources could be obtained according to the line of origin where populations derived from genetic subgroup Suwan presenting higher levels of resistance. The ridge regression best linear unbiased prediction (rr-BLUP) and Bayesian stochastic search variable (BSSV) models presented equivalent abilities regarding predictive processes. CONCLUSION: Our work showed that is possible to select maize lines presenting a high resistance to Stenocarpella maydis. This claim is based on the acceptable level of predictive accuracy obtained by Genome-wide Selection (GWS) using different models. Furthermore, the lines related to background Suwan present a higher level of resistance than lines related to other groups.