Genomic selection to resistance to Stenocarpella maydis in maize lines using DArTseq markers.
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.



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.



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.
Department of Biology, Federal University of Lavras, Lavras, MG, CP 3037, Brazil.
Jhonathan Pedroso Rigal
JP
Dos Santos
Department of Agriculture, Federal University of Lavras, Lavras, MG, CP 3037, Brazil.
Luiz Paulo Miranda
LP
Pires
Department of Biology, Federal University of Lavras, Lavras, MG, CP 3037, Brazil.
Renato Coelho
RC
de Castro Vasconcellos
Department of Biology, Federal University of Lavras, Lavras, MG, CP 3037, Brazil.
Gabriela Santos
GS
Pereira
Department of Agriculture, Federal University of Lavras, Lavras, MG, CP 3037, Brazil.
Renzo Garcia
RG
Von Pinho
Department of Exact Science, Federal University of Lavras, Lavras, MG, CP 3037, Brazil. marciobalestre@dex.ufla.br.
Marcio
M
Balestre
D001203:Ascomycota / Q000502:physiology*; D060467:Disease Resistance; D059647:Gene-Environment Interaction; D010935:Plant Diseases / Q000235:genetics* / Q000276:immunology*; D025341:Principal Component Analysis; D003313:Zea mays / Q000235:genetics* / Q000276:immunology*
Bayesian stochastic search variable; Ear rot; Genetic groups; Ridge regression best linear unbiased prediction