415-11 Genomic Selection and Identification of Causal Regions Associated with Resistance to Stenocarpella Maydis in Maize Lines Using Dartseq Markers.
Poster Number 508
See more from this Division: ASA Section: Global Agronomy
See more from this Session: Global Agronomy: III
Wednesday, November 18, 2015
Minneapolis Convention Center, Exhibit Hall BC
Abstract:
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 of 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 causal regions 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 in clusters in order to indentify groups related
to resistance to Stenocarpella maydi and use Bayesian stochastic search variable
approach to indentify causal regions related to resistance to ear rot.
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;
however, the BSSV method was superior in the identification of resistance regions.
Three markers highly associated with resistance to Stenocarpella maydis were
identified, and they were all located within or very close to genes that act directly or
indirectly on mechanisms of resistance to maize diseases.
Our work showed that is possible to select maize lines presenting high resistance
to Stenocarpella maydis. This claim is based on the high level of predictive accuracy
obtained by GWAS using different models. Furthermore, the lines related to
background Suwan present higher level of resistance than lines related to other groups.
Three sequences related to significant markers presented a fine association with
mechanism of resistance in genes linked to Cytokinin dehydrogenase, Peroxidase
activity and G Proteins.
See more from this Division: ASA Section: Global Agronomy
See more from this Session: Global Agronomy: III