Browsing by Person "Han, Sen"

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Gibberella ear rot resistance in European maize : genetic analysis by complementary mapping approaches and improvement with genomic selection
(2022) Han, Sen; Melchinger, Albrecht E.
During the last decades, implementation of molecular markers such as single nucleotide polymorphisms (SNPs) has transformed plant breeding practices from conventional phenotypic selection to marker-assisted selection (MAS) and genomic selection (GS) that are more precise, faster and less resource-consuming. In this dissertation, we investigated these three selection approaches for improving the polygenic trait Gibberella ear rot (GER) resistance in maize (Zea mays L.), which is an important fungal disease in Europe and North America leading to reduced grain yield and grain contaminated with mycotoxins such as deoxynivalenol (DON) and zearalenone (ZON). Three different sets of materials were evaluated in multiple environments and analyzed for different objectives. In the first study, five flint doubled-haploid (DH) families (with size 43 to 204) inter-connected at various levels through common parents, were generated in an incomplete half-diallel design with four parental lines developed by the University of Hohenheim. Significant genotypic variances and generally high heritabilities were observed for all three traits (i.e., GER, DON and days to silking (DS)) in all families, implying good prospects for resistance breeding and phenotypic selection against GER across different environments in European maize germplasm. Genetic correlations were extremely tight between DON and GER and moderately negative for DS with DON or GER, suggesting that indirect selection against GER would be efficient to reduce DON, but maturity should be considered in GER resistance breeding. Using a high-density consensus map with 2,472 marker loci, we compared classical bi-parental mapping of QTL (quantitative trait locus/loci) with multi-parental QTL mapping conducted with joint families and using four different biometric models. Multi-parental QTL mapping models identified all and even further QTL than the bi-parental QTL mapping model conducted within each family. Interestingly, QTL for DON and GER were mostly family-specific, yet multiple families had several common QTL for DS. Many QTL displayed large additive effects and most favorable alleles originated from the highly resistant parent. Interactions between detected QTL and genetic background (family) were rare and had comparatively small effects. Multi-parental QTL mapping models generally did not yield higher prediction accuracy than the bi-parental QTL mapping model for all traits. In the second study, two diversity panels consisting of 130 elite European dent and 114 flint lines, respectively, from the University of Hohenheim were evaluated and subject to a genome-wide association study within each pool. Similar to the first study, highly significant genotypic and genotype × environment interaction variances were observed for GER, DON and DS. Heritabilities were moderately high for GER and DON and high for DS in both pools. Estimated genomic correlations between pools were close to zero for DON and DS, and slightly higher for GER. The detected QTL for DON were all specific to each heterotic pool and none of them was in common with previously detected QTL. Furthermore, no QTL was detected for GER and DS in both pools. Genomic prediction (GP) across pools yielded low or even negative prediction accuracy for all traits. When the training set (TS) size was increased by combining lines from both heterotic pools, the combined-pool GP approaches had no higher prediction accuracy than the within-pool GP approach. Different from expectation, method BayesB did not outperform genomic best linear unbiased prediction (GBLUP). In the third study, we analyzed two backcross (BC) families derived from a resistant and a susceptible recurrent parent. Both BC populations differed substantially in their means for all traits, suggesting that the two recurrent parents have different QTL alleles for GER resistance. Relatively high correlations were observed between DON and ZON concentrations measured by immunoassays and GER visual severity scoring and NIRS (near-infrared spectroscopy) within each BC population. Thus, the mycotoxin content in grain can reliably be reduced by directional selection for GER severity and NIRS measurements that are less expensive and less laborious. In conclusion, GER resistance in European maize germplasm can be effectively improved through breeding with resistant donor lines. GER visual severity scoring and NIRS measurements were found to be reliable predictors for DON and ZON concentrations in grain. We observed that QTL for GER and DON are mostly specific to a few families or a limited number of materials, whereas QTL for DS are more commonly shared between families. The multi-parental QTL mapping approach is complementary to the classical bi-parental QTL mapping in that the latter has generally higher power to identify rare but large-effect QTL for traits such as GER and DON, whereas the former is superior in detecting common but small-effect QTL for traits such as DS. Composing the TS with materials more closely related to the prediction set and increasing the TS size generally resulted in higher prediction accuracy for MAS and GS, irrespective of the trait and statistical model.